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廉政文化建设研究综述

廉政文化建设研究综述曲晓楠（齐鲁工业大学，山东济南250353）摘要：随着党中央反腐倡廉工作的不断深入开展，廉政文化建设在反腐倡廉道路上的重要性也日益凸显。

学者们围绕廉政文化的相关问题进行了大量的研究，达成一定共识，取得阶段性成果。

通过对学者的研究成果进行概括和梳理，本文从廉政文化的内涵、作用及廉政文化建设面临的挑战等方面进行归纳，以期从中吸取教训，总结经验，为日后新时代廉政文化建设做出一些参考。

关键词：廉政文化；建设研究；反腐倡廉中图分类号：D602文献标志码：A文章编号：1674-9324（2014）35-0136-02探索；重视我院金工实习和毕业实习，切实考核学生实践技能；充分发挥产学研合作单位的作用，真正落实学生实习基地的作用；鼓励支持在校学生参加学科竞赛，以赛促学。

3.做好大学生职业生涯规划和就业指导工作。

大学生职业生涯规划和就业指导工作在很多学校并不完善，建议：加强就业指导师资队伍建设和人才培养，提高从业人员专业化和职业化，为促进大学生就业提供一支高素质队伍；完善课程体系，扩宽教学内容，丰富教学方式，健全课程考核体系，提高课程时效性。

除此之外，还需进一步做好就业服务工作：举办招聘会和引进校园招聘的企业无论从数量和质量上都有待提高；多邀请有实务经验的企业人才来校开展讲座，增加学生对就业市场的了解；组织学生之间、学生和师兄师姐的学习就业方面交流，增加求职和就业经验。

4.重视第二课堂，丰富课外活动，提升学生就业素质。

大学生的就业能力不单纯指某一项技能、能力，而是学生多种能力的集合，这一概念是对学生各种能力的全面包含。

在内容上，它包括学习能力、思想能力、实践能力、应聘能力和适应能力等。

这些能力的获取必须依靠学生在实践活动中获取，由此可见，我们应当重视第二课堂对就业能力培养的重要作用，建议：多开展文化、体育、艺术、社会服务类的活动，为学生提供一个全方位展现个人能力的平台，发掘每个学生的特长，提高个人综合素质；对于参与活动不积极的学生，辅导员应多给予关注，鼓励他们加入社团，融入到集体活动中，提高沟通和表达能力，强化团队合作精神；支持各项社团的创办，培育社团文化，培养学生特长和兴趣；尤其鼓励各项科技类竞赛类和职业大赛类活动，科技竞赛类有利于学生培养实践能力和创新精神，而且有助于全校形成良好学风，而职业大赛活动则可以让学生提前感受职场氛围，提升就业能力。

电视高压包型号通脚查询

电视高压包型号/通脚查询BSC29-1081G FBT-B-31 海尔29F7A-T JF0501-21933BSC29-0197F 123/456BSC29-3807-22BSC29-0115G JF0101-83851 高士达25"带电容双聚焦123/4679 BSC25-N0864 37-FBA0002-CAA0E 051012-51 JF0501-3215 37-FBA001-CAAOC 129/346710BSC25-0277D 37-SC2502-77D01 1310/45679JF0101-81813 海尔135/46789BSC26-2606S 1LB4L40B06800 L40B07800 124/3568910BSC29-01B25 创佳8696LTTFB3092AD 123/4910BSC29-0109Y 5132-051232-00 创维32T88HSTLF14453B 松下29v1R 145/678/910BSC25-N2303B 普通双聚焦秦栏嘉华做 JAVA 假松下1210/34567BSC25-C2904 海信TC2517 JF0101-0115 高路华的行包2518 124/58910JF0501-21933 29" 海尔单聚焦BSC25-01N40L5 T111470 BSC25-01N4016C T111053 直接代用BSC25-01N40L4 123/4910BSC29-0115Q 32D90HTBSC25-01N4034CZTFK07011A ZTFK07009A 高士达25″松下32WG 25G 128/3457BSC29-3956 BSC26-0409H 123/456910BSC25-05N2110 12345610/78BSC30-0806 30000352 T2993N BSC30-0812 30000 017 BSC30-N2504 双聚焦大骨架康佳T3888N 123/45679108-598-848-00, 1-453-354-11, NX4010 M3Q4 SONY背投13929012B 308 205515109-053859-49BSC31-0103F SVA 高士达25″ BSC31-0104D T111067 SVA 带电容高士达25" BSC28-1931 T111060 BSC24-2640S T111068 SV A34" 123/467/5910BSC31-0103C T111062 高士达25″JF0501-19290 TCL 普通货1310/45679BSC29-22B BSC25-21R BSC25-01N4012D 13/458101-453-160-13 SONY背投分压盒 1-453-108-11 12JF0501-90828 BSC25-0244 BSC25-1192F FBT-A-06HT-2199D JF0501-19809 12/345BSC27-01A(K) 58-66478-01 康力CE6468A电视25"用 BSC25-5602 123/567910BSC25-3565S 熊猫C2580BSC26-N0301K BSC25-21R 创佳普通单聚焦富华做 BSC25-02AW36 13/45810BSC30-1088D 高士达25″双聚焦1234/56/7910BSC24-2616S 1LB4L40B05300 三洋CKM2589-0BSC27-0327C 天华产组装机25" 单聚焦123410/78BSC29-0128 37-BSC290-128 高士达25″ TCL2912 12/458TFB4002AD 东芝单聚焦123/4567910BSC29-3802-24R 普通双聚焦123/47910JF0501-19910A FBT-A-14 BSC25-0281C CF0801-5426 BSC25-1192E 、 BSC25-4801、BSC25-0251 BSC25-0273B A3 110V BSC25-3304 BSC25-01BW5 BSC25-1505 BSC25-N0307BSC31-1937 BSC33-0803 配夏华带电容高士达 25" 厦华MT-29F1 13/456JF0101-83867 配海信带电容高士达 25"BSC28-N2317 123/469BSC30-N2535BSC29-0106BBSC29-0128EBSC24-3105BSC29-0197BBSC25-02AW52BSC29-3929BSC29-0196E 37-SC2901-96EOX 带电容高士达 25"BSC29-3807-43 5100-051434-02 带电容高士达25"4410Z-A001L LG 变压盒 1根线100BSC29-0134A 带电容高士达 25" 123/45/6710BSC31-0101F 带电容高士达 25"F1364CE 夏普134/268F1438CE 夏普127/3456810F1491CE 夏普137/24569/1011F1493CE F1584CE 夏普148/356710/1112F1584CE F1491CE 夏普137/24569/1011F1607CE 夏普149/356710/1112F1856CE 夏普134/257910F1903CE/2311AS 夏普149/356710F1952CE 夏普149/356710AT2090/33 显示器飞利蒲46710/35/12小金星23/579/810小金星23/579/810BSC25-8301 BSC25-8302 新飞利浦21″ BSC23-2370K 127/356/910JF0208-0220 BSC23-0901XB 星宝1538 =970# BSC23-0201XB 123/4567 BSC28-7605 幸福29″123/456/7810熊猫2118A 123/468BSC25-2355DA 熊猫2528 BSC25-N1806 BSC25-3355D BSC25-3355C BSC25-1059B BSC25-1059S BSC25-1059C 123/46810BSC29-0102 德州三和产 KF58371N 熊猫29”12/345/6710BSC25-3355-1 BSC25-3355RF BSC26-01N40G 熊猫2977 123/46910 BSC24-2004S FCM-20B027 熊猫54P5 123/45679熊猫64P3 1210/34567游戏机22″191012/23458游戏机25″91012/23458游戏机CFT-715 12910/23457813/24789/10111212/3456/8910139/4568BSC27-0501 高路华123/4567910BSC75I3 123/45679BSC25-N1508 海信TC2961A 124/58910 6174Z-8006A 129/37810/45BSC27-0501T 5104-051029-00 BSC25-2682S5118-051029-00 JF0101-0166 5101-0 51029-00 BSC28-1916 5114-051029-00 1210/39/4567BSC21-2665S 1LB4L40B00900 124, 38910BSC25-N1508 BSC25-3358 BSC25-4101 夏华21" 12458/3910 BSC25-1059T 1210,34567KFT4AX242F2 松下tc-29p20r 1210,45,3671172.0128 仪器高压包1234.691BSC29-0146 高清，带电容海信123.456791BSC73D 普通双聚焦123/4567910BSC73Z 普通双聚焦带变压块 PF3495 123/4567910BSC28-0702 30001292 BSC26-N1001K 123/4568910BSC28-0726 30001622 普通双聚焦 BSC26-N2004K 123/4810 BSD70B 长虹HP38A1 BSD70B、BSC70C 长虹HP5175背投高压包12/45910BSD70A 123/4569BSC75W BSC75S 双聚焦123/4567910BSC75N 双聚焦123/4679BSC75C 单聚焦 BSC75M 代用123/4679BSC75L 单聚焦123/4679BSC73Y 双聚焦123/4567910BSC70B 123/4567JF0101-01801 135/6789BSC25-3310 T111450 金星2518B 13/49108-598-816-10 带电容123/45/6789BSC29-3807-39 5109-051425-00 25T98HT 带电容，双聚焦 BSC27-0123S 5132-51425-00BSC68Q 123/4679BSC29-0147 普通单聚焦原装BSC29-3319 5114-051229-00 123910/4567BSC30-1080G 12/456710JF0501-2165 58-68618S- 1 2002070110 128/3567BSC29-1081E HP-2999A BSC29-0160 135/6789BSC23-2370K 21D8 25-8301 127,3456,910MC-FBC-002 039-00801-006-6 T-10420 单显58910/67BSC30-N2506 海信高士达25"带电容 TF3488D TF3482E JF0101-83818 1210/45689100-4150D 定做仪器高压包珠海南科BSC30-N2506 金海29″123/45689HVG/32663 DTV 5138-051850-01BSC29-0186G BSC30-N2567 JF0101-83802 高士达25"带电容 BSC29-01N4036B 123/4679BSC31-18J 123/45679106174Z-6103J 128/345710BSC31-18G 123/4567910JF0101-01150 5101-051434-07 13/467910BSC28-5305C 普通双聚焦嘉华29“125/3467910BSC28-0638 30002212 单聚焦纯平13/248/56910CF0801-7401 高士达25"带电容123/467910BSC29-0118W 37-SC2901-18W01 高士达25"带电容145/681011JF0101-81831 FBT-B-14 BSC29-0139D FBT-B-1 4 BSC29-0139F 海尔29F2A-S 纯平单聚焦FBT-C-06 123/456JF0101-19991 6174V-6016A 带电容，单聚焦123/46910JF0101-85027 松下背投海尔12/69BSC25-0299D 37-SC2502-99DOX BSC25-0211 37-SC2502-99D0X BSC25-0299D 124/356810JF0501-19504 30001473 123/4568910BSC29-0138D 5132-051309-05 带电容 BSC29-0138G 5100-051309-07 5132-051309-07 123/467BSC70Y 单聚焦带变压盒 BSC70X1 123/4567910BSC73M 普通双聚焦123/45679BSC73L 普通双聚焦123/4567910BSC70K 单聚焦带变压盒 SF2911 长虹SF3411F 123/4567910BSC29-0138 海尔D29FV6-A CF0801-7402 高清带电容123/4567910BSC73W 普通双聚焦 BSC73W1 123/4567910BSC70J 123/456910BSD69X 长虹 JP5186 BSC70E 12JF0101-01810 FBT-B-15 BSC29-0130F 1210,4568BSC29-3807-30 单聚焦带电容123/4579FUW-50A0036174V-5003A BSC28-N2325 BSC28-N2312 6174V-5003L BSC28-N2334 6174V-6003L 125/ 346810TFB5067AD 高士达25" 123,5789BSC25-0820 福利牌12/568910BSC29-3706 BSC26-01N4016H SVA D2957F 123 /456910BSD70A-1 三枪大背投123/4569CF0801-5402 123，45679BSC30-0913 ******** P3409T 13/24689101072.0294 小监视器高压包2356/410/789BSC29-3970V 普通双聚焦123/457910BSC23-2682S 1LB4L40B05100 高士达25”配三头1234/56910BSC25-5402 ZTFK82003A 松下 TC-2118A 12/457/689BSC28-0633 30000962 T2581C F2509C1 123/4568910JF0501-2505P 37-F05012-505 124,3567,8910 BSC29-0402 V2966G 1210/3456BSC29-0149Q 37-SC2901-94QOXFLK-29A081 1234/56791019.70040.001 FEA578 高士达25”配三头12/458JF0101-01844 日立25″129/34568BSC30-0906 ******** BSC30-086/A 123/46810BSC30-0870 ********BSC30-0907 30001752 P29FM186BSC26-N2003K 康佳P29FM216 EK19801 13/4568910BSC30-0850 30001753 双聚焦康佳的机型是P29FM105 123/4568910BSC30-0940 30001932 单聚焦 BSC30-0938 13/24568910 BSC30-0942 30001934 双聚焦13/24568910 BSC30-0903 ******** 双聚焦123/4568910BSC30-0826 ******** 双聚焦 BSC26-N2011K 13/24810BSC23-2684S 30001642 BSC23-027/A 双聚焦 P2902M P2905M 123/4810TFB4122AH 东芝2970XHEJF0101-2746A JF0101-2746 5100-051434-33 5100-051434-32 普通双聚焦 5线1210/39/4567JF0101-85003 242253162502 12/910/4567BSC14-01N1022 亿佳黑白高压包定做BSC20-0823 5732026A 12/568910BSC28-0724 ******** 1234/8910BSC24-09F 12/3456"BSC28-N2377 5100-051379-00 高士达25""带电容单聚焦" 123/4579BSC24-01N4016J 123/4910BSC25-N0104R1 58-67496-06R1 康力29"BSC25-2063S 12346/5910JF0101-85927 海信3406D 普通双聚焦123/467910BSC29-0178 TC-29P100GJ 松下34P68G KFT4AV184F TC-34P68G 123/56/89BSC28-2683S 康佳3498JF0101-83842 双聚焦高士达25"BSC29-0501AB 1234/56/7910BSC29-0151D 松下52背投 BSC29-0143D BSC29-0151A KFT7AA334F1 KFT7AA334F2 12 3/89BSC29-0189A 37-SC2901-89A0X 高清带电容双聚焦 TCL-HiD291S 可以用BSC29-0184A 代换把管座2个连起来。

2SK2906-01中文资料

160 240 ns
150 230 ns
100
A
1,0 1,5 V
85
ns
0,21
µC
- Thermal Characteristics Item Thermal Resistance
R th(ch-c) R th(ch-a)
Symbol channel to case channel to ambient
↑ 8
↑↑ 9
VGS [V] IF [A]
VDS [V]
→ VDS [V]
Maximum Avalanche Energy vs. starting Tch
Eas=f(starting Tch): VCC=24V; IAV ≤ 100A
→ Qg [nC]
Safe Operation Area
ID=f(VDS): D=0,01, Tc=25°C
BV DSS
ID=1mA
VGS=0V
Gate Threshhold Voltage
V GS(th)
ID=10mA
VDS=VGS
Zero Gate Voltage Drain Current
I DSS
VDS=60V
Tch=25°C
VGS=0V
Tch=125°C
Gate Source Leakage Current
N-channel MOS-FET
60V 7,8mΩ ±100A 150W
> Outline Drawing
> Applications
- Motor Control - General Purpose Power Amplifier - DC-DC converters

康佳彩电高压包机型对照表

康佳彩电高压包机型对照表(2011)编号型号应用 (代表) 机型BSC30-063/A T3498BSC25-2684S T3898BSC25-067/A P2156EBSC25-2620S T3498ID P2999ID T2999BSC31-064/A A2986 P2916 A2991 A2910 配三星管BSC25-2618S T2999 A2981 T2912 T2912BCBSC30-0823 DT298 A2986 A2991 P2916 A2910 配东芝管BSC30-0827 P3492IDBSC30-0828 P2982C P2986C P2990C P2992C P2990NBSC30-0830 P3486CBSC30-0829 P2982C P2986C P2990N P2990C P2992CBSC29-067/A P2982C P2986C P2990C P2992C P2990NBSC28-0634 T3472C T3466C T3477CBSC28-0830 P3492C 配东芝管BSC25-0126 P2190E1 P2190E P2156E 配彩虹、赛格、三星管BSC25-0125 T2176K T2168K 配彩虹管BSC30-0914 P2929 P2990E 配LG管BSC30-079/A P2901 配彩虹、东芝管BSC29-076/A P2562K P2960K P2961K P2962K P2962K1 (单聚焦) BSC29-076/A T2968K T2975K T2976K 配LG管、彩虹管BSC29-077/A T3468KBSC21-2068S T3466E 配金星、赛格管BSC P3460K 配东芝管BSC21-2074S P2960K P2961K P2962K P2962K1 (双聚焦) 配三星管、华飞管、永新管、LG管 BSC25-N2702 P2162K P2179K 配三星、华飞管BSC-30-0816 T3412ID 汤姆逊管BSC-30-083/A P2901 配北松管BSC-25-0129 T2168K T2176K 配福地管BSC-25-0129 P2162K P2179K 配北松管BSC26-N2306 P2960S P2961S P2971S P2972S P2967S （双聚焦）配华飞、永新、LG管BSC28-070/A P2960S P2961S T2975S T2976S T2973S BSC28-070/A P2971S P2972S 配彩虹管、北松管、汤姆逊管BSC28-070/A P2572S P2571S 配彩虹管BSC22-025/A P3460K 配北松管BSC JF0501-004 P2171S P2172S 配三星、华飞、北松管BSC JF0501-004 T2173S T2176S 配北松、华飞管BSC JF0501-002 T2173S T2176S 配三星,彩虹,金星,永新,赛格,福地管BSC22-026/A P3460K 配三星、北松管BSC28-070/A P2967S P2571S T3476S 配北松、彩虹管BSC22-022/A P3460T P3409T P34FT189 配北松管(细)、华飞管BSC23-023/A P3460T P3409T P34FT189 配三星管BSC22-027/A P2902M LG-PHILIPS管BSC23-028/A P3460T P3409T 配东芝管BSC30-078/A P2902T P2906T 配北松管BSC23-025/A P2902T P2906T 配彩虹管BSC23-027/A P2902M P2905M 配LG管BSC30-086/A P2958I P2902I P2916I 配永新管、LG管BSC30-088/A P2958I P2902I P2916I 配北松管BSC23-026/A P2903T P2908T P29FT188 配永新、LG管BSC30-089/A P2903T P2908T 配LG-PHILIPS管、彩虹BSC26-053/A P2572S P2571S 配LG管、三星管BSC22-024/A BT5080 BT4310 BT5080H BT4310L BT4320HBSC25-086/A P2156E(配北松管) T2176E T2169ET2877X、T2979X、T2983N、T2989N、T2977BT2977X、T2979X、T2983X、T2989N、T2989X、T2979X、T2983N、T2989M、T2989N1、T2987BT2983X、T2989M、T2989X、T2987BF2968D、F2968D/G、F2977D、F2979D、F2980D、F2977D1、F2977D2/G、F2979D2/G、F2977D/G、F2979D/G、F2980D/G、T2979D1、F2982D2/G、T2986D1、F2977D2、F2979D2、F2982D2、T2982D1、T2530D、VT298T2983X、T2983L、T2985L T3488N、T3488PT3472B、T3472B1、T3477B、T3482B、T3487B、T3487B1、T3487N、T3477N、T3477N2 T3477B1T3877N、T3877N2T2888ND、T3888NIT2110T953FSⅡT953FSⅡT2111T1437D2、T3731D1、T3733D1、T3731D、F1437D5、K1437C、T1437D2/G、F1437D5/G、T3732D、T3735D、T3736D、T3731E1T1517T3731E1T1726T3731E1T2528H、T2583H、T2583H1、T2587H、T2587L、T2588N、T2588N2、T2588X2、T2588X6、T2588XT953ST2106T2106T2120T5471K、T5466KT2128T2108E、T2128AT5401AT2510、T2512AT2510T2516T2510T2588T2528H、T2583H、T2583H1、T2587H、T2587L、T2588N、T2588N2、T2588X2、T2588X6、T2588XT2588N、T2588N2T2587H、T2588N、T2588N2、T2588X2、T2588X6、T2583H、T2583H1、T2587L、T2588X、T2588X2、T2588X6、T2518T2506T2977BT2988P、T2998NI、T2998N、T2998NDST2989、T2985H、T2988L、T2989N2、T2991H1、T2983H、T2985L、T2989H、T2990L、T2991L、T2983L、T2988H、T2989L、T2991H、T2991L1、T2989L、T2989H、T2991L、T2991H、T2991H1、T2992NK1418LF、K14718NF、T3731E1F2132D4、F2132D4/G、F2133D4、F2135D、F2135D4、F2135D4/G、F2137D3、F2137D3/G、F2137D5、F2139D、F2139D/G、F2139D2、F2139D3、F2139D3/G、F2139D4、F2139D4/G、F2139D5、F2139D5/G、F953D、F953D4、F953D4/G、F953DA、F953DA/G、F953DB、F953DB/G、T2136N、T2169B、T5471NF2977D、F2979D、F2980D、F2977D1、F2977D2/G、F2979D2/G、F2977D/G、F2979D/G、F2980D/G、T2979D1、F2982D2/G、T2986D1、F2977D2、F2979D2、F2982D2、T2982D1、T2530D 021-T2587D、T2587D1、T2530D显示器15寸ZXI-03 K2979H3、T2991GT3498T3898T2966L、T2983L、T2980H、T2985H、T2985L、T2989L、T2990L、F2980LT2983XF2131D/G、F2135D4、F2139D5、F2131D、F953DB/G、T5429D1、F2131D4、F2135D4/G、F2139D5/G、T2132D、F953DB、T5471N、F2131D4/G、F2137D2、F5428D、T2133D、F953D4/G、T953D、F2132D、F2137D5、F5428D/G、T2135D、F953D/G、T5429D、F2132D/G、F2137D5/G、F5428D4、T2136D、F2131D、T5428D、F2132D4、F2139D、F5428D4/G、T2136N、F953D4、T5428D1、F2132D4/G、F2139D/G、F5429D、T2137D、F953D、F5429D4/G、F2133D4、F2139D2、F5429D/G、T2137D2、F2135D/G、F2135D、F2139D4、T2139D4/G、F5429D4、T2139DF2519D1、F2518D、F2520D3、F2530D/G、F2581D2、F2519D1、F2519D3、F2518D2、F2528D/G、F2530D2、F2581D2/G、F2520D、F2519D、F2528D2/G、F2531D/G、F2582D、T2530D1、F2520D/G、F2519D/G、F2528D2/G、F2531D2、F2587D1/G、T2519D1、T2519D2、T2531D、T2580D、T2586D、T2587D1、T2587D2、T2589D、T2587DF2132D4、F2132D4/G、F2133D4、F2135D、F2135D4、F2135D4/G、F2137D3、F2137D3/G、F2137D5、F2139D、F2139D/G、F2139D2、F2139D3、F2139D3/G、F2139D4、F2139D4/G、F2139D5、F2139D5/G、F953D、F953D4、F953D4/G、F953DA、F953DA/G、F953DB、F953DB/G、T2136N、T2169B、T5471NT2991H、T2990L、T2991H1、T2992NF2519D1、F2518D、F2520D3、F2530D/G、F2581D2、F2519D1、F2519D3、F2518D2、F2528D/G、F2530D2、F2581D2/G、F2520D、F2519D、F2528D2/G、F2531D/G、F2582D、T2530D1、F2520D/G、F2519D/G、F2528D2/G、F2531D2、F2587D1/G、T2519D1、T2519D2、T2531D、T2580D、T2586D、T2587D1、T2587D2、T2589D、T2587DT2979X、T2979X1、T2989NI、TT2977X、T2989XT2977X、T2979XT2983X、T2989M、T2989X、T2987BT2982D1T3289WT3289W1F1437D5/G、F1437D5、T1437D2、T3731D、T1437D2/G、T3731D1、T3732D、T3733D、T3733D1、T3735D、T3736DT953P3DT218E、DT218ES、P2156E、P2190E、P2190E1、P2190N、A2186E、A2186N、DT216E、DT216ES、F2109E、F2109E/G、F2109E2、F2109E2/G、F2133A1、F2135A1、F2136A1、F2139J1/G、T2109N、T2139N、T2166E、T2166E1、T2166N、T2169N、T2188E、T5471NWF2518D、F2518D2、F2519D、F2519D/G、F2519D1、F2519D3、F2520D、F2520D/G、F2520D3、F2528D/G、F2528D2/G、F2530D/G、F2530D2、F2531D/G、F2531D2、F2587D1/G、F2968D、F2968D/G、F2980H、F2980LF2519D1、F2518D、F2520D3、F2530D/G、F2581D2、F2519D1、F2519D3、F2518D2、F2528D/G、F2530D2、F2581D2/G、F2520D、F2519D、F2528D2/G、F2531D/G、F2582D、T2530D1、F2520D/G、F2519D/G、F2528D2/G、F2531D2、F2587D1/G、T2519D1、T2519D2、T2531D、T2580D、T2586D、T2587D1、T2587D2、T2589D、T2587DT3472D、T3472N、K3477LFP2992N、T2993N、P2993NT2982D1、T2988D、T2991D、T2989D、T2991D1、F2980HT2998NST2989、T2986H、T2989L、T2990L、T2988HT2977X、T2979X1、T2979X、T2989X、T2992NT2983X、T2983L、T2985LP2993NP2992N、T2993N、P2993NP2982N、P2987N、P2989NP2993NT3289WT3472B、T3472B1、T3477B、T3482B、T3487B、T3487B1、T3477NP2987NT3289WP2992N、T2993N、P2993NT3888N2、T3888NDT2131F，T2136GT1437D2、T1437D2/GK2588A2、K2588A2（SKD）、K2588C、K2588D、K2588G、K2588T、K2588TA、K2588TS P3492NF2109C、T2166C1、T2166CITV2912、T2912、T2912BC、T2999、P2999ID、T3498IDA2910、A2911、A2986、A2991、DT298、PD292、P2992ID、P2999ID、P2916、P2986、 ITV2912、T2912、T2912BC、A2981、T2999A1488E/G、A1486E/G、T1437AF2587E、F2587E/G、T2525N、T2566B、T2566E、T2566E1、T2566E2、T2566E3、T2566E5、T2566E6、T2569E、T2569N、T2580E、T2588ET2131F、T2132F、T2133F、T2135F、T2136F、T2136GP2592E、P2592N、P2591N、P2590EDT138M、DT138MW、DT138U、DT138UW、DTO138UP3489N 与30-0814一样用HR3093U、HD3098UA2910、A2911、A2991、P2916F2509C、F2580C、F2581C、F2581C1、F2586C、F2589C、ST2580、SY2580CP2987N、P2989NF2979AT2909C1、T2966C1、T2983C、T2985CDT148、DT148E、DT148ES、KDT148A2981C、K2966S、T2909C、T2965C、T2966C、T2969C、T2988C、T2989C、T2990C、T2990NT、T2991C、T2992CF2518A、F2528A、F2530A、F2531A、T2531A、T2566A、T2566R、T2590R、F2968A、F2980A、F2982A、F2982A3T2589C、F2580CA1486E、A1486E1、A1486N、A1488E、A1488N、A1488E1DT348、P3492IDHD3098UA2971C、DT298CS、P2982C、P2986C、P2990C、P2990N、P2992C、P2992C1P3492C、P3486CDT298CS、P2982C、P2990N、DT298CS、P2982C、P2990C、P2990N、P2992C、P2992C1T2909C、T2965C、T2969CT3468C、T3472C、T3477C、T3466C、K3472EYP3486C、P3492CP2190NDT208UT2569E、T2566E、T2566E2、T2566E3、T2566E6、T2588E、T2566E5FL3299UF2509C、、F2509C1、F2566C、F2566C3、F2580C、F2581C、F2581C1、F2586C、F2589C、F2509C1、T2566C、T2566C3T2166R、K2169TQ、K2169TQ1、K2169TQ2、K2169TQ3P2165E、P2172E、P2190E、P2190E1T2168N、A2176K、A2176N、T2180KP3211、PR2992F953A、K2180D9T2168E、A2176ET2166R、T2168K、K2106TQT1476A、T1473A、A14SE086F2509A、F2565、T2522E、T2525、T2526A、T2563A、T2563E、T2566A2、T2566E2、T2566E3、T2566E5、T2566E6、T2569A、T2569E、T2580E、T2588AA2176E、T2168EDT-21K5P2556E、P2590E、P2591N、P2592E、P2592N、T2922E、T2969E、T2969N、T2980E、T2988E、T2989EP2551A、F2509A、F2565、T2526A、T2563A、T2566A2、T2569A、T2588A、F2909A、F2909A1、F2965、T2966A2、T2988A、P2951A、F2968A1、F2979A1、F2980A1、F2982A1、T2927AP2929、P2951A、P2956E、P2990EP2901T、P2902TF2587E、F2587E/G、T2525N、T2566B、T2566E、T2566E1、T2566E2、T2566E3、T2566E5、T2566E6、T2569E、T2569N、T2580E、T2588ET2568KP2902、P2901P2562K、P2562V、P2579K、T2968K、T2976K、P2928、P2960K、P2961K、P2962K、P2962K1、P2962V、P2979K、P2998KT3468KP2928、P2960K、P2961K、P2962K、P2962K1、P2962V、P2979K、P2998KT3466EP2162K、P2179KP2162K、P2179K、T2168KP2960R、P2961S、P2962R、P2962S、P2967S、P2971S、P2972S、P2977S、P29SE072、P29SE077、P29SE151、P29SE186、P29SE281、P29SE282、P29TE282、P29TE661、P3460SP2571S、P2571SN、T2920S、T2922S、T2926、T2968R、T2973S、T2975R、T2975S、T2975SN、T2976S、T2978S、T29SE073、P2960R、P2961S、P2962R、P2962S、P2967S、P2971S、P2972S、P2977S、P29FS061、T3476S、T34SK076、T3473SA1386UM、A14SE086、DT14SK008、DT0138UY、T14SA073、T14SA076、T14SA128P3211P3409T、P3460T、P34FT189P2916SP21SK566、P21AM390、P21SA281、P21SA282、P21SA376、P21SA383、P21SA387、P21SA390、P21SE071、P21SE151、P21SE282、P21TE569、P21TE661、T2126PPD、T2173S、T2176S、T21SA026、T21SA073、T21SA120、T21SA236、T21SA267、T21SA326、T21SE358、T21SK022、T21SK026、T21SK026T、T21SK068、T21SK076、T21SK078、T21SK120、T21SK236、T21SK267、T21TE358、T21TE569、T21TE661KP2951AXTBT4320H、BT4301、BT4310、BT4310H、BT4310L、BT4320、BT4360H、BT4380H、BT5060H、BT5080、BT5080H、BT5080L、BT5090、VW4301、VW5001、VW4301T25SK068V、T2520S、T2522S、T2526、T2576S、T2578S、T25SE073、T25SE120、T25SE267、T25SE358、T25SK026、T25SK068、T25SK076、T25SK120、T25SK569、T25TE267、T25TE358、T25TE661、T2927SSP21SK391、SP21SK520、SP21SK529、SP21SK529V、DT15SK203P、P15SK107、K20SA201U、A21SE090、DT21SK003P、P2171S、P2172S、P21AM390、P21SA281、P21SA282、P21SA376、P21SA383、P21SA390、P21SE071、P21SE072、P21SE151、P21SE282、P21SK056、P21SK056V、P21SK177、P21SK383V、P21TE569、P21TE661、SP21TK520、DT21SK008、T2176S、T21SA073、T21SA120、T21SA236、T21SA267、T21SA326、T21SE358、T21SK022、T21SK026、T21SK026T、T21SK068、T21SK076、T21SK078、T21SK120、T21SK236、T21SK267、T21TE358、T21TE569、T21TE661P2571S、P2571SN、P2572SKP2190C、KP2190C（SKD）P3460KT2522E、T2525、T2563EP3409T、P3460T、P34FT189P2902MP2902I、P2916I、P2958IP2151A、P21FA071、P21FA281、P21FA282、F2100、F2100A、F2109A1、F2165、T2120A、T2121、T2122A、T2123、T2126A、T2126A2、T2173A、T2178A、T2188A、T21FA236、T21FA267P2156E、P2172E、T2163E、T2169E、T2173E、T2176E、T2180EP2156E、P2172EP2902TP3438S、P34SE138、P34SK138VOD、P34SK383P2903T、P2908T、P29FT188P2902MP29SK061P3409T、P3460T、P34FT189P2902I、P2916I、P2958IP25SE071、P25SE072、P25SE151、P25SE281、P25SE282、P25SK062、P25SK071、P25SK151、P25SK151V、P25SK151VOD、P25SK282V、P25SK376、P25SK383、P25SK387、P25SK569、P25SK569V、P25TE282、P25TE661、T25SK026、T25SK068、T25SK068V、T25SK076、T25SK120、T25SK569、T25SE073、T25SE120、T25SE267、T25SE358、T25TE267、T25TE358、T25TE661、P29TK281、T29SE073、T29SK068、T29SK068V、T29SK076、T29SK076T、P29SE072、P29SE077、P29SE151、P29SE186、P29SE281、P29SE282、P29SK067、P29SK077、P29SK151V、P29SK151VOD、P29SK282、P29SK282V、P29SK376、P29SK383、P29SK387、P29SK569、P29SK569V、P29TE282、P29TE661、P29TK383、K29AM281、T29SK120、T29SK178、P31SE292P2903T、P2908TP2902TT34SK068、T34SK073、T34SK073P29FM105、P29FM216、P29FM186、P29FM296、P29FM297、P29TM296、P29TM297、P29TM319P2905M、P29FM105、P29FM216P28FG298、P28FG298U、P28ST319、P30ST319、P30TM319、P25MV281VOD、P25MV390、P25MV281、P25MV281V、P25ST390、P29MV281VOD、DC29FG297、DT29MV297、P2916M、P2919、P29217M、P29FG058、P29FG108、P29FG108U、P29FG188、P29FG188U、P29FG282、P29FG297、P29FM296、P29FV103、P29MV102、P29MV103、P29MV217、P29MV281、P29MV281V、P29MV390、P29SG108、P29SG188、P29SM296、P29ST217、P29ST390T1476A、T14FA073、T14FA128、T3731AP32FG298、P32FG298U、P32TM319H、P34FG109、P34FG189、P34FG218、P34FG218U、P34FG218U2、P34FM296、P34MV160、P34MV216、P34MV390、P34SG218、P34ST390、P34TM296、P34TM297P31FM292P34FG297P29FR383P25AS390、P25AS529、P25SG383、P25ST281、P25ST218VOD、P25ST390、P28ST319D、P28AS566、P28TG529E、P28TT520、P29AS217、P29AS281、P29AS386、P29AS520、P29AS528、P29AS528E、P29AS529、P29SG383、P29ST186J、P29ST216、P29ST217、P29ST281、P29ST281VOD、P29ST390、P29ST528、P29TG383、P29TG529、P29TT390、P30AS319、P31ST292、P34AS386、P34AS390SP29AS391、SP29AS566、SP29ST391、SP29TM391、SP29TM520、SP29TM529SP32TM391、SP32AS391、SP32ST391、SP32TM520、SP32TM529P32ST319、P32ST319U、P32ST319VOD、P32ST298、P32TG520、P32SG383、P34ST216、P34ST386、P34ST390、P28AS566、P28TM319、P28TM520、P28TM529SP21AS529、P24AS319BT4088W、BT4330DZ、BT4366U、BT4370U、BT4380U、BT4390W、BT4398U、BT4688W、BT5066U、BT5090W、BT5688W、BT5390E。

TB2906HQ中文资料

Features
• : High power output POUT MAX (1) = 43 W (typ.) P (VCC = 14.4 V, f = 1 kHz, JEITA max, RL = 4 Ω) : POUT MAX (2) = 39 W (typ.) (VCC = 13.7 V, f = 1 kHz, JEITA max, RL = 4 Ω) : POUT (1) = 26 W (typ.) (VCC = 14.4 V, f = 1 kHz, THD = 10%, RL = 4 Ω) : POUT (2) = 23 W (typ.) (VCC = 13.2 V, f = 1 kHz, THD = 10%, RL = 4 Ω) • Low distortion ratio: THD = 0.015% (typ.) (VCC = 13.2 V, f = 1 kHz, POUT = 5 W, RL = 4 Ω) • • • • • • Low noise: VNO = 180 µVrms (typ.) (VCC = 13.2 V, Rg = 0 Ω, BW = 20 Hz to 20 kHz, RL = 4 Ω) Built-in standby switch function (pin 4) Built-in muting function (pin 22) Built-in Off-set detection function (pin 25)
Note:
Some of the functional blocks, circuits, or constants in the block diagram may be omitted or simplified for explanatory purpose.

UC2906中文资料

UC3906 Sealed Lead-Acid Battery ChargerFEATURES•Optimum Control for Maximum Battery Capacity and Life •Internal State Logic Provides Three Charge States •Precision Reference Tracks Battery Requirements OverTemperature•Controls Both Voltage and Current at Charger Output •System Interface Functions •Typical Standby SupplyCurrent of only 1.6mA DESCRIPTIONThe UC2906 series of battery charger controllers contains all of the necessary circuitry to optimally control the charge and hold cycle for sealed lead-acid batter-ies. These integrated circuits monitor and control both the output voltage and cur-rent of the charger through three separate charge states; a high current bulk-charge state, a controlled over-charge, and a precision float-charge, or standby, state.Optimum charging conditions are maintained over an extended temperature range with an internal reference that tracks the nominal temperature charac-teristics of the lead-acid cell. A typical standby supply current requirement of only 1.6mA allows these ICs to predictably monitor ambient temperatures.Separate voltage loop and current limit amplifiers regulate the output voltage and current levels in the charger by controlling the onboard driver. The driver will sup-ply up to 25mA of base drive to an external pass device. Voltage and current sense comparators are used to sense the battery condition and respond with logic inputs to the charge state logic. A charge enable comparator with a trickle bias output can be used to implement a low current turn-on mode of the charger, preventing high current charging during abnormal conditions such as a shorted battery cell.Other features include a supply under-voltage sense circuit with a logic output to indicate when input power is present. In addition the over-charge state of the charger can be externally monitored and terminated using the over-charge indi-cate output and over-charge terminate input.UC3906 Supply Voltage (+V IN). . . . . . . . . . . . . . . . . . . . . . . . . . . 40VOpen Collector Output Voltages. . . . . . . . . . . . . . . . . . . 40VAmplifier and Comparator Input Voltages. . . -0.3V to +40VOver-Charge Terminate Input Voltage. . . . . . -0.3V to +40VCurrent Sense Amplifier Output Current. . . . . . . . . . 80mAOther Open Collector Output Currents. . . . . . . . . . . . 20mATrickle Bias Voltage Differential with respect to V IN. . . -32VTrickle Bias Output Current. . . . . . . . . . . . . . . . . . . . -40mADriver Current. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80mAPower Dissipation at T A = 25°C(Note 2). . . . . . . . 1000mWPower Dissipation at T C = 25°C (Note 2). . . . . . . . 2000mWOperating Junction Temperature. . . . . . . . -55°C to +150°CStorage Temperature. . . . . . . . . . . . . . . . . -65°C to +150°CLead Temperature (Soldering, 10 Seconds). . . . . . . 300°CNote 1:Voltages are referenced to ground (Pin 6). Currentsare positive into, negative out of, the specified terminals.Note 2: Consult Packaging section of Databook for thermallimitations and considerations of packages.ABSOLUTE MAXIMUM RATINGS (Note 1)Unless otherwise stated, these specifications apply for T A = -40°C to +70°C for theUC2906 and 0°C to +70°C for the UC3906, +V IN = 10V, T A = T J.ELECTRICAL CHARACTERISTICS:the reference and the thermal resistance, junction-to-ambient.ELECTRICAL CHARACTERISTICS:Unless otherwise stated, these specifications apply for T A = -40°C to +70°C for theUC2906 and 0°C to +70°C for the UC3906, +V IN = 10V, T A = T J.Dual Level Float Charger OperationsThe UC2906 is shown configured as a dual level float charger in Figure 1. All high currents are handled by the external PNP pass transistor with the driver supplying base drive to this device. This scheme uses the TRICKLE BIAS output and the charge enable comparator to givethe charger a low current turn on mode. The output cur-rent of the charger is limited to a low-level until the battery reaches a specified voltage, preventing a high current charging if a battery cell is shorted. Figure 2 shows the state diagram of the charger. Upon turn on the UV sense circuitry puts the charger in state 1, the high rate bulk-charge state. In this state, once the enable threshold has been exceeded, the charger will supply a peak current that is determined by the 250mV offset in the C/L ampli-fier and the sensing resistor R S.T o guarantee full re-charge of the battery, the charger’s voltage loop has an elevated regulating level, V OC , during state 1 and state 2. When the battery voltage reaches 95% of V OC , the charger enters the over-charge state,state 2. The charger stays in this state until the OVER-CHARGE TERMINATE pin goes high. In Figure 1, the charger uses the current sense amplifier to generate this signal by sensing when the charge current has tapered to a specified level, I OCT . Alternatively the over-charge could have been controlled by an external source, such as a timer, by using the OVER-CHARGE INDICATE signal at Pin 9. If a load is applied to the battery and begins to dis-charge it, the charger will contribute its full output to the load. If the battery drops 10% below the float level, the charger will reset itself to state 1. When the load is re-moved a full charge cycle will follow. A graphical repre-sentation of a charge, and discharge, cycle of the duallever float charger is shown in Figure 3.OPERATION AND APPLICATION INFORMATIONOPERATION AND APPLICATION INFORMATION (continued)Compensated Reference Matches Battery Requirements When the charger is in the float state, the battery will be maintained at a precise float voltage, V F . The accuracy of this float state will maximize the standby life of the battery while the bulk-charge and over-charge states guarantee rapid and full re-charge. All of the voltage thresholds on the UC2906 are derived from the internal reference. This reference has a temperature coefficient that tracks the temperature characteristic of the optimum-charge and hold levels for sealed lead-acid cells. This further guaran-tees that proper charging occurs, even at temperature ex-tremes.Dual Step Current Charger OperationFigures 4, 5 and 6 illustrate the UC2906’s use in a differ-ent charging scheme. The dual step current charger is useful when a large string of series cells must be charged. The holding-charge state maintains a slightly elevated voltage across the batteries with the holding cur-rent, 1H . This will tend to guarantee equal charge distribu-tion between the cells. The bulk-charge state is similar to that of the float charger with the exception that when V 12is reached, no over-charge state occurs since Pin 8 is tied high at all times. The current sense amplifier is used to regulate the holding current. In some applications a series resistor, or external buffering transistor, may be requiredat the current sense output to prevent excessive power dissipation on the UC2906.A PNP Pass Device Reduces Minimum Input to Out-put DifferentialThe configuration of the driver on the UC2906 allows a good bit of flexibility when interfacing to an external pass transistor. The two chargers shown in Figures 1 and 4both use PNP pass devices, although an NPN device driven from the source output of the UC2906 driver can also be used. In situations where the charger must oper-ate with low input to output differentials the PNP pass de-vice should be configured as shown in Figure 4. The PNP can be operated in a saturated mode with only the series diode and sense resistor adding to the minimum differen-tial. The series diode, D1, in many applications, can be eliminated. This diode prevents any discharging of the battery, except through the sensing divider, when the charger is attached to the battery with no input supply voltage. If discharging under this condition must be kept to an absolute minimum, the sense divider can be refer-enced to the POWER INDICATE pin, Pin 7, instead of ground. In this manner the open collector off state of Pin 7 will prevent the divider resistors from discharging thebattery when the input supply is removed.OPERATION AND APPLICATION INFORMATION (continued)OPERATION AND APPLICATION INFORMATION (continued)UNITRODE INTEGRA TED CIRCUITS7 CONTINENTAL BLVD. • MERRIMACK, NH 03054TEL. 603-424-2410 • FAX 603-424-3460IMPORTANT NOTICETexas Instruments and its subsidiaries (TI) reserve the right to make changes to their products or to discontinue any product or service without notice, and advise customers to obtain the latest version of relevant information to verify, before placing orders, that information being relied on is current and complete. All products are sold subject to the terms and conditions of sale supplied at the time of order acknowledgement, including those pertaining to warranty, patent infringement, and limitation of liability.TI warrants performance of its semiconductor products to the specifications applicable at the time of sale in accordance with TI’s standard warranty. Testing and other quality control techniques are utilized to the extent TI deems necessary to support this warranty. Specific testing of all parameters of each device is not necessarily performed, except those mandated by government requirements.CERTAIN APPLICATIONS USING SEMICONDUCTOR PRODUCTS MAY INVOLVE POTENTIAL RISKS OF DEATH, PERSONAL INJURY, OR SEVERE PROPERTY OR ENVIRONMENTAL DAMAGE (“CRITICAL APPLICATIONS”). TI SEMICONDUCTOR PRODUCTS ARE NOT DESIGNED, AUTHORIZED, OR WARRANTED TO BE SUITABLE FOR USE IN LIFE-SUPPORT DEVICES OR SYSTEMS OR OTHER CRITICAL APPLICATIONS. INCLUSION OF TI PRODUCTS IN SUCH APPLICATIONS IS UNDERSTOOD TO BE FULLY AT THE CUSTOMER’S RISK.In order to minimize risks associated with the customer’s applications, adequate design and operating safeguards must be provided by the customer to minimize inherent or procedural hazards.TI assumes no liability for applications assistance or customer product design. TI does not warrant or represent that any license, either express or implied, is granted under any patent right, copyright, mask work right, or other intellectual property right of TI covering or relating to any combination, machine, or process in which such semiconductor products or services might be or are used. TI’s publication of information regarding any third party’s products or services does not constitute TI’s approval, warranty or endorsement thereof.Copyright © 1999, Texas Instruments Incorporated。

第五届峨眉校区数学建模知识竞赛复赛题

1，峨眉校区上课时间问题峨眉校区的同学们在周一到周五的日子里，都或多或少地对学校的上课时间有着自己的意见和看法，或许早晨8点第一讲的课令你疲乏不堪，或许在肚子咕咕叫时冲进食堂又发现人上人海......这些的一切，都是我们的上课时间安排所造成的。

下面是峨眉校区上课时间表：问题：（1）学校现在的上课时间合理吗？请你运用数学建模的知识，查阅相关资料，合理选取影响因素，并对问题进行一定的量化，对学校现在的作息时间合理性作出评价，并用一段文字阐述。

（2）对于你的结果，你认为现在的上课时间需不需要调整？如果需要，应该如何安排？峨眉校区的基建处需要确定与屋顶配套的檐沟的规格。

现在假设中山梁一栋教学楼的房屋的屋顶都是矩形，长12米，从屋脊到檐沟的宽为6米，屋顶对水平面的倾角还未定，但大致将在20度和50度之间。

一家檐沟生产公司急欲与学校基建处签定供货合同，该公司声称他们的新型塑料檐沟经久耐用，无论什么样的天气情况都能有效地满足要求，对这批屋顶，设计的檐沟横截面是半径为7.5厘米的半圆，用一条直径为10厘米的排水管就够了。

学校的领导不能确信檐沟供应单位的声称，因此找到了对数学建模感兴趣的你，希望建一个数学模型，在批量定货前对此作一个全面分析，其中至关重要的是这种尺寸在暴雨时是否足以排水。

并提交合理的建议。

峨眉校区的后勤部门一周中每天需要不同数目的全时雇员来对学校的卫生，教学楼的财务安全，以及水电设施的维修进行管理。

每个人每天工作8小时：周一到周四每天至少50人，周五和周日每天至少80人，周六至少90人。

现规定应聘者须连续工作5天，试确定聘用方案，即周一到周六每天聘用多少人，使在满足需要的条件下聘用的总人数最少？如果周日的需要量由80增加至90人，方案怎样改变？如果可以用两个临时聘用的半时雇员（一天工作4小时，不需要连续工作）代替一个全时雇员，但规定半时雇员的工作量不得超过总工作量的四分之一。

又设全时雇员和半时雇员每小时的酬金分别为5元和3元，试确定聘用方案，使在满足需要的条件下所付酬金总额最小？4、医疗站选址问题今年我国提出了“建设社会主义新农村”的伟大举措，国家将拿出1000多亿元建设农村公路，数百亿元解决农民看病难。

气象专用术语

气象专用术语葡福风力等级表（BEAUFORT WIND SCALE）二・风浪和涌浪等级表（SEA AND SWELL SCALE）在北太平洋（包括南海）。

将热带气旋分为4级。

我国和日本都采用这个标准热带低压TD： TROPICAL DEPRESSION——风速：34KN （风力V8级）热带风暴TS： TROPICAL STORM ——风速：34KN—47KN （风力8—9 级）强热带风暴STS： SEVERE TROPICAL STORM——风速：48KN （风力10—11 级）台风T： TYPHOON ——风速：＞64KN （风力＞12 级）。

台风半径范I羽:TYPHOON——RADIUS 最大风力:MAX——WINDS三.雾情和能见度等级表四.天气缩语时间用语（地方时）白天：DAY08— —20时夜间： NIGHT 20— —08时早展：MORNING 05- ―8时傍晚： EVENING 18— —20时上午：MORNING 08- ——12时上半夜 :EVENING20— —24时中午：NOON 下午：AFTERNOON 今天：TODAY11— 12- 一14时 ~18时昨天：YESTERDAY午夜：下半夜： MIDNIGHT 23— FULL NIGHT 00— 明天：TOMRROVV—03时—05时上海气象台台风实例SHHAI OBSY TYPHOON TALIM 0513 (0513) WARING上海气象台台风泰利 05年13号警报292000ZNR02： TYPHOON TALIM 0513 (0513)930HPA CENTER 29日20时世界时台风泰利 05年13号 930百帕中心POSITION 21。

2N 130. 06EAT 291800ZMOVING WNW 13KTS位置 21° 02f N 130° ()6' E 在29 H 18时世界时移动西北西13节MAX WINDS 106KTS NEAR CENTER RADIUS OF 30KTSWINDS 最大风力106节附近中心半径范围30节风 270 NAUTICAL MILES AND RAUIUS OF 50KTS WINDS • 140 270海里和半径范围50节风140NAUTICAL MILES FORECAST POSITION FOR 301800Z AR23. ON海里预测位置从 30日18时世界时在 23。

Bayesian group-sparse modeling and variational inference

Bayesian Group-Sparse Modeling and Variational InferenceS.Derin Babacan,Member,IEEE,Shinichi Nakajima,and Minh N.Do,Fellow,IEEEAbstract—In this paper,we present a general class of multi-variate priors for group-sparse modeling within the Bayesian framework.We show that special cases of this class correspond to multivariate versions of several classical priors used for sparse modeling.Hence,this general prior formulation is helpful in analyzing the properties of different modeling approaches and their connections.We derive the estimation procedures with these priors using variational inference for fully Bayesian estimation. In addition,we discuss the differences between the proposed in-ference and deterministic inference approaches with these priors. Finally,we show theﬂexibility of this modeling by considering several extensions such as multiple measurements,within-group correlations,and overlapping groups.Index Terms—Bayes methods,group-sparsity,variational inference.I.I NTRODUCTIONW E consider the general linear model given by(1) where observations of the original unknown signal are taken with an measurement matrix(or dictionary),and represents the noise.This paper is concerned with the problem ofﬁnding an estimate of the un-known signal from the observations.Generally,the case of interest is the regime,which makes the problem challenging and requires appropriate modeling of the unknown signal.Manuscript received May20,2012;revised January07,2014;accepted March28,2014.Date of publication April22,2014;date of current version May09,2014.The associate editor coordinating the review of this manuscript and approving it for publication was Dr.Sukeyman S.Kozat.S.D.Babacan acknowledges the Beckman Postdoctoral fellowship from University of Illinois at Urbana-Champaign.S.Nakajima thanks the support from MEXT Kakenhi 23120004.M.N.Do acknowledges the support of the National Science Foundation grant CCF09-64215.S.D.Babacan was with the Beckman Institute for Advanced Science and Technology,University of Illinois at Urbana-Champaign,Urbana,IL,USA.He is now with Google,Incorporated,Mountain View,CA94043USA(e-mail: dbabacan@).S.Nakajima is with the Optical Research Laboratory,Nikon Corporation, Tokyo140-8601,Japan(e-mail:nakajima.s@nikon.co.jp).M.N.Do is with the Department of Electrical and Computer Engineering and the Beckman Institute for Advanced Science and Technology,Uni-versity of Illinois at Urbana-Champaign,Urbana,IL61801USA(e-mail: minhdo@).Color versions of one or more of theﬁgures in this paper are available online at .Digital Object Identiﬁer10.1109/TSP.2014.2319775Problems of the general form(1)are very common in signal processing,statistics,neuroscience and machine learning. Typical applications include compressive sensing[1],sparse representation[2]–[4],super resolution[5],source localization [6],variable/model selection and prediction[7],among many others.A general design principle in these approaches is spar-sity,which amounts toﬁnding the most important components of and suppressing the elements with relatively lower im-portance.In this design,the unknown vector is assumed to contain a small number of nonzero elements,while the majority of the components are zero.This assumption is translated into the optimization problem forﬁnding using sparsity-pro-moting penalty functions,of which the most common example is the-norm based formulation given by(2) This formulation is commonly referred to as basis pursuit de-noising[4]and is related to lasso[8].It implicitly models the noise as zero-mean white Gaussian distributed with variance ,and is the regularization parameter controlling the strength of the enforced sparsity.A large number of optimiza-tion methods have been developed for solving(2)[4],[8]–[11]. In addition,different sparse signal models have been proposed extending the-norm to the more general-norm with[9],[11].In the traditional sparse modeling,the sparsity constraint is imposed on individual components of.Recently,a different modeling approach has emerged where sparsity is enforced on groups instead of the individual components.This group-sparse (also called block-sparse)approach is a natural generalization of the traditional sparse modeling methods.It effectively models the structural properties of the signal by clustering relevant signal components together,such that dependencies between signal components are taken into account.It is also shown to lead to higher performance in pruning out irrelevant components compared to independent modeling of the coefﬁ-cients[12].Group-sparsity has recently been considered in compressive sensing[12]–[16]and machine learning[17]–[21],and is also closely related to signal modeling within union of subspaces [12],[22]–[24].It has rapidly found applications in, e.g., imaging[25],[26]and network analysis[27],demonstrating promising performance.A general optimization formulation for group-sparse regular-ization is(3)1053-587X©2014IEEE.Personal use is permitted,but republication/redistribution requires IEEE permission.See /publications_standards/publications/rights/index.html for more information.where denotes the combined-norm with(4) where denotes the th group,and is the number of groups. Each group contains elements,such that if the groups are not overlapping.It is clear that this formulation includes the traditional-based formulation as a special case (when).The optimization problem(3)is similar to the-based opti-mization,and thus some-based approaches can be applied to this problem with some modiﬁcations.Deterministic methods directly addressing the problem(3)have been developed in [3],[28],[29],and in group-lasso methods[21],[20].Several Bayesian approaches have been developed for group-sparse modeling:the Bayesian group-lasso[30]proposed to use multivariate Laplace priors on separate groups,and provided a sampling scheme for inference.A similar group-sparse prior is used in covariance estimation problem in[18].In[17],[31], Laplacian scale mixtures have been used for the construction of the group-sparse prior,and the inference is performed using expectation-maximization(EM).An important issue in all sparse reconstruction problems is choosing the regularization parameters and.Clearly, optimizing(3)jointly with respect to them is not suitable since it results in the trivial solution.A similar problem is encountered when the problem is converted to weighted least squares problems,as in iteratively reweighted least squares (IRLS)with-priors[9],[11],[32].Deterministic heuristic methods are devised for parameter estimation,such as L-curves [33]or penalizing the trivial solution[9].A more systematic approach can be obtained using Bayesian inference,as shown in this article.In this paper,we present a Bayesian approach for group-sparse modeling and ing a normal variance mix-ture formulation,we present the hierarchical construction of a general signal prior suitable for modeling group-sparse signals. This general signal prior contains a large class of distributions as special cases,obtained via different selections of distributions in the hierarchical ing this general formulation, we explore different options for group-sparse modeling,ana-lyze their connections,and their sparsity-enforcing properties. We show that some of the special cases of this generalized prior correspond to several standard models used in the sparse and group-sparse reconstruction literature.For estimation using this class of priors,we provide the hierarchical inference rules using the variational Bayesian(VB)approach for a fully-Bayesian es-timation(i.e.,including algorithmic parameters).We compare the proposed inference with deterministic inference approaches, and show the thresholding properties of different priors both in deterministic and Bayesian frameworks.Finally,we consider several extended modeling possibilities within Bayesian group-sparse modeling,such as within-group correlations and over-lapping groups,and consider the multiple measurement vector case.The rest of this paper is organized as follows.Section II pro-vides the hierarchical construction of the generalized group-sparse prior using normal variance mixtures.We also derive its special cases and show their properties.In Section III,we de-velop fully-Bayesian inference methods using these priors via variational Bayesian approximation.Properties of the modeling and inference in comparison with deterministic approaches are discussed in Section IV.Several extensions to Bayesian group-sparse modeling are provided in Section V.Empirical evalua-tion of different aspects of the group-sparse modeling are pre-sented in Section VI,and conclusions are drawn in Section VII.II.B AYESIAN G ROUP-S PARSE M ODELINGThe Bayesian modeling of(1)requires the deﬁnition of a joint distribution of all unknown and observed quantities.This joint distribution typically includes the conditional distribution for the observations,and a prior that models the characteristics of the unknown signal.In the following,weﬁrst present a class of distributions suitable for group-sparse modeling of using variance mixtures of Gaussian distributions.We then de-rive its special cases and show the connections between them and models proposed in the literature.Finally,we complete the Bayesian model by specifying the observation model and hy-perpriors assigned to the parameters of all distributions.We use the following notation throughout this paper.Vectors are denoted by small-case bold letters,while matrices are in capital bold letters.is a diagonal matrix with vector as its diagonal,and denotes the expectation with respect to the corresponding distribution.A.Signal ModelsFor modeling the unknown signal,weﬁrst deﬁne groups of coefﬁcients such that the vector contains signal coef-ﬁcients assigned to group.The case with, corresponds to independent sparse modeling of the coefﬁcients. Assuming a priori independence between groups,we express the signal prior as(5) where is the vector containing all.Independent groups arise naturally in many applications(e.g.,multi band signal recon-struction[34],sampling signals that lie in a union of subspaces [22],microarray analysis[30]),and group independence is a good approximation in many others.Note also that the infer-ence scheme adopted in this work makes the groups dependent a posteriori(see Section III-A).Sparsity is enforced on each group via the conditional priors.For their representa-tion,we use the normal variance mixture model[35](also called scale mixtures of Gaussians[36],[37]).Speciﬁcally,we repre-sent each group as(6) where and is a standard multivariate Gaussian variable, i.e.,with a zero vector of length andthe identity matrix.It is clear that given,isa multivariate Gaussian variable with zero mean and variance,that is(7) Notice that the coefﬁcients within each group are not indepen-dent.The marginal probability distribution of can be found by integrating out the latent variables as(8) Here,is called the mixing distribution and determines the form of the marginal distribution.Normal variance mixtures have been extensively used in the literature for representing a large number of distributions,and for deriving efﬁcient inference procedures for parameter esti-mation[36]–[40].A variety of distributions can be represented in this fashion by different selection of the mixing distribution .In this paper,for the mixing distribution we consider the generalized inverse Gaussian(GIG)distribution(9) where is the modiﬁed Bessel function of the second kind. The moments of this distribution are given by[41](10) With this mixing density,the marginal distribution of is found from(8)as the generalized hyperbolic(GH)distribution [35](11)In this paper,we chose the GIG distribution as the mixing dis-tribution as it includes a fairly broad class of distributions com-monly used as hyperpriors,and the resulting marginal distribu-tion,the GH distribution,again covers a large number of distri-butions as special cases.Due to this generalization,we are able to analyze the connections between different modeling strate-gies.As we shall see in the following,several special cases cor-respond to standard priors commonly used in sparse modeling. To see the rich family of distributions that can be obtained from the GH distribution,distributions obtained with varying values of,and are depicted in Figs.1–3.It can be seen that both the central and tail behavior can be varied using dif-ferent parameter values,and as will be shown later,the resulting distributions have different estimation characteristics.In the fol-lowing,we consider the special cases of the GH distribution at the limit parameter values,along with the mixing distributions.Let usﬁrst give some expressions on asymptotic approxima-tions of the modiﬁed Bessel function that will be useful:(12)(13)(14)(15) and for integer,(16) 1)McKay’s Bessel Function Distribution:Whenwith,the mixing GIG distribution reduces to the gamma distribution,given by(17) The corresponding marginal distribution is(18) which is McKay’s Bessel function distribution[42]–[44](also called multivariate variance-gamma[38],multivariate general-ized Laplace[43],or multivariate K distribution[39],[40]). We now consider two special cases of(18)that are related to the Laplace distribution.In the case,the mixing distri-bution becomes the exponential distribution(19) such that the marginal becomes(20) To see the relation with the univariate Laplace distribution,we can use(16)and rewrite(20)for odd as(21) The similarity to the univariate case can be seen from the ex-ponential term,and noticing that all other terms vanish with .Note,however,that there are additional terms that are power functions of.A more directly related case can beFig.1.Generalized hyperbolic distributions(a)and log-distributions(b)with varying,when,(,the cross-section is shown).Fig.2.Generalized hyperbolic distributions(a)and log-distributions(b)with varying,when,(,the cross-section is shown).Fig.3.Generalized hyperbolic distributions(a)and log-distributions(b)with varying,when,(,the cross-section is shown).TABLE IS UMMARY OF D ISTRIBUTIONS AND P ARAMETER ESTIMATESfound by the selection ,which simpli ﬁes (18)using (16)as(22)in which case the mixing distribution is a gamma distribution given by(23)Both distributions (20)and (22)were termed as multivariate Laplace distributions in the literature:the form in (20)is used in [39],[45]due to the similarity of the hierarchical structure to the univariate case,and (22)is used in the Bayesian group-lasso method [30]due to the similarity of the marginal distributions.Here we will use the term multivariate Laplace for the distri-bution in (22)since it has an estimation behavior similar to the univariate case (see Section IV-A).The distribution in (20)will be referred to as McKay .Notice that both distributions reduce to the univariate Laplace distribution when .It is also possible to integrate out from by as-signing a gamma hyperprior on .When ,the corresponding marginal has a closed form and is given by(24)which is the multivariate version of the generalized double Pareto distribution [46],[47].2)Multivariate Student’s :Whenwith ,we have the inverse gamma distribution as the mixing density(25)The corresponding marginal is given by(26)which is a multivariate Student’s t distribution withde-grees of freedom.Finally,when ,and ,we have the Jeffrey’s non-informative prior .In this case,the marginaldistribution becomes(27)Fig.4.McKay,Laplace,Student’s t,Jeffrey’s and Gaussian log-distributions(,the cross-section is shown).In summary,the variance mixture model with the GIG mix-ture distribution includes a number of classical distributions as special cases at the limiting values of its parameters.In the fol-lowing,we mainly limit our discussion to the four distributions described above,i.e.,multivariate McKay ,Laplace,Student’s t distributions and Jeffrey’s prior.These distributions along with the corresponding parameter selections are summa-rized in Table I.The log-distributions for all cases are shown in Fig.4,along with the Gaussian distribution.It is evident that all distributions have heavy-tails,which is generally considered to be a desirable property for enforcing sparsity and variable plete ModelAfter the signal model is de ﬁned,we complete the Bayesian model characterization by modeling the observations in (1).Assuming independent Gaussian noise with zero mean and vari-ance equal to ,the conditional distribution is expressed as(28)with a conjugate gamma prior placed onas(29)A prior is called conjugate if it leads to a posterior distribution that has the same functional form as the prior [7].The use of con-jugate priors signi ﬁcantly simplify the form of posterior distri-bining(28),(29)and the hierarchical signal prior (7)and(9),we deﬁne the joint probability distribution as(30) where,,,are vectors containing,,,and respectively.The hyperprior is used to model the pa-rameters and for their estimation,and will be discussed in Section III-C.III.V ARIATIONAL I NFERENCEBayesian inference is based on the posterior distribution,where denotes the set of all un-knowns such that.However,as in many multidimensional problems,the Bayesian model deﬁned with the joint distribution in(30)does not allow for exact inference as the marginal distribution is intractable.Therefore, approximation methods must be used for the inference.In the following,we use the variational Bayesian(VB)approximation [48],[49],which has attractive computational properties along with high estimation performance.With the deﬁnition of the joint distribution in(30),the variational Bayes method provides a distribution that approximates the posterior. Speciﬁcally,is found by minimizing the Kullback-Leibler (KL)divergence between the approximation and the unknown posterior as[48],[49](31)(32) where is the joint probability distribution given in(30). To solve this optimization,the only assumption needed is an appropriate factorization of.Here we use the mean-ﬁeld approximation[48]with(33)Using this factorization in(32),the distributions of each variable is found as[48],[49](34)(35)where denotes the set with removed.Individual dis-tributions are updated by(35)at each iteration byﬁxing the remaining distributions,which corresponds to an alternating minimization of the KL divergence in(32).This it-erative procedure is repeated until the KL distance converges. The VB method is a generalization of the maximum a pos-teriori(MAP)and expectation-maximization(EM)methods. The EM estimates can be found by restricting some distribu-tions to be degenerate,i.e.,delta distributions at a par-ticular value.On the other hand,MAP solutions can be found by restricting all of the distributions to be degenerate.When a distribution is degenerate,it can be shown from(32)that its corresponding estimation amounts to minimizing the negative expected log joint distribution,which re-duces to the log joint distribution in the case We will discuss the MAP estimation in more detail in Section IV.In the following subsections,we provide the explicit forms of the update rules for all unknowns.For notational simplicity, the optimal distributions are denoted by instead of.A.Signal EstimateFrom(35),the posterior approximation of is found as a multivariate Gaussian(36) with parameters(37)(38)(39) with,with each repeated times.1It can be seen from(38)that except when,the groups are a posteriori dependent,despite the a priori independence assumption in(5).Sparsity in the groups occur when particular variables,in which case the th group is pruned out from the signal estimate.2Notice also the estimation of requires the inversion of an matrix using(38),and an matrix using(39).B.Estimation of the Variance ParametersThe crucial part of(37)is the estimates of,which control the sparsity and hence the structure of the signal estimate.Here we derive the estimation rules for the general case with the GIG hyperprior,from which the special cases can easily be obtained. First,with some algebra,it can be derived from(35)in combi-nation with(33)that the distribution factorizes over, such that(40) Therefore,in the following we provide the update rules for each ing(35),weﬁnd the approximate posterior from(7)and(9)as a GIG distribution(41) with the expectation computed as(42) 1Notice that this assumes non-overlapping groups;overlapping groups willbe discussed later.2The modeling used in this paper does not allow for exact sparsity.However, sparsity occurs in practice when estimates become very large such that the coefﬁcients in the th group are from zero.where denotes the submatrix of corresponding to the th group.The posterior estimate of can be calculated by the moments of this distribution in(10)as(43) The update rules for the limiting cases can be found from this general form,and are shown in the third column of Table I. C.Estimation of the Hyperparameters andNotice that in the general case(43),the posterior estimate of contains the hyperparameters,,and,which deter-mine the shape of the enforced distribution on.With the vari-ational approximation,their posterior distributions can be esti-mated using(35)as well,with the appropriate selection of the hyperpriors,and(or with a joint hyperprior ).However,in the general case with GIG mixing distribution,the joint estimation of all,and is chal-lenging:the estimation of requires numerical solutions(in-stead of analytical closed form updates),and when all parame-ters are jointly estimated,the accuracy greatly depends on the initial estimates.Therefore,we instead provide hyperparameter estimates of and in the special cases,and leave as a free parameter.1)McKay’s Bessel Function Distribution:Recall that withand,we have the gamma distribution(17)as the mixing density.As the corresponding hyperprior for,we choose the conjugate gamma distribution(44) with the shape parameter and the inverse scale parameter. The posterior becomes(45) with the corresponding update(46) The moment can be found from(41)using(10).2)Multivariate Student’s:When with, the mixing distribution(25)is an inverse gamma distribution in terms of,but it is a gamma distribution with respect to the parameter.Hence we choose the gamma distribution that is conjugate for(47) The posterior distribution is found as a gamma distribution(48)with mean(49)D.Estimation of the Noise VarianceThe Bayesian methodology allows for the estimation of the noise variance as ing the prior in(29),the posterior of becomes a gamma distribution,and can be estimated using its mean as(50)with the expectation given by(51)E.SummaryThe signal priors presented in the previous sections,along with the corresponding mixing distributions and variational es-timation rules are summarized in Table I.The algorithm alter-nates between estimating the signal using(37),and the vari-ances and hyperparameters,using the equations shown in Table I,according to the selected signal distribution.The normal variance mixture with the GIG mixing distribu-tion is extremelyﬂexible,and encompasses a large family of distributions some of which can be used for modeling group-sparse signals.Other,non-standard,distributions can also be obtained by further extending the hierarchical construction and marginalization.The advantages of using the variance mixture formulation are the tractable properties of the Gaussian distri-bution obtained for the signal estimate in(36)and the conjugate prior mechanism that allows for closed-form estimation of the parameters.In this work,we used a three-level hierarchical estimation procedure,involving the estimation of,,and in alternating fashion.Instead,two-level hierarchical estimation procedures can be devised using the marginal distributionsand appropriate hyperpriors on and (therefore bypassing the estimation of).This approach is a generalization of Laplacian scale mixtures[17].However, this approach brings some difﬁculties:First,the marginal distributions have complicated forms and the corresponding conjugate hyperpriors on and are hard toﬁnd.Second,the marginal distributions generally do not allow for closed form updates of the posterior mean.Finally,the posterior mean updates of and in general require expectations that do not have closed forms.Hence,fully-Bayesian inference with this two-level hierarchy is generally hard.Note,however,that if parameter estimation is not desired,deterministic approaches can be used(see Section IV)with relative ease with some forms of the marginal distributions,e.g.,the Laplace distribution. This approach is closely related to reweighted-minimization schemes[11],[32]and the EM approach presented in[17].IV.C OMPARISON W ITH D ETERMINISTIC E STIMATION The signal priors considered in Section II-A can also be used in a deterministic maximum a posteriori(MAP)framework,which is commonly encountered in the ing a de-terministic framework allows us to show some interesting con-nections between different signal priors and also compare and demonstrate some properties of the variational Bayesian esti-mation described before.For the MAP optimization with the Bayesian model in this paper,two approaches can be considered.A.MAP Estimation Using Marginal DistributionsBy forming the joint probability distributionusing the observation model in (28)and the generalized hyperbolic distribution in(11)as the signal prior,and applying a log-transform,we obtain the MAP estimate as(52)(53) Note that the mode of the posterior distribution is sought within this formulation.In the general case with nonzero,,and, closed form updates for cannot be found and numerical so-lutions are required.However,closed-form updates can easily be found in the case of multivariate Laplace(22)and t-distribu-tions(26),and Jeffrey’s prior(27).In the case of multivariate Laplace priors,the optimization problem becomes(54) which is equivalent to the-norm formulation in(3).With the multivariate t-distributions,we have(55) Although the connection between this problem and the -norm formulation in(3)is not immediately clear,they are in fact related.Consider the following-norm based group-sparse estimation problem(56) with.Notice that recovers the-norm minimization in(3).Using the formula(57) it can be seen that the multivariate t prior is a limiting case of the -norm based group-sparse estimation procedure.In addition, in the case of Jeffrey’s priors,the penalty function is the limiting case of as.In this regard,the Laplace and t-distri-butions can be thought to be at the opposite ends of the-norm penalties;while Laplace prior leads to an-based method,t-dis-tributions enforce sparsity similar to-norms.The generalized -norm based formulation with can be constructed using Gaussian variance mixtures as well,but the mixing dis-tribution is an alpha-stable distribution without a closed-form, which makes the inference very hard.Using the MAP formulation in(53),we can also analyze the thresholding properties of different distributions when is or-thonormal,i.e.,.In this case,the problem decouples into optimization problems(the groups become independent), and can be solved for each group separately as(58) The thresholding functions for different distributions forﬁxed, and are shown in Fig.5(a).The multivariate Laplace distri-bution has a soft-thresholding behavior(similar to the univariate case),while the behavior of all other distributions is similar to hard-thresholding,including the McKay distribution. In addition,the multivariate Laplace and McKay priors have a constant bias independent of the signal value.Student’s t and Jeffrey’s priors do not have this disadvantage;the bias con-verges to zero as the signal magnitude increases.On the other hand,the Laplace prior is continuous at the thresholding value, whereas the others have discontinuities,which is generally con-sidered as a disadvantage since small changes in the data might lead to large changes in the estimation[50].In comparison,the thresholding functions obtained by the variational Bayesian inference described in the previous sections is shown in Fig.5(b).It can be observed that all thresh-olding curves become smoother,and in fact,none of the priors lead to a thresholding rule:the estimates are only“almost”sparse,i.e.,they have very small values in an interval but are never exactly zero.Interestingly,the thresholding function of the Jeffrey’s prior now exhibits a soft-thresholding behavior while the bias is again converging to zero as the signal mag-nitude increases.On the other hand,the thresholding property of the Laplace and McKay is decreased.However,it should be emphasized that when,and are not constant but also estimated,all priors lead to exact thresholding rules. An important remark is that simultaneous estimation of the parameters and cannot in general be performed using the MAP formulation if the hyperpriors and are not suitably chosen.The objective(53)becomes unbounded from below for some values of parameters,,,,in which case the global minimum is obtained at the trivial solution ,and.Therefore,other methods should be employed,such as cross-validation or L-curves[33].B.Hierarchical EstimationA second method is to use the hierarchical representations of the distributions,and consider the joint minimization problem as(59)。

电视高压包型号通脚查询

电视高压包型号/通脚查询BSC29-1081G FBT-B-31海尔29F7A-T JF0501-21933BSC29-0197F 123/456BSC29-3807-22BSC29-0115G JF01-83851高士达25"带电容双聚焦123/4679BSC25-N0864 37-FBA0002-CAA0E 051012-51 JF0501-3215 37-FBA001-CAAOC 129/346710BSC25-0277D 37-SC2502-77D01 1310/45679JF01-813海尔135/46789BSC26-2606S 1LB4L40B06800 L40B07800 124/BSC29-01B25创佳8696LTTFB3092AD 123/4910BSC29-0109Y 5132-051232-00创维32T88HSTLF14453B松下29v1R 145/678/910BSC25-N2303B普通双聚焦秦栏嘉华做JAVA假松下1210/34567BSC25-C2904海信TC2517 JF01-0115高路华的行包2518 124/58910JF0501-21933 29"海尔单聚焦BSC25-01N40L5 T111470 BSC25-01N4016C T111053直接代用BSC25-01N40L4 123/4910BSC29-0115Q 32D90HTBSC25-01N4034CZTFK07011A ZTFK07009A高士达25″松下32WG25G 128/3457BSC29-3956 BSC26-0409H 123/456910BSC25-05N2110 /78BSC30-0806 300352 T2993N BSC30-0812 300017 BSC30-N2504双聚焦大骨架康佳T3888N 123/8-598-848-00, 1-453-354-11, NX4010 M3Q4 SONY背投B 308 205515109-053859-49BSC31-0103F SVA高士达25″BSC31-0104D T111067 SVA带电容高士达25" BSC28-1931 T111060 BSC24-2640S T111068 SVA34" 123/467/5910BSC31-0103C T111062高士达25″JF0501-19290 TCL普通货1310/45679BSC29-22B BSC25-21R BSC25-01N4012D 13/458101-453-160-13 SONY背投分压盒1-453-108-11 12JF0501-90828 BSC25-0244 BSC25-1192F FBT-A-06 HT-2199DJF0501-19809 12/345BSC27-01A(K) 58-66478-01康力CE6468A电视25"用BSC25-5602 123/567910BSC25-3565S熊猫C2580BSC26-N0301K BSC25-21R创佳普通单聚焦富华做BSC25-02AW36 13/45810BSC30-1088D高士达25″双聚焦1234/56/7910BSC24-2616S 1LB4L40B05300三洋CKM2589-0BSC27-0327C天华产组装机25"单聚焦123410/78BSC29-0128 37-BSC290-128高士达25″TCL2912 12/458TFB4002AD东芝单聚焦123/BSC29-3802-24R普通双聚焦123/47910JF0501-19910A FBT-A-14 BSC25-0281C CF0801-5426 BSC25-1192E、BSC25-4801、"BSC25-0251 BSC25-0273B A3110V BSC25-3304 BSC25-01BW5 BSC25-1505 BSC25-N0307BSC31-1937 BSC33-0803配夏华带电容高士达25"厦华MT-29F1 13/456JF01-83867配海信带电容高士达25"BSC28-N2317 123/469BSC30-N2535BSC29-0106BBSC29-0128EBSC24-3105BSC29-0197BBSC25-02AW52BSC29-3929BSC29-0196E 37-SC2901-96EOX带电容高士达25" BSC29-3807-43 5100-051434-02带电容高士达25" 4410Z-A001L LG变压盒1根线100BSC29-0134A带电容高士达25" 123/45/6710BSC31-01F带电容高士达25"F1364CE夏普134/268F1438CE夏普127/F1491CE夏普137/24569/1011F1493CE F1584CE夏普148/356710/1112F1584CE F1491CE夏普137/24569/1011F1607CE夏普149/356710/1112F1856CE夏普134/257910F1903CE/2311AS夏普149/356710F1952CE夏普149/356710AT2090/33显示器飞利蒲46710/35/12小金星23/579/810小金星23/579/810BSC25-8301 BSC25-8302新飞利浦21″BSC23-2370K127/356/910JF0208-0220 BSC23-0901XB星宝1538 =970# BSC23-0201XB123/4567BSC28-7605幸福29″123/456/7810熊猫2118A 123/468BSC25-2355DA熊猫2528 BSC25-N1806 BSC25-3355D BSC25-3355CBSC25-1059B BSC25-1059S BSC25-1059C 123/46810BSC29-0102德州三和产KF58371N熊猫29”12/345/6710BSC25-3355-1 BSC25-3355RF BSC26-01N40G熊猫2977 123/46910BSC24-2004S FCM-20B027熊猫54P5 123/45679熊猫64P3 1210/34567游戏机22″191012/23458游戏机25″91012/23458游戏机CFT-715 12910/23457813/24789/10111212/3456/8910139/4568BSC27-0501高路华123/BSC75I3 123/45679BSC25-N1508海信TC2961A 124/589106174Z-8006A 129/37810/45BSC27-0501T 5104-051029-00 BSC25-2682S 5118-051029-00JF01-0166 5101-051029-00 BSC28-1916 5114-051029-00 1210/39/4567BSC21-2665S 1LB4L40B00900 124,38910 BSC25-N1508 BSC25-3358 BSC25-4101夏华21" 12458/3910 BSC25-1059T 1210,34567KFT4AX242F2松下tc-29p20r 1210,45,3671172."0128仪器高压包1234."691BSC29-0146高清，带电容海信123."456791BSC73D普通双聚焦123/BSC73Z普通双聚焦带变压块PF3495 123/BSC28-0702 BSC26-N1001K 123/BSC28-0726 普通双聚焦BSC26-N2004K 123/4810BSD70B长虹HP38A1 BSD70B、BSC70C长虹HP5175背投高压包12/45910BSD70A 123/4569 BSC75W BSC75S双聚焦123/BSC75N双聚焦123/4679BSC75C单聚焦BSC75M代用123/4679BSC75L单聚焦123/4679BSC73Y双聚焦123/BSC70B 123/4567JF01-01801 135/6789BSC25-3310 T111450金星2518B 13/49108-598-816-10带电容123/45/6789BSC29-3807-39 5109-051425-00 25T98HT带电容，双聚焦BSC27-0123S 5132-51425-00BSC68Q 123/4679BSC29-0147普通单聚焦原装BSC29-3319 5114-051229-00 123910/4567BSC30-1080G 12/456710JF0501-2165 58-68618S- 1 10 128/3567BSC29-1081E HP-2999A BSC29-0160 135/6789 BSC23-2370K 21D8 25-8301 127,3456,910MC-FBC-002 039-00801-006-6 T-10420单显58910/67BSC30-N2506海信高士达25"带电容TF3488D TF3482E JF01-83818 1210/45689100-4150D定做仪器高压包珠海南科BSC30-N2506金海29″123/45689HVG/32663 DTV 5138-051850-01BSC29-0186G BSC30-N2567 JF01-83802高士达25"带电容BSC29-01N4036B 123/4679BSC31-18J 123/6174Z-6103J 128/345710BSC31-18G 123/JF01-01150 5101-051434-07 13/467910BSC28-5305C普通双聚焦嘉华29“125/BSC28-0638 单聚焦纯平13/248/56910CF0801-7401高士达25"带电容123/467910BSC29-0118W 37-SC2901-18W01高士达25"带电容145/681011JF01-81831 FBT-B-14 BSC29-0139D FBT-B-14 BSC29-0139F 海尔29F2A-S纯平单聚焦FBT-C-06 123/456JF01-19991 6174V-6016A带电容，单聚焦123/46910JF01-85027松下背投海尔12/69BSC25-0299D 37-SC2502-99DOX BSC25-0211 37-SC2502-99D0X BSC25-0299D 124/356810JF0501-19504 123/BSC29-0138D 5132-051309-05带电容BSC29-0138G 5100-051309-07 5132-051309-07 123/467BSC70Y单聚焦带变压盒BSC70X1 123/BSC73M普通双聚焦123/45679BSC73L普通双聚焦123/BSC70K单聚焦带变压盒SF2911长虹SF3411F 123/BSC29-0138海尔D29FV6-A CF0801-7402高清带电容123/BSC73W普通双聚焦BSC73W1 123/BSC70J 123/456910BSD69X长虹JP5186 BSC70E 12JF01-01810 FBT-B-15 BSC29-0130F 1210,4568BSC29-3807-30单聚焦带电容123/4579FUW-50A0036174V-5003A BSC28-N2325 BSC28-N2312 6174V-5003L BSC28-N2334 6174V-6003L 125/346810TFB5067AD高士达25" 123,5789BSC25-0820福利牌12/568910BSC29-3706 BSC26-01N4016H SVA D2957F123/456910BSD70A-1三枪大背投123/4569CF0801-5402 123，45679BSC30-0913 P3409T 13/1072."0294小监视器高压包2356/410/789BSC29-3970V普通双聚焦123/457910BSC23-2682S 1LB4L40B05100高士达25”配三头1234/56910BSC25-5402 ZTFK82003A松下TC-2118A 12/457/689BSC28-0633 300962 T2581C F2509C1 123/JF0501-2505P 37-F05012-505 124,3567,8910BSC29-0402 V2966G 1210/3456BSC29-0149Q 37-SC2901-94QOXFLK-29A081 1234/56791019."70040."001 FEA578高士达25”配三头12/458JF01-01844日立25″129/34568BSC30-0906 BSC30-086/A 123/46810BSC30-0870BSC30-0907 P29FM186 BSC26-N2003K康佳P29FM216 EK19801 13/BSC30-0850 双聚焦康佳的机型是P29FM105 123/BSC30-0940 单聚焦BSC30-0938 13/BSC30-0942 双聚焦13/BSC30-0903 300802双聚焦123/BSC30-0826 双聚焦BSC26-N2011K 13/24810BSC23-2684S BSC23-027/A双聚焦P2902M P2905M123/4810TFB4122AH东芝2970XHEJF01-2746A JF01-2746 5100-051434-33 5100-051434-32普通双聚焦5线1210/39/4567JF01-85003 2502 12/910/4567BSC14-01N1022亿佳黑白高压包定做BSC20-0823 A 12/568910BSC28-0724 1234/8910BSC24-09F 12/3456"BSC28-N2377 5100-051379-00高士达25""带电容单聚焦" 123/4579BSC24-01N4016J 123/4910BSC25-N0104R1 58-67496-06R1康力29"BSC25-2063S 12346/5910JF01-85927海信3406D普通双聚焦123/467910BSC29-0178 TC-29P100GJ松下34P68G KFT4AV184F TC-34P68G 123/56/89BSC28-2683S康佳3498JF01-83842双聚焦高士达25"BSC29-0501AB 1234/56/7910BSC29-0151D松下52背投BSC29-0143DBSC29-0151AKFT7AA334F1 KFT7AA334F2 123/89BSC29-0189A 37-SC2901-89A0X高清带电容双聚焦TCL-HiD291S可以用BSC29-0184A 代换把管座2个连起来。

车辆识别代码

R&D CENTER
Q/CACBW-28.1-2005解析
本标准分为8个部分，第一部分范围，第二部分规范性引用文件，第三部分车辆识别代号的组成，第四部分世界制造厂识别代号，第五部分车辆特征代码，第六部分车辆指示代码的构成，第七部分车辆识别代号的其它要求，第八部分编制举例。下面详细列出Q/CACBW28.1-2005的内容，并结合强标规定分析其编制及应用。
R&D CENTER
Q/CACBW-28.1-2005解析
第六部分：车辆指示代码（VIS）的构成 1）年份代码
R&D CENTER
Q/CACBW-28.1-2005解析
2）生产装配厂代码
R&D CENTER
Q/CACBW-28.1-2005解析
3）生产顺序号的确定
生产顺序号的确定应遵照如下原则（6.3.1条）对使用同一年份代码（第10位字码）、同一生产装配厂代码（第11位字码）和同一生产线代码（第12 位字码，该代码的使用见6.3.2）的VIN代号,不论 VIN的前八位码是否相同，其生产顺序号均为同一序列，按自然顺序依次排列。若年份代码、生产装配厂代码和生产线代码三项中有一项或一项以上内容发生变化，则应另成序列，另行按自然顺序依次排列。
一汽集团企业标准车辆识别代号系列企业标准介绍
标准化室李春蕾
R&D CENTER
主要内容
➢ VIN的含义 ➢ VIN的编制依据 ➢ 一汽VIN 系列企业标准发展变更过程 ➢ 一汽现行VIN 系列企业标准构成 ➢ 一汽VIN 系列企业标准解析
R&D CENTER
VIN的含义
VIN （Vehicle Identification Number），中文名叫车辆识别代号，VIN是指车辆生产企业为了识别某一辆车而为该车辆指定的一组字码，这个代号是由制造厂按照一定的规则，依据本厂的实际而指定的。车辆识别代号中含有车辆的制造厂家、生产年代、车型、车身型式、发动机以及其它装备的信息。

碳纳米管-聚苯胺

浙江理工大学学报,第51卷,第2期,2024年3月J o u r n a l o f Z h e j i a n g S c i -T e c h U n i v e r s i t yD O I :10.3969/j.i s s n .1673-3851(n ).2024.02.002收稿日期:2023-03-10 网络出版日期:2023-06-07基金项目:国家自然科学基金项目(51503183)作者简介:刘德运(1996- ),男,山东滕州人,硕士研究生,主要从事吸波材料方面的研究㊂通信作者:朱曜峰,E -m a i l :yf z h u @z s t u .e d u .c n 碳纳米管-聚苯胺/聚乙烯醇复合气凝胶的制备及其吸波性能刘德运,朱曜峰(浙江理工大学材料科学与工程学院,杭州310018) 摘要:为了获得高性能复合气凝胶吸波材料,以螺旋碳纳米管(H e l i c a l c a r b o n n a n o t u b e s ,H C N T s )和聚苯胺(P o l y a n i l i n e ,P A N I )为吸波剂,聚乙烯醇(P o l y v i n yl a l c o h o l ,P V A )为基体,采用定向冷冻法和低温原位聚合法制备了高性能螺旋碳纳米管-聚苯胺/聚乙烯醇复合气凝胶(H C N T s -P A N I /P V A c o m p o s i t e a e r o g e l s ,H P P A )㊂采用扫描电子显微镜㊁红外光谱仪㊁拉曼光谱仪和X 射线衍射仪对H P P A 复合气凝胶的形貌与结构进行表征,并使用矢量网络分析仪测定H P P A 复合气凝胶的电磁参数和吸波特性㊂结果表明:所制备的H P P A 复合气凝胶具有优异的吸波性能,最小的反射损耗为-69.08d B ,有效吸收带宽为4.20G H z ;H P P A 复合气凝胶优异的吸波性能主要归因于其定向的多孔结构和非均匀介质界面形成的良好阻抗匹配特性和多重极化协同效应㊂该文为构建高性能复合气凝胶吸波体系提供了新思路㊂关键词:复合气凝胶;定向冷冻;低温原位聚合;聚苯胺;吸波性能中图分类号:T B 332文献标志码:A文章编号:1673-3851(2024)03-0153-08引文格式:刘德运,朱曜峰.碳纳米管-聚苯胺/聚乙烯醇复合气凝胶的制备及其吸波性能[J ].浙江理工大学学报(自然科学),2024,51(2):153-160.R e f e r e n c e F o r m a t :L I U D e y u n ,Z H U Y a o f e n g .P r e p a r a t i o n a n d m i c r o w a v e a b s o r p t i o n p r o pe r t i e s of c a r b o n n a n o t u b e -p o l y a n i l i n e /p o l y v i n y l a l c o h o l c o m p o s i t e a e r og e l s [J ].J o u r n a l o f Zh e ji a n g S c i -T e c h U n i v e r s i t y,2024,51(2):153-160.P r e p a r a t i o n a n d m i c r o w a v e a b s o r p t i o n p r o pe r t i e s of c a r b o n n a n o t u b e -p o l y a n i l i n e /p o l y v i n y l a l c o h o l c o m p o s i t e a e r o ge l s L I U D e y u n ,Z H U Y a of e n g(S c h o o l o f M a t e r i a l s S c i e n c e &E n g i n e e r i n g ,Z h e j i a n g S c i -T e c h U n i v e r s i t y ,H a n gz h o u 310018,C h i n a ) A b s t r a c t :T o o b t a i n h i g h -p e r f o r m a n c e c o m p o s i t e a e r o g e l a b s o r b i n g m a t e r i a l s ,h i g h -pe rf o r m a n c e H C N T s -P A N I /P V A c o m p o s i t e a e r og e l s (H P P A )w e r e p r e p a r e d b y d i r e c t i o n a l f r e e z i n g an d l o w -t e m p e r a t u r e i n -s i t u p o l y m e r i z a t i o n w i t h h e l i c a l c a r b o n n a n o t u b e s (H C N T s )a n d p o l ya n i l i n e (P A N I )a s t h e ab s o r b i n g f u nc t i o n a l a g e n t ,a nd p o l y v i n y l a l c o h o l (P V A )a s t he m a t r i x .T h e m o r p h o l o g y an d s t r u c t u r e o f t h e H P P A c o m p o s i t e a e r o g e l s w e r e c h a r a c t e r i z e d b y s c a n n i n g e l e c t r o n m i c r o s c o p y ,i n f r a r e d s p e c t r o s c o p y,R a m a n s p e c t r o s c o p y ,a n d X -r a y d i f f r a c t i o n .T h e e l e c t r o m a g n e t i c p a r a m e t e r s a n d a b s o r b i n g p r o pe r t i e s of t h e H P P A c o m p o s i t e a e r og e l s w e r e a n a l y z e d b y v e c t o r n e t w o r k a n a l yz e r .T h e r e s u l t s s h o w t h a t t h e p r e p a r e d H P P A c o m p o s i t e a e r o g e l s e x h i b i t e x c e l l e n t w a v e a b s o r p t i o n p e r f o r m a n c e w i t h a m i n i m u m r e f l e c t i o n l o s s o f -69.08d B a n d e f f e c t i v e a b s o r p t i o n b a n d w i d t h o f 4.20G H z .T h e g o o d m i c r o w a v e a b s o r p t i o n p e r f o r m a n c e o f t h e H P P A c o m p o s i t e a e r o g e l s i s m a i n l y a t t r i b u t e d t o t h e i r d i r e c t i o n a l p o r o u s s t r u c t u r e a n d h e t e r o g e n e o u s m e d i u m i n t e r f a c e t o f o r m a g o o d i m p e d a n c e m a t c h i n g a n d m u l t i -p o l a r i z a t i o n s y n e r g i s t i c e f f e c t .T h i s s t u d y p r o v i d e s a n e w i d e a f o r t h e c o n s t r u c t i o n o f t h e h i g h -p e r f o r m a n c e c o m p o s i t e a e r o g e l a b s o r b i n g s ys t e m.K e y w o r d s:c o m p o s i t e a e r o g e l s;d i r e c t i o n a l f r e e z i n g;l o w t e m p e r a t u r e i n s i t u p o l y m e r i z a t i o n;P A N I; m i c r o w a v e a b s o r p t i o n p r o p e r t i e s0引言通信技术的高速发展在给人们生活带来极大便利的同时也产生了不容忽视的电磁辐射污染问题[1]㊂电磁波吸收材料可吸收入射电磁波并且转化成其他形式的能量,从而有效地解决电磁污染问题[2-4]㊂然而,传统金属氧化物电磁吸波材料存在密度高和耐腐蚀性差等问题,使其在特定应用场景中受到限制[5-6]㊂气凝胶材料因其具备低密度㊁高孔隙率和大比表面积等优势,使其在吸波材料的广泛应用中展现出了潜力[7]㊂W a n g等[8]采用溶剂热和冷冻干燥方法制备了碳@镍钴合金@镍纳米管多组分气凝胶,该材料在13.3G H z处的最小反射损耗为-57.4d B,最大有效吸收带宽为6.4G H z㊂然而,此类以无机材料为主体的气凝胶材料存在力学性能较差㊁易碎裂等问题,应用受限[9]㊂相比之下,聚合物基复合气凝胶材料具备良好的力学强度和韧性,为气凝胶吸波材料的研究提供了新的思路[10]㊂聚苯胺(P o l y a n i l i n e,P A N I)具有结构可设计㊁制备工艺简单㊁密度低和电导率可调等优势,是一类极具潜力的新型吸波材料[11-12],但P A N I的溶解性和机械加工性较差,难以单独形成稳定骨架结构的气凝胶吸波材料㊂Z h a n g等[13]采用原位聚合和冷冻干燥法制备纤维素-壳聚糖/P A N I复合气凝胶吸波材料,该材料在X波段的最小反射损耗为-43d B,有效吸收宽为3G H z㊂聚乙烯醇(P o l y v i n y l a l c o h o l,P V A)具有良好的水溶性㊁低密度和高弹性模量等特点,是良好的气凝胶基体[14-16]㊂苯胺单体与聚乙烯醇在液相混合体系下,可通过定向冷冻和低温原位聚合结合一步制备P A N I/P V A 复合气凝胶吸波材料[17],但该复合气凝胶吸波材料体系存在电磁波损耗形式单一的缺点,无法满足新型高性能吸波材料的要求㊂本文以聚苯胺为吸波剂第一组分,引入螺旋碳纳米管(H e l i c a l c a r b o n n a n o t u b e s,H C N T s)作为吸波剂第二组分,并采用定向冷冻和低温原位聚合相结合的方式一步制备H C N T s-P A N I/P V A复合气凝胶(H C N T s-P A N I/P V A c o m p o s i t e a e r o g e l s, H P P A)吸波材料,以制备具有优异力学性能和高性能吸波特性的复合气凝胶吸波材料㊂采用多维度测试方法对H P P A复合气凝胶的微观形貌和结构进行表征,通过测试复合气凝胶电磁参数计算出试样反射损耗值,探讨复合气凝胶吸波材料结构和吸波剂含量对其吸波性能的影响㊂1实验部分1.1实验材料聚乙烯醇(P V A,M o w i o l P V A-124)㊁过硫酸铵(A P S,ȡ98.0%)和苯胺(A N,ȡ99.5%)购于上海阿拉丁生化科技股份有限公司;螺旋碳纳米管(H C N T s)购于南京先丰纳米科技有限公司;盐酸(H C l,36%~38%)购于国药化工;去离子水,实验室自制㊂1.2H P P A复合气凝胶的制备将150m g H C N T s加入30m L去离子水中,经超声波处理分散,加入1.5g P V A,并在85ħ下搅拌溶解形成均匀的悬浮液;在悬浮液中加入186μL 苯胺单体㊁456m g过硫酸铵和85μL盐酸,并混合均匀(保持苯胺单体与过硫酸铵摩尔比为1ʒ1)㊂将上述混合液转移至模具中,采用液氮定向冷冻,再置于-5ħ环境下低温聚合反应72h㊂反应结束后,将样品解冻,清洗去除杂质,置于-50ħ下真空冷冻干燥48h,制得复合气凝胶H P P A㊂分别将苯胺初始摩尔浓度为0.05㊁0.10m o l/L和0.20m o l/L 所制得的H P P A记为H P P A-1㊁H P P A-2和H P P A-3㊂在P A V溶液中未添加其他组分或试剂,保持其他试样制备条件不变,制得纯P V A气凝胶,记为P V A-A㊂在不添加P V A和H C N T s的情况下进行苯胺和过硫酸铵的低温聚合,保持其他试样制备条件不变,制得P A N I试样㊂1.3测试与表征采用场发射扫描电子显微镜(H i t a c h i S-4800)观察试样微观形貌;采用傅里叶红外光谱仪㊁拉曼光谱仪和X射线衍射仪对试样进行结构测试;采用矢量网络分析仪(N5222A;K e y s i g h t)波导法对长22.86m m㊁宽10.16m m的试样在8.20~12.40G H z的频率范围内的电磁参数进行测试㊂2结果与讨论2.1H P P A复合气凝胶试样的微观形貌分析图1(a)为P V A-A气凝胶的S E M照片,从S E M照片中可以看出,P V A-A气凝胶在Z轴方向451浙江理工大学学报(自然科学)2024年第51卷上具有垂直排列的孔道结构㊂该结构产生的原因是在定向冷冻过程中冰晶垂直生长,导致P V A分子链聚集在相邻冰晶之间,形成平行冰晶的骨架孔道㊂在X轴方向上,孔壁之间相互连接呈现出鱼骨状结构,这种形貌是由冰晶的生长的占位效应导致的㊂图1(b) (d)为H P P A复合气凝胶S E M图,由图可知:H P P A复合气凝胶在Z轴方向具有排列规整的垂直孔道骨架结构,且邻近孔道间距约30μm;在X轴方向上,H P P A复合气凝胶的垂直孔道之间形成鱼骨状支架,且相邻支架距离约为5μm㊂随着苯胺含量的增加,H P P A复合气凝胶骨架结构更明显,其原因是聚苯胺分子链本身的刚性提高了骨架结构稳定性,使得材料内部骨架结构更完整㊂上述结果表明,H P P A复合气凝胶具有定向性多孔结构,且该结构有利于入射电磁波在材料内部的多重反射和散射,并延长电磁波传输路径[18]㊂图1P V A-A和H P P A复合气凝胶试样的S E M照片注:图中坐标轴X轴方向为垂直冰晶生长方向,Z轴方向为平行冰晶生长方向㊂2.2H P P A复合气凝胶试样的红外光谱分析图2为P V A-A㊁P A N I㊁H C N T s和H P P A复合气凝胶的红外光谱图㊂由图2可知:P V A-A试样在3253㊁2906c m-1和1051c m-1处出现吸收峰,分别归因于聚乙烯醇分子链中O H伸缩振动㊁C H 伸缩振动和C O伸缩振动[19];P A N I试样在1294㊁1491c m-1和1572c m-1处出现吸收峰,分别归因于聚苯胺分子链中C N伸缩振动㊁醌环和苯环结构振动的特征峰,在1122c m-1处出现的吸收峰为质子化-N H+的特征吸收峰,表明所合成的聚苯胺为掺杂态[20];单一的H C N T s试样并未出现明显的红外吸收峰;H P P A复合气凝胶同时出现了聚乙烯醇和聚苯胺的红外特征吸收峰,且未出现新的红外吸收峰㊂H P P A试样中O H伸缩振动(3224c m-1)㊁C N伸缩振动(1296c m-1)以及质子化-N H+伸缩振动(1122c m-1)的吸收峰均出现红移现象,这是由于聚乙烯醇和聚苯胺分子链之间形成的氢键作用[17]以及聚苯胺分子链和螺旋碳纳米管之间存在的相互作用所形成的π-π共轭效应[21]㊂不同H P P A复合气凝胶试样的红外吸收峰位置基本相同,但在1491c m-1(醌环结构)和1572c m-1(苯环结构)处的聚苯胺特征吸收峰的强度不同,表明H P P A复合气凝胶中聚苯胺的形成且含量不同㊂图2P V A-A㊁P A N I㊁H C N T s和H P P A复合气凝胶试样红外光谱图2.3H P P A复合气凝胶试样的拉曼光谱分析图3为P V A-A㊁P A N I㊁H C N T s和H P P A复合气凝胶试样的拉曼光谱图㊂由图3可知:P V A-A无明显的拉曼光谱特征峰,H C N T s试样在1346c m-1和1590c m-1处呈现特征峰,分别对应碳材料的D 带和G带㊂P A N I和H P P A复合气凝胶均呈现典型的聚苯胺拉曼光谱特征峰㊂其中,在1163㊁1486c m-1和1590c m-1处的吸收峰分别对应聚苯胺分子链中醌环的C H弯曲振动㊁C N+基团和C C双键伸缩振动峰[22];在1223c m-1和1620c m-1处的吸收峰分别对应聚苯胺分子链中苯二胺的C N和苯环的C C伸缩振动峰[23];在1223c m-1处的C N伸缩振动峰与1486c m-1处C N+伸缩振动峰,证明样品中聚苯胺分子链为质子掺杂状态;随着苯胺单体含量升高,3种H P P A551第2期刘德运等:碳纳米管-聚苯胺/聚乙烯醇复合气凝胶的制备及其吸波性能复合气凝胶位于1486c m -1处的C N +伸缩振动峰因共轭效应增强及电荷离域增大,致使该峰强度逐渐降低[24]㊂图3 P V A -A ㊁P A N I ㊁H C N T s 和H P P A复合气凝胶试样的拉曼光谱图2.4 H P P A 复合气凝胶试样的X R D 分析为进一步分析材料结构,采用X R D 对材料晶态结构进行分析,结果如图4所示㊂由图4可知:P V A -A 试样在2θ为20ʎ和40ʎ处出现衍射峰分别为聚乙烯醇(101)和(102)晶面的特征衍射峰[17];P A N I 在2θ为20ʎ和25ʎ处出现衍射峰,分别为聚苯胺主链平行的(100)面和主链周期垂直正交的(110)面特征衍射峰,同时峰强度越强表明聚苯胺的结晶性越高[21];H P P A 复合气凝胶试样同时具有聚乙烯醇㊁聚苯胺和螺旋碳纳米管的特征衍射峰,且未发现新的衍射峰,表明H P P A 复合气凝胶没有形成新结晶相;随着在制备过程中苯胺单体含量的增加,H P P A 复合气凝胶试样在2θ=25ʎ处的衍射峰强度逐渐增强,表明复合气凝胶中聚苯胺组分含量的增加㊂图4 P V A -A ㊁P A N I ㊁H C N T s 和H P P A复合气凝胶试样的X R D 曲线2.5 H P P A 复合气凝胶的吸波性能分析基于传输线理论,试样的反射损耗(R L )可通过式(1) (2)计算[25-26]:Z i n =Z 0μr εrt a n h j 2πf d c μr εr(1)R L =20l o gZ i n -Z 0Z i n +Z 0(2)其中:Z 0是自由空间的特征阻抗,Ω;εr 与μr分别是复介电常数和复磁导率;f 为微波频率,H z ;d 是吸波材料的厚度,m ;c 是自由空间中的光速,m /s㊂图5为H P P A 复合气凝胶的反射损耗图㊂由图5可知,H P P A -2复合气凝胶展现出最优异的吸波性能,当厚度为5.21m m ,频率在9.29G H z 处,H P P A -2复合气凝胶最小反射损耗达-69.08d B ,有效吸收频宽为4.20G H z (反射损耗小于-10.00d B),主要归因于气凝胶的多孔结构改善了材料阻抗匹配特性,使电磁波可以有效地进入材料内部,并通过材料内部各个组分之间的多重极化效应的协同作用,将电磁波能量转化为其他能量耗散[27],实现高效电磁波吸收㊂2.6 H P P A 复合气凝胶的电磁参数分析为分析H P P A 复合气凝胶对电磁波损耗机制,对试样复介电常数(εr =ε'-j εᵡ)进行分析㊂复介电常数中实部ε'代表材料的介电储存能力,虚部εᵡ代表材料的介电损耗能力[11]㊂图6为H P P A 复合气凝胶在8.20~12.40G H z 频率范围内的电磁参数㊂随着频率的增加,各试样的ε'和εᵡ值呈现下降趋势,这主要是由电磁波频率散射效应所引起[28]㊂同时,ε'和εᵡ值随聚苯胺含量的增加而增加(图6(a) (b )),表明其介电储存与损耗能力增加㊂图6(c )为H P P A 复合气凝胶的介电损耗曲线,H P P A -3复合气凝胶的介电损耗值最大,且出现多个共振峰,归因于材料内部的多重极化损耗[29]㊂H P P A 复合气凝胶的极化损耗机制可以通过C o l e -C o l e 曲线分析,结果如图7所示㊂图7显示:不同含量的H P P A 复合气凝胶均呈现多个类半圆形状,是由试样的多组分异质界面之间的电荷分布不均匀导致的界面极化效应[30];对比3个样品曲线图发现,H P P A -1与H P P A -2复合气凝胶C o l e -C o l e曲线末端呈现拖尾直线,表明H P P A -1和H P P A -2试样电磁波损耗主要以导电损耗为主;H P P A -3复合气凝胶C o l e -C o l e 曲线中出现多个严重畸形的半圆形状,表明其在电磁场作用下存在多个极化损耗过程,具有较强的极化损耗能力㊂651浙江理工大学学报(自然科学)2024年第51卷图5 H P P A 复合气凝胶试样的反射损耗图基于传输线理论,衰减常数(α)可用于表征材料对电磁波的损耗能力,如式(3):α=2cπf (εᵡμᵡ-ε'μ')+(εᵡμᵡ-ε'μ')2+(εᵡμ'-εᵡμ')2(3) 通常,α值越大,代表试样对电磁波损耗能力越强㊂图8为试样在8.20~12.40G H z 频率范围内的衰减常数曲线㊂在X 波段范围内,H P P A 复合气凝胶材料的衰减常数值随着聚苯胺的含量增加而升高,其中H P P A -3的衰减常数最大可达180以上(图8),表明该材料具有优异的电磁波损耗能力㊂优异的吸波性能不仅要求材料本身具有较强的损耗能力,还要求其具备良好的阻抗匹配特性[31]㊂751第2期刘德运等:碳纳米管-聚苯胺/聚乙烯醇复合气凝胶的制备及其吸波性能图6 H P P A 复合气凝胶试样的电磁参数图图7 H P P A复合气凝胶试样的C o l e-C o l e 曲线图8 H P P A复合气凝胶试样的衰减常数图当吸波材料的输入阻抗与自由空间阻抗比值(|Z i n/ Z0|)为1时,允许电磁波尽可能多地进入吸收材料内部,实现电磁波能量的损耗㊂图9为8.20~ 12.40G H z频率范围内H P P A复合气凝胶的阻抗匹配特性曲线㊂由图9中可得,H P P A-1与H P P A-3的整体阻抗匹配值与1相差较远,表明该材料的阻抗匹配特性较差;H P P A-2复合气凝胶的阻抗匹配值更接近于1,说明H P P A-2复合材料具有良好的阻抗匹配特性,电磁波能有效地进入吸波体内部,从而实现对电磁波能量的损耗㊂3结论为制备高性能复合气凝胶吸波材料,本文以图9 H P P A复合气凝胶的阻抗匹配曲线P V A为三维骨架基体,以H C N T s和P A N I为吸波剂,通过定向冷冻和原位聚合法制备了具有定向三维多孔结构的H P P A复合气凝胶,并分析了复合气凝胶吸波材料结构和吸波剂对体系吸波性能的影响,主要结论如下:a)通过定向冷冻和低温原位聚合制备的H P P A 复合气凝胶在平行于冰晶生长方向上具有排列规整的垂直孔道骨架结构;在垂直于冰晶生长方向上, H P P A复合气凝胶的垂直孔道之间形成鱼骨状支架,掺杂态P A N I在材料内部聚合形成,且未发生新的化学反应㊂b)在H C N T s质量浓度为5g/L,苯胺浓度为0.10m o l/L的条件下制备的H P P A复合气凝胶试851浙江理工大学学报(自然科学)2024年第51卷样显示出最优异的吸波性能,当厚度为5.21m m,频率为9.29G H z处,最小反射损耗达-69.08d B,有效吸波频宽为4.20G H z;c)H P P A复合气凝胶优异的吸波性能主要归因于其定向的多孔结构和非均匀介质界面形成的良好阻抗匹配特性和多重极化协同效应㊂本结果为开发高性能复合气凝胶吸波材料提供了参考㊂参考文献:[1]W a n g C X,L i u Y,J i a Z R,e t a l.M u l t i c o m p o n e n t n a n o p a r t i c l e s s y n e r g i s t i c o n e-d i m e n s i o n a l n a n o f i b e r s a s h e t e r o s t r u c t u r e a b s o r b e r s f o r t u n a b l e a n d e f f i c i e n t m i c r o w a v e a b s o r p t i o n[J].N a n o-M i c r o L e t t e r s,2023, 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191:625-635.[9]L v H L,Y a n g Z H,P a n H G,e t a l.E l e c t r o m a g n e t i ca b s o r p t i o n m a t e r i a l s:c u r r e n t p r o g r e s s a n d n e w f r o n t i e r s[J].P r o g r e s s i n M a t e r i a l s S c i e n c e,2022,127:100946.[10]肖维新,袁静,严开祺,等.生物聚合物气凝胶的制备与应用研究进展[J].材料导报,2022,36(20):243-252.[11]L i X,Z h u L T,K a s u g a T,e t a l.C h i t i n-d e r i v e d-c a r b o n n a n o f i b r o u s a e r o g e l w i t h a n i s o t r o p i c p o r o u s c h a n n e l s a n d d e f e c t i v e c a r b o n s t r u c t u r e s f o r s t r o n g m i c r o w a v e a b s o r p t i o n[J].C h e m i c a l E n g i n e e r i n g J o u r n a l,2022, 450:137943.[12]L i X,Y u L M,Z h a o W K,e t a l.P r i s m-s h a p e d h o l l o wc a r b o nde c o r a t e d w i t h p o l y a n i l i n ef o r m i c r o w a v e a b s o r p t i o n[J].C h e m i c a l E ng i n e e r i n g J o u r n a l,2020, 379:122393.[13]Z h a n g Z,T a n J W,G u W H,e t a l.C e l l u l o s e-c h i t o s a nf r a m e w o r k/p o l y a i l i n e h y b r i d a e r og e l t o w a r d th e r m a li n s u l a t i o n a n d m i c r o w a v e a b s o r b i n g a p p l i c a t i o n[J].C h e m i c a l E n g i n e e r i n g J o u r n a l,2020,395:125190.[14]魏冀璇,赵春霞,王智萱,等.聚乙烯醇气凝胶研究进展[J].化工新型材料,2022,50(1):248-251. [15]H e D X,Y a n g X J,H u a n g D S,e t a l.P a l l a d i u m-M X e n e s a e r o g e l d e c o r a t e d b y a l k y n e f u n c t i o n a l i z e d p o l y v i n y l a l c o h o l(P V A)a s a h i g h l y e f f i c i e n t c a t a l y s t f o r e l e c t r o c a t a l y t i c h y d r o g e n e v o l u t i o n[J].C h e m i c a l P h y s i c s L e t t e r s,2022,805:139942.[16]L i u S D,L i D S,C h e n X M,e t a l.B i o m i m e t i cc u t t l e b o n e p o l y v i n y l a l c o h o l/c a r b o n n a n o t u b e s/ h yd r o x y a p a t i te a e r o g e l s c af f o l d s e n h a n c e d b o n e r eg e n e r a t i o n[J].C o l l o i d s a n d S u r f a c e s B:B i o i n t e r f a c e s,2022,210:112221.[17]L i L,Z h a n g Y,L u H Y,e t a l.C r y o p o l y m e r i z a t i o n e n a b l e sa n i s o t r o p i c p o l y a n i l i n e h yb r i d h y d r o g e l s w i t h s u p e r e l a s t ic i t y a nd h i g h l y def o r m a t i o n-t o l e r a n t e l e c t r o c h e m i c a l e n e rg y s t o r a g e[J].N a t u r e C o m m u n i c a t i o n s,2020,11(1):62.[18]J i a n g Y,C h e n Y,L i u Y J,e t a l.L i g h t w e i g h t s p o n g yb o n e-l i k e g r a p h e n e@S i C a e r o g e lc o m p o s i t e s f o r h i g h-p e r f o r m a n c e m i c r o w a v e a b s o r p t i o n[J].C h e m i c a lE n g i n e e r i n g J o u r n a l,2018,337:522-531.[19]张灿英,张丽,赵辰,等.太阳能水蒸发P V A/炭黑/聚氨酯复合材料的制备及性能研究[J].化工新型材料,2022,50(8):111-116.[20]W a n g H G,M e n g F B,H u a n g F,e t a l.I n t e r f a c e m o d u l a t i n g C N T s@P A N i h y b r i d s b y c o n t r o l l e d u n z i p p i n g o f t h e w a l l s o f C N T s t o a c h i e v e t u n a b l e h i g h-p e r f o r m a n c e m i c r o w a v e a b s o r p t i o n[J].A C S A p p l i e d M a t e r i a l s&I n t e r f a c e s,2019,11(12):12142-12153.[21]B e n J W,S o n g Z Y,L i u X K,e t a l.F a b r i c a t i o n a n de l e c t r o c h e m i c a l p e rf o r m a n c e o f P V A/C N T/P A N If l e x i b l e f i l m s a s e l e c t r o d e s f o r s u p e r c a p a c i t o r s[J]. N a n o s c a l e R e s e a r c h L e t t e r s,2020,15(1):151.951第2期刘德运等:碳纳米管-聚苯胺/聚乙烯醇复合气凝胶的制备及其吸波性能[22]Z h a n g L,Z h a n g Z L,L v Y Y,e t a l.R e d u c e dg r a p h e n e o x i d e a e r o g e l s w i t h u n i f o r m l y s e l f-a s s e m b l e d p o l y a n i l i n e n a n o s h e e t s f o r e l e c t r o m a g n e t i c a b s o r p t i o n [J].A C S A p p l i e d N a n o M a t e r i a l s,2020,3(6):5978-5986.[23]Y a n g W T,S u n J W,L i u D Y,e t a l.R a t i o n a l d e s i g n o fh i e r a r c h i c a l s t r u c t u r e o f c a r b o n@p o l y a n i l i n e c o m p o s i t e w i t h e n h a n c e d m i c r o w a v e a b s o r p t i o n p r o p e r t i e s[J].C a r b o n,2022,194:114-126.[24]L i P P,J i n Z Y,P e n g L L,e t a l.S t r e t c h a b l e a l l-g e l-s t a t ef i b e r-s h a p e d s u p e r c a p a c i t o r s e n a b l e d b y m a c r o m o l e c u l a r l y i n t e r c o n n e c t e d3Dg r a ph e n e/n a n o s t r u c t u r e d c o n d u c ti v e p o l y m e r h y d r o g e l s[J].A d v a n c e d M a t e r i a l s,2018,30 (18):e1800124.[25]孙佳文,朱曜峰.多相碳粒硅橡胶柔性吸波膜的制备及其性能[J].浙江理工大学学报(自然科学版), 2022,47(4):533-541.[26]杨期鑫,俞璐军,董余兵,等.磁功能化多孔生物质炭复合材料的制备及吸波性能[J].新型炭材料,2019, 34(5):455-463.[27]L i u Q H,C a o Q,B i H,e t a l.C o N i@S i O2@T i O2a n d C o N i@A i r@T i O2m i c r o s p h e r e s w i t h s t r o n g w i d eb a n d m ic r o w a v e a b s o r p t i o n[J].Ad v a n ce d M a t e r i a l s,2016,28(3):486-490.[28]A b d a l l a I,E l h a s s a n A,Y u J Y,e t a l.A h y b r i dc o m p r i s ed o f p o r o u s c a r b o n n a n o f i be r s a n d r G Of o r e f f i c i e n t e l e c t r o m ag n e t i c w a v e a b s o r p t i o n[J].C a r b o n, 2020,157:703-713.[29]H o u T.Q,W a n g B.B,M a M.L,e t a l.P r e p a r a t i o n o f t w o-d i m e n s i o n a l t i t a n i u m c a r b i d e(T i3C2T x)a n d N i C o2O4c o m p o s i t e s t o a c h i e v e e x c e l l e n t m i c r o w a v e a b s o r p t i o n p r o p e r t i e s[J].C o m p o s i t e s P a r t B:E n g i n e e r i n g,2020,180:107577.[30]L i Y,M e n g F B,M e i Y,e t a l.E l e c t r o s p u n g e n e r a t i o n o f T i3C2T x M X e n e@g r a p h e n e o x i d e h y b r i d a e r o g e l m i c r o s p h e r e s f o r t u n a b l e h i g h-p e r f o r m a n c e m i c r o w a v e a b s o r p t i o n[J].C h e m i c a l E n g i n e e r i n g J o u r n a l,2020, 391:123512.[31]W a n g T,C h e n G,Z h u J H,e t a l.D e e p u n d e r s t a n d i n g o f i m p e d a n c e m a t c h i n g a n d q u a r t e r w a v e l e n g t h t h e o r y i n e l e c t r o m a g n e t i c w a v e a b s o r p t i o n[J].J o u r n a l o f C o l l o i d a n d I n t e r f a c e S c i e n c e,2021,595:1-5.(责任编辑:张会巍)061浙江理工大学学报(自然科学)2024年第51卷。

刹车片国内车型-FMSI编号

R
皇冠3.0，MS132
F
丰田光冠
F
丰田赛力卡
光冠
F
姬先达? 皇冠MS-60，MS-70
皇冠2000，3000
F
0.5T皮卡
F
花冠1600
F
赛力卡ESP
陆地巡洋舰KJ60 FJ60
F
FJ40-75四缸大吉普
皮卡
F
丰田
皇冠2.0，2.6，2.8，
F MS112 MS122，TS120，5M
YS120
F
83-80 79-78
90-81 87-86 88-86
83-79
74-70 83-80 79-78 82-79 81-79 83-79 88-85
88-85 95-84
82
92-87
91-86
98-92 98-86 85-83
74 89-83
92 87-85 88-86
83
对应码备注
2062
D662/D30 4
R
吉FJ80 FZJ80
陆地巡洋舰HDJ81V
D488 D613 D572 D325 D488
D476 D476 D501
D500
D606
D606 D606 D606 D606 D606 D606 D606
D325 D325 D325 D325
D572 D571
D304 D304 D304
D501
D502
标志405
F 奥迪200
奥迪200
F
年代 85-80 75-73 84-75 87-85 82-80 84-83 84-82 97-90 87-84 91-86
88 95-90

多种彩电解锁方法

多种彩电解锁方法，解童锁方法1．乐华N21K8:打开遥控器在最下面有一个空键就是工厂键，按一下既可进入维修状态，可找到童锁项，也可以按菜单+6483，3次既可进入！2．.乐华100Hz机心万能密码是987；3．乐华N21K8解童锁，打开遥控器在最下面有一个空键就是工厂键，按下可以进入维修状态，可找到童锁项，也可以按菜单+6483，3次进入！4．乐华三菱+飞利浦机心万能密码是2442；5．乐华21A1童锁输入024，童锁自行消除海信锁定菜单通用密码汇总1．A12机芯（LA76810）通用密码：7681 代表机型：TC1423 TC2175G TC2181F TC2961L TC2588D/L TC2199/D/M/A TF2110D等2．LA76818机芯通用密码：7688 代表机型：TC1418H TC2102H TC2188H TC2502H/06H TC2588H TF2502H TF2588H等3．TB1238机芯通用密码：1238（或2175，但限次数）代表机型：TC2100 TC2139A TC2175/A TC2500 TC2566D TC2900 TC2902G TC2910D T C2940A TF2988/G TF2989 TF25100等4．TB1251机芯通用密码：1251 代表机型：TC2908U TC3401 TC3842D/3488D TF2908U TF3488D等5．H98C（TB1227）机芯通用密码：8888 代表机型：TF2900DP TF2988DP TF3488DP 等6．TG-1B(TB1227)无通用密码,锁定后需换存储器代表机型TC2978N TF2998D TC3418D TF2999A等7．H97B (TA8880)机芯通用密码：8880 代表机型：TC2939系列TC2979系列TC3418系列TF2999G/N等8．21～25寸飞利浦UOC（TDA9373、9370）通用密码：1963 代表机型：TC2102D/F TC2175GF TF2106D TF2107F TF2507F等9．29寸飞利浦UOC(UOC001、UOC002) 通用密码：9012 代表机型：TC2906H TC2908UF TC2911AL TC2911UF TC2977 TC2418UF TF2906H/07H TF2911UF等10．21寸东芝单片TMPA8823（8803）通用密码：3088 代表机型：TC2111A TC2118H TF2106A等11．25～34寸东芝单片TMPA8829(8809) 通用密码：设定到186频道，按AV1，输入88090916 代表机型：TF2902D TF3406D TF2902DH TC2918DH TF2902DH等12．TDF2988(西门子胶片系列) 通用密码：8888/9400 代表机型：TDF2918 TDF2988 ETV2988等13．DP2999（NDSP胶片系列）通用密码：8843（或2999）代表机型：DP2999 ITV2911 ITV2988等14．泰鼎胶片系列通用密码：8052 童锁功能可按遥控任意键解开代表机型：DP2988H DP2906H等15．飞利浦胶片系列通用密码：7118 代表机型：TDF2901 DP2906G16.（飞利浦数字高清系列）初始密码：8888 通用密码：7118 代表机型：HDP2908/HDP2906D/HDP3406D17.泰鼎高清系列通用密码：8052 使用遥控器开机即可解开童锁功能代表机型：HDP2902H/06H HDP2910L HDP2919 HDP3406H HDP3410L等18.GS高清系列通用密码：5147 代表机型：HDP2911G/H HDP2919H HDP3411G/H HDP3419H等19. HDTV系列通用密码：8052 代表机型：HDTV320120. MST系列初始密码：8888 通用密码：6126代表机型：HDP291021.液晶TLM3277 通用密码：1111超级密码：同时按遥控器上“静音”和“9”键海尔童锁功能有如下几种解锁方式：1.用菜单键解锁：按“MENU”键（或“FUNC”键），选择功能显示菜单（系统设定菜单），在子菜单里有童锁一项，按P+/-来移动光标移动到“童锁”字样处，按V+/-键将童锁设置为“关”，即将童锁功能关闭；2.按屏显键解锁：此类机器童锁后屏幕上无锁定标志，但是按屏显键节目号是红色：此类机器的解锁方法很简单：按遥控器上的“DISPLAY”键（频道号显示键），持续3秒钟（或5秒钟）以上，屏幕显示的节目号由红色变成绿色即可解锁。

万能解锁

万能解锁部分用户使用了彩电密码锁或童锁功能。

若忘记了密码，会出现不能自动搜台、或屏幕呈现黑屏状态提示输入密码，或不能换台等现象。

不知道密码也会使接修彩电的维修员一筹莫展。

现介绍几种品牌彩电的解锁万能码。

1.海信东芝TB1238机心万能密码是2175或1238；海信TF2507F自动/手动搜索节目编辑微调均上锁，可把“限时“开关关掉需要的密码为1963注：海信锁定菜单通用密码汇总1/．LA76818机芯通用密码：7688 代表机型：TC1418H TC2102H TC2188H TC2502H/06H TC2588H TF2502H TF2588H等2/．TG-1B(TB1227)无通用密码,锁定后需换存储器代表机型TC2978N TF2998D TC3418D TF2999A等3/．A12机芯（LA76810）通用密码：7681 代表机型：TC1423 TC2175G TC2181F TC2961L TC2961AD TC2588D/L TC2198C TC2199/D/M/A TF2110D等TF2908U TF3488D等5/．H98C（TB1227）机芯通用密码：8888 代表机型：TF2900DP TF2988DP TF3488DP等6/．TB1238机芯通用密码：1238（或2175，但限次数）代表机型：TC2100 TC2139A TC2175/A TC2500 TC2566D TC2588A TC2900 TC2902G TC2910D TC2940A TF2988/G TF2989 TF25100等并置“锁定全清”项为开7/．21寸东芝单片TMPA8823（8803）通用密码：3088 代表机型：TC2111A TC2118H TF2106A等8/．H97B (TA8880)机芯通用密码：8880 代表机型：TC2939系列TC2979系列TC3418系列TF2999G/N等9/．21～25寸飞利浦UOC（TDA9373、9370）通用密码：1963 代表机型：TC2102D/F TC2175GF TF2106D TF2107F TF2507F等10/．29寸飞利浦UOC(UOC001、UOC002) 通用密码：9012 代表机型：TC2906H TC2908UF TC2911AL TC2911UF TC2977 TC2418UF TF2906H/07H TF2911UF等11/．25～34寸东芝单片TMPA8829(8809) 通用密码：设定到186频道，按AV1，输入88090916 代表机型：TF2902D TF3406D TF2902DH TC2918DH TF2902DH等12/．TDF2988(西门子胶片系列) 通用密码：8888/9400 代表机型：TDF2918 TDF2988 ETV2988等13/．DP2999（NDSP胶片系列）通用密码：8843（或2999）代表机型：DP2999 ITV2911 ITV2988等14/．泰鼎胶片系列通用密码：8052 童锁功能可按遥控任意键解开代表机型：DP2988H DP2906H等15/．飞利浦胶片系列通用密码：7118 代表机型：TDF2901 DP2906G16/.（飞利浦数字高清系列）初始密码：8888 通用密码：7118 代表机型：HDP2908/HDP2906D/HDP3406D17/.泰鼎高清系列通用密码：8052 使用遥控器开机即可解开童锁功能代表机型：HDP2902H/06H HDP2910L HDP2919 HDP3406H HDP3410L等18/.GS高清系列通用密码：5147 代表机型：HDP2911G/H HDP2919H HDP3411G/H HDP3419H等19/. HDTV系列通用密码：8052 代表机型：HDTV320120/. MST系列初始密码：8888 通用密码：6126代表机型：HDP291021/.液晶TLM3277 通用密码：1111超级密码：同时按遥控器上“静音”和“9”键2.乐华100Hz机心万能密码是987；3.乐华三菱+飞利浦机心万能密码是2442；例RH29NED4.夏华E系列三洋单片机万能密码是4321；夏华TS2130 在被锁频道按音乐键3次，夏华XT21A6N 在被锁频道按0807《0870》5.康佳T5435彩电的解锁方法是：同时按面板上的“频道+”和“频道-”键；6.长虹A6机心的解锁方法是同时按遥控器上的“静音”键和“显示”键；7.长虹CN-12机心的解锁方法是同时按遥控器上的“F”键和“静音”键，或“F”键和“返回”键。

2906介绍

Internal Block Diagram
Rev. 1.0.4
©2001 Fairchild Semiconductor Corporation
LM431A/LM431B/LM431C
Absolute Maximum Ratings
(Operating temperature range applies unless otherwise specified.) Parameter Cathode Voltage Cathode current Range (Continuous) Reference Input Current Range Power Dissipation M, Z Suffix Package Operating Temperature Range LM431xC LM431xI Storage Temperature Range TOPR TSTG -25 ~ + 85 -40 ~ + 85 -65 ~ + 150
Symbol
VREF
Conditions
VKA=VREF, IKA=10mA
LM431A
LM431B
LM431C
Min. Typ. Max. Min. Typ. Max. Min. Typ. Max.
2.450 2.500 2.550 2.470 2.495 2.520 2.482 2.495 2.508
0.25 –0.05
0~15°
+0.10
0.010 –0.002
+0.004
9
LM431A/LM431B/LM431C
Mechanical Dimensions (Continued)

ISOTS 16949-2009 IATF认可的TS认证机构名录(219最新发布)Certification Body Official List

E-mail: egijselinck@vincotte.be Web: www.vincotte.be
BVC（原名：BVQI）
Bureau Veritas Certification
2nd Floor, Tower Bridge Court 224-226 Tower Bridge Road SE1 2TX London UK Contact: Mr. Peter Bonnaerens Tel: + 44 777 33 93 788 Fax:
E-mail: frank.lomas@ Web:
E-mail: peter.bonnaerens@ Web:
ISO/TS 16949:2002 Certification Body Official List
E-mail: alfredo@.br Web: .br
IRQS
Indian Register Quality Systems
Indian Register of Shipping 52A, Adi Shankaracharya Marg, Opp. Powai Lake Powai, Mumbai 400 072, Maharashtra, India Contact: Mr. S. Kumar Tel: + 91 22 3051 9400 Fax: + 91 22 2570 3611
E-mail: christelle.sauvage@ Web:
AQA
AQA International, LLC
501 Commerce Drive NE Columbia, SC 29223 USA Contact: Mr. Carl Blazik Tel: + 1 803 779 8150 Fax: + 1 803 779 8109

碳化硅晶须与颗粒分散性能研究

53科技资讯 S CI EN CE & T EC HNO LO GY I NF OR MA TI ON 工业技术碳化硅晶须一般采用气相反应法和固体材料法生产,前者可以合成纯度较高的产品,有时可接近100%,后者投资和运行成本较低,易于生产控制,目前已广泛应用到实际中[1～3]。

但采用固体材料法生产出的晶须产品纯度很低,混杂有大量的碳化硅颗粒[4～5],利用碳化硅晶须和碳化硅颗粒的物理化学性质的不同达到分散的目的,是实现碳化硅晶须与颗粒分离的先决条件。

对于碳化硅产品的分散通常有研磨法、棒磨法、超声波分散和添加分散剂的方法。

研磨和棒磨会打断晶须产品,不适合采用[6]。

除了超声波分散外,可以采用添加分散剂的方法,既能起到分散的作用,又不会对晶须产生破坏[7]。

1 试验材料与方法1.1试验材料试验用碳化硅晶须和碳化硅颗粒样品取自徐州某公司由稻壳生产并提纯的的产品,碳化硅晶须提纯产品TE M照片见图1;六偏磷酸钠、水玻璃、木质素等分散剂均为工业纯试剂。

1.2研究方法试验采用自制沉降分析仪测定不同条件下分散率。

分散率的计算:将分散后的料液加入200mL量筒中,在t时刻观察清水层与下面絮体的分界面,记录分界面的高度,按下式计算分散率,η=ht/h 0,其中,h t 为t时刻记录高度;h 0为初始高度。

2 试验结果与讨论2.1碳化硅晶须和碳化硅颗粒的性质对比碳化硅晶须和碳化硅颗粒是同一种物质、同种晶型,它们之间的唯一差异就是形态。

由于形态的差异导致了一系列物理和化学性质的不同。

2.1.1碳化硅晶须和碳化硅颗粒的物理性质比较由稻壳热分解产生的碳化硅产品中,碳化硅晶须含量为30%左右,碳化硅颗粒含量约60%左右,其余的是碳、石英以及其它杂质[8]。

碳化硅晶须和碳化硅颗粒的物理性质如表1所示。

从碳化硅晶须和碳化硅颗粒的物理性质的比较可以看出,在密度和颜色等方面,晶须和颗粒区别不大,它们之间性质差异较大之处是它们的外形和堆密度,这是因为碳化硅晶须常相互交织在一起,近似于网状,所包含的孔隙大,相对地所占空间就大,使得它的堆密度比碳化硅颗粒的堆密度要小得多。