《汽油机爆震特征提取与诊断研究》硕士学位论文

工学硕士学位论文汽油机爆震特征提取与诊断研究张建峰哈尔滨工业大学2003年7月国内图书分类号：U464国际图书分类号：629工学硕士学位论文汽油机爆震特征提取与诊断研究硕士研究生：张建峰导师：杨建国副教授申请学位：工学硕士学科、专业：车辆工程所在单位：汽车工程学院答辩日期：2003年7月授予学位单位：哈尔滨工业大学Classified Index：U464U.D.C: 629Dissertation for the Master’s Degree in Engineering RESEARCH ON ENGINE KNOCK FEATURE EXTRACTION AND FAULTDIAGNOSISCandidate:Supervisor:Academic Degree Applied for: Speciality:Date of Defence:Degree-Conferring-Institutio: Zhang JianfengAssociate Prof. Yang Jianguo Master of Engineering Vehicle EngineeringJuly, 2003Harbin Institute of Technology哈尔滨工业大学工学硕士学位论文摘要火花点火式汽油机广泛应用于各种汽车。

汽油机爆震的存在制约了其动力性和经济性能的改善。

研究有效的爆震信号特征的提取方法，进而准确的诊断爆震的强度，一方面可以避免爆震的危害，另一方面为控制汽油机工作在爆震边界区以提高其动力性和经济性能奠定基础。

本文主要针对爆震特征的提取方法、爆震强度指标和诊断策略进行研究。

分析了短时傅立叶变换(STFT)、Wigner-Ville分布(WVD)和离散小波变换(DWT)在处理非平稳信号时的优势和不足。

给出了各自的离散化算法。

分析了Wigner-Ville分布中产生交叉项的原因，并着重研究了抑制交叉项的方法，即平滑伪Wigner-Ville分布(SPWD)。

结果表明：SPWD可以有效地抑制交叉项。

对STFT、SPWD和DWT三种时频分析方法处理非稳态信号的有效性进行了仿真研究，论证了三种方法提取冲击特征的有效性。

将STFT、SPWD和DWT三种时频分析方法应用于汽油机缸内压力信号和缸盖上的振动信号的处理，对三种方法进行了爆震特征提取的实际应用研究，应用和分析结果表明：STFT和SPWD两种方法不但能从汽油机缸内压力信号中有效提取爆震特征，而且还能从缸盖上的振动信号中有效提取爆震特征。

SPWD方法计算量大，耗时长。

STFT和SPWD只有在适当滤掉低频成分的前提下，才能有效地提取爆震特征。

DWT方法可以直接从缸内压力信号和机体振动信号中有效地提取爆震特征。

提出了两种基于DWT的爆震强度指标，即信号DWT结果特征域上信号的平均能量(KI)和峰值(Amax)。

这两种强度指标作为压力信号和振动信号统一的强度指标，实用性较高。

提出了一种以检测信号的爆震指标与爆震指标的参考值之间的差值来衡量爆震强弱的诊断方法。

应用该方法诊断某型HYUNDAI汽油机的爆震，结果表明，该方法能够较准确的评价爆震的强弱程度。

该诊断方法不仅适用于缸内压力信号，而且同样适用于机体振动信号。

关键词汽油机；爆震；特征提取；小波变换；爆震强度- I -哈尔滨工业大学工学硕士学位论文AbstractSpark ignition engines have been widely used on various cars. Knock limits the improvement of power and fuel economy of car engines. It is of great significance to find an effective method to be used to extract the knock feature from a measured signal, and a method to be used to diagnose the knock intensity exactly. These are the focus of this thesis.The effectiveness and shortcomings of the short time Fourier transform (STFT), the Wigner-Ville distribution (WVD) and the discrete wavelet transform (DWT) in processing non-stationary signals are studied. The discrete algorithms of the three methods are presented. The cause of cross-terms inheres in WVD is studied. Besides, the smooth pseudo Wigner-Ville distribution (SPWD) which is used to suppress the cross-terms in WVD is analyzed. It is shown that the cross-terms are suppressed effectively in SPWD. In order to demonstrate the fact that the three methods, that is, STFT, SPWD and DWT, are efficient in processing non-stationary signals, simulations are implemented. Then the effectiveness to extract shock feature from a non-stationary signal by the three methods is demonstrated.The applications of STFT, SPWD and DWT to extract knock feature from both the pressure signals measured from an engine cylinder and the vibration signals measured on an engine head is studied. The results are as follow. STFT and SPWD can extract engine knock feature effectively from both the pressure signals and the vibration signals. SPWD needs more computational effort and is timely cost. Knock feature can be extracted by STFT and SPWD only if certain low-frequency components are filtered from the original signals, while knock feature is extracted outstandingly by DWT from the two kinds of original signals.Based on DWT, two kinds of knock intensities are presented. They are the average energy (KI) of a signal in the characteristic domain of DWT and the peak (Amax) of the signal in the characteristic domain of DWT. The two knock intensities are very practical when work as the unified knock intensity for both the pressure signal and the vibration signal. A diagnosis strategy is presented, that is, using the difference between the knock intensity value of a measured signal- II -哈尔滨工业大学工学硕士学位论文and the referential value to determine the intensity of knock. This strategy is applied to diagnose the knock for a HYUNDAI engine. It is shown that the strategy can judge knock intensities effectively. The strategy can work well not only for the pressure signals but also for the vibration signals.Key words SI engine; knock; feature extraction; wavelet transform;knock intensity- III -哈尔滨工业大学工学硕士学位论文目录摘要 (I)Abstract (II)第1章绪论 (1)1.1 课题的来源以及研究的目的和意义 (1)1.2 国内外的研究现状 (2)1.2.1 爆震燃烧的研究现状 (2)1.2.2 爆震测量的研究现状 (3)1.2.3 爆震特征提取方法的研究现状 (3)1.2.4 爆震强度指标的研究现状 (5)1.3 主要研究内容 (5)第2章爆震信号处理方法的研究 (6)2.1 爆震信号的特点 (6)2.2 短时傅立叶变换 (8)2.3 Wigner-Ville分布 (10)2.3.1 Wigner-Ville分布的定义 (10)2.3.2 模糊函数与Cohen类时频分布 (11)2.3.3 交叉项的抑制 (12)2.4 小波变换 (15)2.4.1 小波变换的时频分析特性 (15)2.4.2 小波变换结合FFT的信号处理方法 (17)2.5 本章小结 (23)第3章爆震信号的特征提取 (24)3.1 汽油机爆震试验 (24)3.2 爆震特征的提取 (25)3.2.1 应用短时傅立叶变换提取爆震特征 (27)3.2.2 应用平滑伪Wigner-Ville分布提取爆震特征 (29)3.2.3 应用小波变换提取爆震特征 (31)3.3 本章小结 (34)第4章爆震指标及诊断策略的研究 (36)- IV -哈尔滨工业大学工学硕士学位论文4.1 爆震强度评价指标的选择 (36)4.2 压力信号和振动信号的爆震强度指标的比较 (37)4.3 爆震诊断策略 (39)4.4 本章小结 (45)结论 (46)参考文献 (47)攻读硕士学位期间发表的学术论文 (51)哈尔滨工业大学硕士学位论文原创性声明 (52)哈尔滨工业大学硕士学位论文使用授权书 (52)致谢 (53)- V -哈尔滨工业大学工学硕士学位论文第1章绪论1.1 课题的来源以及研究的目的和意义本文的研究内容是哈工大博士启动基金项目“小波分析在汽油机爆震检测中应用的研究”的一部分。