YAMAHA YV100XG异型元件识别

设定：
Alignment Group: Special Alignment type: Special Body Size X : 4.02 Body Size Y : 3.28 Body Size Z : 1
Lead Group N: 1
Lead Group S: 1
Lead Number N1: 1
Lead Width N1: 4 Reflectll N1: 3.3
Find Pos X N1: 0
Find Pos Y N1: 1.7 Lead Number S1: 1
Lead Width S1: 4 Reflectll S1: 3.3
Find Pos X S1: 0
Find Pos Y S1: -1.7 Algorithm : Normal Base Alignment : Sp. Quad Vision Option 4 : 0此元件有个小耳朵，与本体反光度比较相近故比较难识别
Alignment Group: Special Alignment type: Special Body Size X : 7 Body Size Y : 13 Body Size Z : 3.5 Lead Group S: 1
Lead Group E: 1
Lead Group W: 1 Lead Number S1: 2
Lead Pitch S1: 5
Lead Width S1: 0.3 Reflectll S1: 1
Find Pos X S1: -3 Find Pos Y S1: -6.5 Lead Number E1: 1
Lead Width E1: 0.8 Reflectll E1: 0.9 Find Pos X E1: 3
Find Pos Y E1: 2 Lead Number W1: 2 Lead pitch W1: 2.5 Lead Width W1: 0.8 Reflectll W1: 0.9 Find Pos X W1: -2.5 Find Pos Y W1: 2.5 Algorithm : Normal Base Alignment : None Vision Option 4 : 0此元件下面两个小脚造成干扰，故以此两脚进行识别。

YAMAHA YV100XG可以精确稳定的识别贴装手机屏蔽盖，对元器件的参数需要有特定的设置，如下：
Alignment Group: Special
Alignment Type : Special
在元器件参数SHAPE一项中，
Algorithm : special 4
Base Alignment: As Mark
Vision option 4: 64
所有RefelectLL都设置为0。

在元器件参数Vision中
Comp.Threshold: 0
另外需要注意的是这种方式识别的是屏蔽盖上的圆孔。

即将圆孔当成管脚来识别。

所以有关管脚的参数都以圆孔的参数来确定。

在元器件参数中元件的尺寸不是屏蔽盖的实际尺寸，而是你所选孔的外沿的距离。

如果孔多的话可以任选3个或4个孔即可。

不过这种方式因为不是实际的尺寸，可能在优化后造成相邻头吸取元件后互相干扰。

如果屏蔽盖没有孔且形状比较规则，可以用Spec.Quad方式识别。

ＹＧ设备设定（识别点为发光部）
Ｙ
Ｇ
ＸＧ设备设定（识别点为发光部）
如果为圆形则
Reflectll不设置
随着SMT技术的不断发展,一些客户的特殊元件形状也越来越复杂,对于没有规则的外轮廓的元件如果其内部有某些特征点可以用来识别的时候经常比较困难,下面对"Special"类型下的Vision Option参数简单作一点介绍.本文介绍是以
YG100机器为例的.
本文中的元件识别方式选用了"Special-Special-Asmark-4General",其中如果实在YVXg机器上没有"4General"选项,实际上在"YVXg"系列机器上可以选择"Special-Special-Asmark-Special4"是一样的效果(已经经过验证).
如上图我们可以选择元件内部的圆点来进行识别,在尺寸设定是我们可以把圆点的直径输入"Lead width"参数中,此时"ReflectLL"参数输入"0"即可,这样机器描绘出的元件管脚形状就是圆形的.下表针对"Vision Option4"参数进行说明.
如"Vision Option4"=64, 表示Noise Cut Inner=0 Noise Cut Outer=0. 从下表中对应关系可以很方便的查出"Vision Option4"的值从0到127对应的Noise Cut Inner以及Noise Cut Outer的数值.
Subject:Regarding the Shielding component recognition function
1. Overview
The slope of ”Controlling line” that composes outline of the component is assumed to be inclination of component, and the center of the circumscribed rectangle of this inclination is made component center.
2. Prerequisite
1. The majority of outline are composed of straight lines in horizontal/vertical direction.
2. Outline must be clear.
(Recognition becomes N.G., when both the red circle part in the above figure become interrupted. )
3. Recognition settings
1) Algorithm
Alignment Group : Special
Alignment Type: Special
Algorithm: Special 8
Base Alignment : Special
2) Shape
Specify the outside dimension of components (the circumscribed rectangle size) .
/
3) Component Threshold
Specify the brightness for component recognition (binarization level). “0”means automatic setting.
4) Component Tolerance
Specify a tolerance of component body size by percentage (%).
５) Search Area
Specify the range of detection.
６) Vision Option 4
When the component image is digitized and shown in binary (black and white), noise may appear outside or inside the component.
76543210<- bit position
s t n2n1
Cut outer noise (0 to 7)
[coefficient: 1] Cut inner
noise (0～7) [coefficient:
8]
Target type [coefficient: 64]
0: Detect target is White / 1: Detect target is Black
Inner & Outer noise cut execution sequence [coefficient: -128]
0: Inner -> Outer 1: Outer -> Inner
This option parameter has the meaning of each bit in the data of one byte. Therefore, when you assume the outer and inner noise cutting value to
be n1/n2,
Target object is White : n2 ×8 + n1
Target object is Black : 64 + n2 ×8 + n1
the value requested by calculating the above-mentioned should be set. For example, when outer noise cutis twice, and inner noise cut is three times, set the following value;
Target object is White :3 ×8 + 2 = 26
Target object is Black :64 + 3 ×8 + 2 = 90
Moreover, when the execution sequence is outer to inner, specify the value in which 128 is subtracted from this value.
In other word, for the above example, specify the following value;
Target object is White : 26 - 128 = -102
Target object is Black :90 - 128 = -38
Alignment Group: Special Alignment type: Special Body Size X : 6
Body Size Y : 7
Body Size Z : 0.5
Lead Group N: 1
Lead Group S: 1
Lead Group E: 0
Lead Group W: 0
Lead Number S1: 1
Lead Pitch S1: 0
Lead Width S1: 6
Reflectll S1: 2
Find Pos X S1: -0
Find Pos Y S1: -2.5
Lead Number N1: 1
Lead Width N1: 6 Reflectll N1: 2
Find Pos X N1: 0
Find Pos Y N1: 2.5 Algorithm :SPECIAL 2 Base Alignment : ASMARK Vision Option 4 : 0
Flip chip recognize
Alignment Group: Special Alignment type: Special Body Size X : 1
Body Size Y : 0.9
Body Size Z : 0.6
Lead Group N: 1
Lead Group S: 1
Lead Group E: 0
Lead Group W: 0
Lead Number S1: 2
Lead Pitch S1: 0.4
Lead Width S1: 0.25 Reflectll S1: 0
Find Pos X S1: -0.2
Find Pos Y S1: -0.2
Lead Number N1: 2
Lead Pitch N1: 0.4
Lead Width N1: 0.25 Reflectll N1: 0
Find Pos X N1: -0.2
Find Pos Y N1: 0.2 Algorithm :SPECIAL 1 Base Alignment : Flip chip Vision Option 4 : 0
V1.21 后遇到Nozzle brightness problem
Alignment Group: Special
Alignment type: Special
Body Size X : 0.58
Body Size Y : 1
Body Size Z : 0.6
Lead Group N: 1
Lead Group S: 1
Lead Group E: 0
Lead Group W: 0
Lead Number N1: 1
Lead Pitch N1: 0
Lead Width N1: 0.58
Reflectll N1: 0.25
Find Pos X N1: 0
Find Pos Y N1: 0.5
Lead Number S1: 1
Lead Pitch S1: 0
Lead Width S1: 0.58
Reflectll S1: 0.25
Find Pos X S1:0
Find Pos Y S1: -0.5
Algorithm :SPECIAL 12
Base Alignment :std chip
Vision Option 4 : 0
Alignment Group: Special Alignment type: Special Body Size X : ２
Body Size Y : ４.２Body Size Z : 0.6
Lead Group N: ０
Lead Group S: ０
Lead Group E: ０
Lead Group W: 0 Algorithm :SPECIAL 8 Base Alignment :sp Quad
元件识别正反面
There are a number of special recognition algorithms available in the Special Rectangle Recognition mode.
1. Special ‘1’: Not supported (check of the average density among the objects)
2. Special ‘2’: Not supported (hole position check)
3. Special ‘3’: Direction judgment --- The direction is judged based on the luminance of a specified field (circle). Option 1: Recognition flag
Option 2: Minimum luminance difference (if 0, 50 will be set) The difference in the average concentrations of detection circles being
00—设定：0 01—设定：1 10—设定：２ 11—设定 3
checked in order to differentiate the directions must be larger than this value, or an error will occur.
The detection circle used to differentiate the directions is set for the Lead Group specified by bits 7, 5, and 4 of Option 1.
No. of Lead Groups: 1 (this is “2” if set to “Group 2”)
No. of leads: 0
Lead length: 0
LeadWidth: Diameter of detection circle (mm)
LeadPitch: 0
Lead reference position X: Detection circle center position X
Lead reference position Y: Detection circle center position Y
The returned result consists of the component tilt plus +90°, +180° or
+270° added based on the direction discrimination results.
The following is an example of a direction judgment. The results recognized using the
component data listed below are shown in the figure below.
The upper figure at the right shows the status in the definitions, and the lower figure at the right shows the recognition results when the component was rotated 180 degrees.
Remark:Option２：Yamaha在识别正反面时，是以相对称的两个位置的黑白光亮度差为依据的。

所以Option２的值光亮度之差。

Alignment Group: Special Alignment type: Special Body Size X : 4.97 Body Size Y : 5.31 Body Size Z : 2 Lead Group N: 1 Lead Group S: 0 Lead Group E: 0 Lead Group W: 0 Lead Number N1: 1 Lead Pitch N1: 0 Lead Width N1: 0.25 Reflectll N1: 0 Find Pos X N1: 1.5 Find Pos Y N1: 1.4 Lead Number S1: 0 Lead Pitch S1: 0 Lead Width S1: 0 Reflectll S1: 0
Find Pos X S1: 0
Find Pos Y S1: 0 Algorithm :SPECIAL 3 Base Alignment :Sp Quad Vision Option 1 :
Vision Option 2 : 30
2=010 识别上面点（北面）0°和90°方向，并且以识别黑色为判断依据
实际差值大于此值，识别ＯＫ，如果小于此值则判断为反面。

如果元件转180deg.手动识别将会判断ＯＫ，但实际运行时判断为ＮＧ，如果有特殊软件，设备将补偿180deg贴装。

YS 设备元件识别正反面
SAMPLE 1 SAMPLE 2
Alignment Group: Special Alignment type: Special Body Size X : 7
Body Size Y : 3.2
Body Size Z : 5
Lead Group N: 1
Lead Group S: 1
Lead Group E: 1
Lead Group W: 0
Lead Number N1: 1
Lead Pitch N1: 0
Lead Width N1: 1 Reflectll N1: 1
Find Pos X N1: -4.8
Find Pos Y N1:1.5
Lead Number S1: 1
Lead Pitch S1:
Lead Width S1:1
Reflectll S1: 1
Find Pos X S1: -4.8
Find Pos Y S1: 1
Lead Number E1: 1
Lead Pitch E1:
Lead Width E1:3
Reflectll E1: 7
Find Pos X E1:3.5
Find Pos Y E1: 0 Algorithm :SPECIAL 4 Base Alignment :Asmark Vision Option 4 : 0 VISION ANGLE: 90
Alignment Group: Special
Alignment type: Special
Body Size X : 5
Body Size Y : 4.5
Body Size Z : 5
Lead Group N: 1
Lead Group S: 1
Lead Group E: 1
Lead Group W: 0
Lead Number N1: 1
Lead Pitch N1: 0
Lead Width N1: 1
Reflectll N1: 1.5
Find Pos X N1: -3
Find Pos Y N1:2.3
Lead Number S1: 1
Lead Pitch S1:
Lead Width S1:1
Reflectll S1: 1.5
Find Pos X S1: -3
Find Pos Y S1: -2.3
Lead Number E1: 1
Lead Pitch E1:
Lead Width E1:4.5
Reflectll E1: 5.5
Find Pos X E1:3.8
Find Pos Y E1: 0
Algorithm :SPECIAL 4
Base Alignment :Asmark
Vision Option 4 : 0
VISION ANGLE: 90
SAMPLE1 SAMPLE2。