WO2021169335A1 - 一种锂电池极耳激光焊点视觉在线检测方法 - Google Patents
一种锂电池极耳激光焊点视觉在线检测方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30152—Solder
Definitions
- the invention relates to the field of laser solder joint detection in a lithium battery automatic packaging process, and in particular to a visual online detection method for laser solder joints of lithium battery tabs.
- the defect detection of the solder joints of the pole ears of lithium battery cells and the PCM plate pole ears adopts traditional visual inspection algorithms.
- the main algorithms are: shape template matching, spot analysis, contour matching, etc.; preprocessing algorithms usually include: grayscale linear transformation, Corrosion, expansion, etc.
- the traditional visual inspection method cannot effectively solve the inspection problem caused by the folds of the lithium battery tabs
- manual visual inspection of the solder joints of the lithium battery is still widely used.
- the manual visual inspection method has disadvantages such as low efficiency and unstable effect. Therefore, it is very important to propose an effective visual solder joint inspection method for the deterioration of image quality caused by the wrinkle and bending of the lithium battery tabs.
- the purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for visual online detection of the laser solder joints of the tabs of the lithium battery.
- the invention overcomes the problem that the traditional detection method is difficult to detect the wrinkle lug solder joints, and at the same time meets the requirements of detection accuracy and online detection.
- the invention selects a specific detection algorithm according to the contrast of the tab image, and reduces the detection ROI area according to the positioning relationship.
- a visual on-line detection method for laser solder joints of lithium battery tabs including the steps:
- PCM circuit protection module
- solder joint detection in a square ROI. If a solder joint is detected, the estimated solder joint coordinates will be compensated to obtain the actual solder joint coordinates in the image of the electrode ear of the battery.
- two sets of dome light sources and the black and white industrial camera module are used to perform a global image of the cell tab and the PCM plate tab of the lithium battery. collection.
- the light source adopts blue light illumination; two industrial cameras are installed opposite to each other, and the lithium battery is located between the two industrial cameras during image collection; the two cameras separately collect the global image of the PCM plate tab and the global image of the battery cell tab; the tab The global image covers the left and right two pole ears; the two industrial camera modules (camera and lens) are exactly the same, and the overlapping area of the field of view needs to completely cover the left and right pole ears; the imaging effect that should be achieved by combining the camera exposure time and the light intensity of the light source is Make the gray value of the normal non-wrinkle tab in the image 255.
- the cell tab global image is divided into a cell left tab local image and a cell right tab local image;
- PCM The global image of the pole ear is divided into a partial image of the left pole of the PCM board and a partial image of the right pole of the PCM board.
- Each partial image of the tab is required to completely contain the contour of the tab, and the partial image of the tab should cover all the positions of the tab of the lithium battery in the global image that may appear due to the lithium battery clamping error.
- the step of judging the contrast of the obtained partial image of the tabs of the lithium battery includes:
- the gray level of the background area far from the light source irradiated by the lithium battery is in the low gray value range, and the range is about 0 to 20;
- the gray scale of the overall lug shadow caused by the shadow or the bending and tilt of the lug is in the middle gray value range, and the range is about 30 to 80; there is no wrinkle in the local image of the lug, and the grayscale of the non-welded area of the normal lug is in a high grayscale.
- Value range the range is approximately 200 to 255;
- ⁇ is greater than or equal to the preset constant const, the partial image of the polar ear is judged as normal contrast, otherwise it is low contrast; the constant const is calculated by comparing the sum of the number of pixels in the high gray value interval of a normal polar ear image with no wrinkles and medium gray The quotient of the sum of the number of pixels in the degree value interval is used as a reference, and the average value can be continuously accumulated in real-time operation to reduce the error.
- the tab ROI extracted from the partial image of the tab needs to meet: the left edge of the ROI coincides with the left edge of the contour of the tab , The right edge of the ROI coincides with the right edge of the ear contour, and the lower edge of the ROI coincides with the lower edge of the ear contour.
- the step of extracting the lug ROI from the local image of the lug by adopting a corresponding method according to the determined contrast result includes:
- the OTSU algorithm is used for thresholding, and the method of finding the smallest circumscribed rectangle is adopted in the binary image.
- the rectangle with the largest area among all circumscribed rectangles is the pole ear ROI;
- the cumulative gray pixel number approximation method is used for thresholding, and the method of finding the smallest circumscribed rectangle is adopted in the binary image.
- the rectangle with the largest area among all circumscribed rectangles is the lug ROI;
- the resulting tab ROI is the tab image.
- the thresholding is performed using the cumulative gray-scale pixel approximation method, specifically as follows: under normal circumstances, the polar ear has a 255 gray value in the image, and the sum of its pixels floats around an average value T, and the local image pixels of the polar ear The length is l, and the number of pixels corresponding to each gray value in the low-contrast polar ear partial image is N i , where i represents the gray value, N represents the number of pixels, and S represents the pixels that are accumulated from 255 gray levels and decremented by 1 Sum, stop the accumulation when S is greater than T for the first time and get the gray value n.
- the thresholding operation is performed with t as the parameter.
- the parameter T is obtained by pre-calculating the number of 255 gray pixels of the normal image of the non-wrinkled battery cell tab and the normal image of the non-wrinkled PCM tab, and can be continuously accumulated and averaged to update T during real-time operation.
- the partial image of the PCM lug with normal contrast is extracted to obtain the PCM lug image with the normal contrast and the low-contrast PCM lug image.
- a low-contrast PCM pole ear image is obtained.
- spot analysis or Hough circle transformation method is used to detect solder joints.
- the solder joint detection step includes:
- the Log-Gabor even filter is used for filtering processing, and the Hough circle transform is used to detect the circle after processing;
- the step of accumulating the circle results detected by the Hough circle transformation after each Log-Gabor even filtering and performing the filtering operation includes:
- All the circles retained in the previous step are arranged from small to large according to the center y coordinate. If the distance between the y coordinates of two adjacent circles is less than ⁇ y , then the y coordinates of the two circles are considered to be the same;
- All the circles retained in the previous step are arranged according to the center x coordinate from small to large. If the distance between the x coordinates of two adjacent circles is less than ⁇ x , then the x coordinates of the two circles are considered to be the same;
- the step of mapping and predicting the welding point coordinates in the cell tab image by detecting the welding point coordinates in the PCM tab image and the calibration information obtained in advance, compare the right tab image of the PCM and the battery core.
- the welding point coordinates of the left pole ear image are transformed, and the transformation formula is as follows:
- ⁇ BL ⁇ is the image coordinate system of the left ear of the battery
- ⁇ FR ⁇ is the image coordinate system of the right ear of the PCM
- the origin of the coordinate system is the upper left corner of the image
- the right is the positive x direction
- the downward is the positive y direction.
- P ij represents the coordinate vector of the welding point, where i represents the row, j represents the column, the PCM right pole ear image length w 1 , height h 1 , the battery cell left pole ear image length w 1 ', height h 1 ', a, a' , B, b′ are the pre-calibration information read from the txt file, a is the pixel length of the P-calibration distance from the left edge of the image in the PCM right polar ear image, and b is the bottom of the P-calibration distance image in the PCM right polar ear image
- the pixel length of the edge, a′ is the pixel length of the left pole ear image of the battery corresponding to the solder point P calibration ′ from the right edge of the image, b′ is the pixel length of the left pole ear image of the battery corresponding to the solder point P calibration ′ from the bottom edge of the image .
- ⁇ BR ⁇ is the image coordinate system of the right ear of the battery
- ⁇ FL ⁇ is the image coordinate system of the left ear of the PCM
- the origin of the coordinate system is the upper left corner of the image
- the right is the positive x direction
- the downward is the positive y direction.
- P mn represents the coordinate vector of the solder joints, where m represents the row, n represents the column, PCM left pole ear image length w 2 , height h 2 , battery cell right pole ear image length w 2 ', height h 2 ', c, c′ , D, d′ are the pre-calibration information read from the txt file, c is the pixel length of the solder joint P calibration distance from the right edge of the image in the PCM left polar ear image, and d is the P calibration distance image bottom in the PCM left polar ear image The pixel length of the edge, c′ is the pixel length of the right pole ear image of the battery corresponding to the solder point P calibration ′ from the left edge of the image, and d′ is the pixel length of the right pole ear image of the battery corresponding to the solder point P calibration ′ from the bottom edge of the image .
- the pre-calibration information is obtained in advance through an additional program, specifically:
- the right pole ear image of the PCM and the left pole ear image of the battery are obtained;
- the acquisition of pre-calibration information is obtained in advance through an additional program, specifically:
- the right pole ear image of the PCM and the left pole ear image of the battery are obtained;
- the pre-calibration information read from the txt file can only use a, b, a', b'or only use c, d, c', d'; when only a, b, a', b'are used, use replace use replace When using only c, d, c′, d′, use replace use replace And in real-time operation, it is possible to repeatedly record a, b, a', b', c, d, c', d'for accumulating average values, thereby reducing errors.
- the method of spot analysis is used to search for the solder joints on the square ROI. If the spot analysis fails to find the solder joints Point, the histogram equalization process is performed on the image, and the Hough circle detection is used to search for solder joints. According to the search results in the square ROI, the formula for compensating the coordinates of the pole ear solder joints of the mapped battery is as follows (the origin of the image coordinate system is in the upper left corner):
- J is the actual welding point coordinates in the pole ear image coordinate system of the battery
- (x temp , y temp ) is the coordinates of the welding point in the square ROI image coordinate system ⁇ Square ⁇
- l is the length of the square ROI. If detected For multiple circles, only the one closest to the center of the rectangle is used.
- the ROI side length l is a preset parameter, which is related to the installation position of the image acquisition mechanism and the model selection, l is about 2 times the diameter of the solder joint and the pixel length
- the present invention has the following beneficial effects:
- the present invention improves the problem of misjudgment of unqualified products caused by traditional algorithms in the detection of wrinkled ear images.
- the present invention meets the real-time requirements of actual automated production.
- Figure 1 is a flow chart of a visual online inspection method for laser solder joints of lithium battery tabs
- Fig. 2 is a flow chart of judging the contrast of the partial pole ear image in an embodiment of the present invention
- Fig. 3 is a flowchart of low-contrast PCM tab image processing in an embodiment of the present invention.
- Fig. 4 is a schematic diagram of obtaining calibration information in the step of mapping the solder joint coordinates of the PCM tab image from the solder joint coordinates of the PCM tab image in the embodiment of the present invention
- Fig. 5 is a schematic structural diagram of a visual online inspection system for laser solder joints of lithium battery tabs in an embodiment of the present invention.
- a visual online inspection system for laser solder joints of lithium battery tabs is provided, and the structure of the system is shown in FIG. 5.
- the lithium battery 113 is transported to the visual inspection station by the feeding mechanism 112, and the lithium battery is fixed and held by the clamp 114.
- the visual inspection station has dome light sources 106 and 108, industrial cameras 107 and 110, and light source control After the lithium battery 113 is placed, the visual inspection method of the present invention starts to work.
- Figure 1 shows a flow chart of a visual online inspection method for laser solder joints of lithium battery tabs, which includes the following steps:
- PCM circuit protection module
- two sets of dome light sources 106, 108 and industrial cameras 107, 110 are used for acquisition.
- the global image of the PCM tab and the global image of the battery cell tab with a size of 2592*1944 are obtained.
- the tabs without wrinkles are highlighted in the image.
- the tabs with wrinkles have most of the shadows.
- the battery cell pole ear global image is divided into a cell left pole ear local image and a cell right pole ear local image;
- the PCM pole ear global image is divided into a PCM board left pole ear local image and a PCM board right pole ear local image .
- set the partial image of the left pole ear as a starting point (0,450), a rectangular area with a length of 800, and a width of 600 in the global image
- set the partial image of the right pole ear as a starting point (1700,600), a length of 800, and a width of 600. 600 rectangular area.
- the resulting PCM left pole ear partial image, PCM right pole ear partial image, battery core left pole ear partial image, and battery core right pole ear partial image are all in the partial image.
- Figure 2 shows the flow chart of the contrast of the partial image of the tabs of the lithium battery obtained by judging, including the steps:
- (3-1) Divide the gray histogram statistical results of the partial image of the extreme ears into 3 intervals: low gray value interval, medium gray value interval, and high gray value interval;
- the gray level of the background area far from the light source irradiated by the lithium battery is in the low gray value range, and the range is about 0 to 20;
- the gray scale of the overall lug shadow caused by the shadow or the bending and tilt of the lug is in the middle gray value range, and the range is about 30 to 80; there is no wrinkle in the local image of the lug, and the grayscale of the non-welded area of the normal lug is in a high grayscale.
- Value range the range is approximately 200 to 255;
- ⁇ is greater than or equal to the preset constant const, the partial image of the polar ear is judged as normal contrast, otherwise it is low contrast; the constant const is calculated by comparing the sum of the number of pixels in the high gray value interval of a normal polar ear image with no wrinkles and medium gray The quotient of the sum of the number of pixels in the degree value interval is used as a reference, and the average value can be continuously accumulated in real-time operation to reduce the error.
- the constant const is 3, and the grayscale histogram of the partial image of the left polar ear of the PCM is counted.
- the sum of the number of pixels in the highlight gray value interval is 10 times the sum of the number of pixels in the middle gray value interval, and it is judged as normal Contrast polar ear image.
- the sum of the number of pixels in the PCM right polar ear partial image is 1.5 times the sum of the number of pixels in the middle gray value range. It is judged as low contrast; similarly, the left electrode of the battery is judged as low. Contrast, the right pole ear of the battery is judged as normal contrast.
- the ROI of the pole ear extracted from the local image of the pole meets: the left edge of the ROI coincides with the left edge of the outline of the pole, the right edge of the ROI coincides with the right edge of the outline of the pole, and the lower edge of the ROI coincides with the lower edge of the outline of the pole.
- different threshold parameters are used to perform threshold image segmentation to extract the polar ear ROI; the PCM left polar ear partial image is of normal contrast, so the OTSU threshold is used for binarization, and the largest connected area in the binarized image is extracted
- the smallest circumscribed rectangle of the domain obtains the PCM left polar ear image; the PCM right polar ear image is of low contrast, and the number of pixels is accumulated from the gray value of 255. When the accumulated sum reaches 85000, the accumulation stops. At this time, the gray The degree is 35, so the binarization operation is performed on the partial image of the PCM right pole ear with a threshold of 35.
- the circumscribed rectangle with the largest area is extracted from the binary image to obtain the PCM right pole ear image; similarly, the left pole ear of the battery is obtained.
- Image image of the right pole ear of the battery cell.
- ⁇ 0 is the center wavelength of 45
- ⁇ ( ⁇ x , ⁇ y ) T
- ⁇ 0 is the parameter that determines the bandwidth.
- ⁇ BL ⁇ is the image coordinate system of the left ear of the battery
- ⁇ FR ⁇ is the image coordinate system of the right ear of the PCM
- the origin of the coordinate system is the upper left corner of the image
- the right is the positive x direction
- the downward is the positive y direction.
- P ij represents the coordinate vector of the welding point, where i represents the row, j represents the column, the PCM right pole ear image length w 1 , height h 1 , the battery cell left pole ear image length w 1 ', height h 1 ', a, a' , B, b′ are the pre-calibration information read from the txt file, a is the pixel length of the P-calibration distance from the left edge of the image in the PCM right polar ear image, and b is the bottom of the P-calibration distance image in the PCM right polar ear image
- the pixel length of the edge, a′ is the pixel length of the left pole ear image of the battery corresponding to the solder point P calibration ′ from the right edge of the image, b′ is the pixel length of the left pole ear image of the battery corresponding to the solder point P calibration ′ from the bottom edge of the image .
- ⁇ BR ⁇ is the image coordinate system of the right ear of the battery
- ⁇ FL ⁇ is the image coordinate system of the left ear of the PCM
- the origin of the coordinate system is the upper left corner of the image
- the right is the positive x direction
- the downward is the positive y direction.
- P mn represents the coordinate vector of the solder joints, where m represents the row, n represents the column, PCM left pole ear image length w 2 , height h 2 , battery cell right pole ear image length w 2 ', height h 2 ', c, c′ , D, d′ are the pre-calibration information read from the txt file, c is the pixel length of the solder joint P calibration distance from the right edge of the image in the PCM left polar ear image, and d is the P calibration distance image bottom in the PCM left polar ear image The pixel length of the edge, c′ is the pixel length of the right pole ear image of the battery corresponding to the solder point P calibration ′ from the left edge of the image, and d′ is the pixel length of the right pole ear image of the battery corresponding to the solder point P calibration ′ from the bottom edge of the image .
- the pre-calibration information is obtained in advance through an additional program, specifically:
- the side length of the square ROI is 20 pixels.
- the spot analysis method is used to search for the solder joints in the square ROI. If the spot analysis fails to search for the solder joints, the histogram equalization process is performed on the image, and then the Hough circle is used to detect the solder joints. point.
- the formula for compensating the coordinates of the pole ear solder joints of the mapped battery is as follows (the origin of the image coordinate system is in the upper left corner):
- J is the actual solder joint coordinates in the pole ear image coordinate system of the battery
- (x temp , y temp ) is the solder joint coordinates in the square ROI image coordinate system ⁇ Square ⁇
- l is 20. If multiple circles are detected Just use the one closest to the center of the rectangle.
- solder joint inspection of all PCM tab images and battery cell tab images has been completed, and the solder joints of the lithium battery 113 are marked as good or defective according to the test results. If it is a good product, the unloading mechanism 109 transports the lithium battery 113 to the good product unloading conveyor belt 103;
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Abstract
Description
Claims (10)
- 一种锂电池极耳激光焊点视觉在线检测方法,其特征在于,包括步骤:采集PCM极耳全局图像与电芯极耳全局图像;对PCM板极耳全局图像和电芯极耳全局图像进行划分,得到锂电池极耳局部图像;对得到的锂电池极耳局部图像的对比度进行判断;依据判断的对比度结果采取相应方法从极耳局部图像中提取极耳ROI,得到PCM极耳图像和电芯极耳图像;依据判断的对比度采取相应方法进行PCM极耳图像的焊点检测;通过检测的PCM极耳图像中的焊点坐标和预先获取的标定信息,映射预估电芯极耳图像中的焊点坐标;在电芯极耳图像中,以得到的每一个映射预估焊点坐标为中心生成一个正方形ROI;在正方形ROI中进行焊点检测,如果检测到焊点就对预估的焊点坐标进行补偿,得到实际的电芯极耳图像中的焊点坐标。
- 根据权利要求1所述的方法,其特征在于,所述采集PCM极耳全局图像与电芯极耳全局图像的步骤中,采用2组圆顶光源和黑白工业相机模组对锂电池的电芯极耳与PCM板极耳进行全局图像采集;所述光源采用蓝光照明;两个工业相机对置安装,图像采集时锂电池位于两个工业相机中间;两个相机分别采集PCM极耳全局图像和电芯极耳全局图像;所述极耳全局图像涵盖左、右2个极耳;两个工业相机模组完全相同,视场重合区域需要完全覆盖左右极耳;综合相机曝光时间和光源光强应该达到的成像效果是使得正常无褶皱极耳在图像中的灰度值为255。
- 根据权利要求1所述的方法,其特征在于,所述对PCM板极耳全局图像和电芯极耳全局图像进行划分的步骤中,电芯极耳全局图像划分为电芯左极耳局部图像和电芯右极耳局部图像;PCM极耳全局图像划分为 PCM板左极耳局部图像和PCM板右极耳局部图像;每个极耳局部图像均要求完整地包含该极耳轮廓,且极耳局部图像应该涵盖全局图像中锂电池极耳因为锂电池装夹误差导致可能出现的所有位置。
- 根据权利要求1所述的方法,其特征在于,所述对得到的锂电池极耳局部图像的对比度进行判断的步骤中,包括:将极耳局部图像的灰度直方图统计结果划分为3区间:低灰度值区间、中等灰度值区间、高灰度值区间;通过高灰度值区间像素和S h与中等灰度值区间像素和S m的比值δ,判断极耳局部图像的对比度:如果δ大于等于预设的常数const,则将极耳局部图像判断为正常对比度,否则为低对比度;其中常数const通过对一个无褶皱正常极耳图像的高灰度值区间像素数总和与中等灰度值区间像素数总和的商做参照,并且可以在实时运行中不断累计求平均值来减小误差。
- 根据权利要求1所述的方法,其特征在于,所述依据判断的对比度结果采取相应方法从极耳局部图像中提取极耳ROI的步骤中,从极耳局部图像提取的极耳ROI需要满足:ROI左边缘与极耳轮廓左边缘重合,ROI右边缘与极耳轮廓右边缘重合,ROI下边缘与极耳轮廓下边缘重合。
- 根据权利要求1所述的方法,其特征在于,所述依据判断的对比度结果采取相应方法从极耳局部图像中提取极耳ROI的步骤中,包括:对于正常对比度的极耳局部图像,采用OTSU算法进行阈值化,并在二值图像中采用寻找最小外接矩形法,所有外接矩形中面积最大的矩形就是极耳ROI;对于低对比度的极耳局部图像,采用累加灰度像素数逼近法进行阈值化,并在二值图像中采用寻找最小外接矩形法,所有外接矩形中面积最大的矩形就是极耳ROI;得到的极耳ROI即为极耳图像;采用累加灰度像素逼近法进行阈值化,阈值t求解公式为:其中,正常情况下极耳在图像中是255灰度值,其像素总和在一个平均值T附近浮动,l为极耳局部图像像素长度,N i为低对比度极耳局部图像中每个灰度值对应的像素数量,i表示灰度值;S表示从255灰度开始按照递减1进行累加的像素和,n表示当累加到S第一次大于T时得到的灰度值。
- 根据权利要求1所述的方法,其特征在于,所述依据判断的对比度采取相应方法进行PCM极耳图像的焊点检测的步骤中,对于低对比度的PCM极耳图像,焊点检测步骤包括:对PCM极耳图像进行直方图均衡化处理;采用Log-Gabor even滤波器进行滤波处理,处理后进行霍夫圆变换检测圆;改变Log-Gabor even滤波器的参数σ 0,重复滤波处理和检测圆若干次;将每一次Log-Gabor even滤波后进行霍夫圆变换检测到的圆结果,累计在一起进行筛选操作,最后保留真正的焊点。
- 根据权利要求7所述的方法,其特征在于,所述将每一次Log-Gabor even滤波后进行霍夫圆变换检测到的圆结果,累计在一起进行筛选操作的步骤中,包括:从第一个圆开始循环遍历,合并圆心坐标距离小于ε的圆,新圆的圆心坐标为所合并圆的圆心坐标的平均值,并标记合并圆的数量;对所有圆按照圆心x坐标从小到大进行排列,如果相邻两个圆x坐标 距离小于ε x,那么认为这两个圆x坐标是同一的;统计同一x坐标下所有合并圆的数目和,如果和大于等于C x,保留该x坐标下的所有圆,反之则删去;对上一步保留的所有圆按照圆心y坐标从小到大进行排列,如果相邻两个圆y坐标距离小于ε y,那么认为这两个圆y坐标是同一的;统计同一y坐标下所有合并圆的数目和,如果和大于等于C y,保留该y坐标下的所有圆,反之则删去;对上一步保留的所有圆按照圆心x坐标从小到大进行排列,如果相邻两个圆x坐标距离小于ε x,那么认为这两个圆x坐标是同一的;统计同一x坐标下所有合并圆的数目和,如果这个和大于等于C x′那么就保留该x坐标下的所有圆,反之则删去;其中C x′>C x。
- 根据权利要求1所述的方法,其特征在于,所述通过检测的PCM极耳图像中的焊点坐标和预先获取的标定信息,映射预估电芯极耳图像中的焊点坐标的步骤中,对PCM右极耳图像和电芯左极耳图像的焊点坐标进行变换,变换公式如下:其中,{BL}为电芯左极耳图像坐标系,{FR}为PCM右极耳图像坐标系,坐标系原点均为图像左上角,向右为x正方向,向下为y正方向,P ij表示焊点坐标向量,其中i表示行、j表示列,PCM右极耳图像长w 1,高h 1,电芯左极耳图像长w 1’,高h 1’,a、a′、b、b′是从txt文档中读取的预先标定信息,a为PCM右极耳图像中焊点P 标定距离图像左边缘的像素长度,b是PCM右极耳图像中P 标定距离图像底边缘的像素长度,a′为电芯左极耳图像对应焊点P 标定′距离图像右边缘的像素长度,b′为电芯左极耳图像对应 焊点P 标定′距离图像底边缘的像素长度;对PCM左极耳图像和电芯右极耳图像的焊点坐标进行变换,变换公式如下:其中,{BR}为电芯右极耳图像坐标系,{FL}为PCM左极耳图像坐标系,坐标系原点均为图像左上角,向右为x正方向,向下为y正方向,P mn表示焊点坐标向量,其中m表示行,n表示列,PCM左极耳图像长w 2、高h 2、电芯右极耳图像长w 2’、高h 2’,c、c′、d、d′是从txt文档中读取的预先标定信息,c为PCM左极耳图像中焊点P 标定距离图像右边缘的像素长度,d是PCM左极耳图像中P 标定距离图像底边缘的像素长度,c′为电芯右极耳图像对应焊点P 标定′距离图像左边缘的像素长度,d′为电芯右极耳图像对应焊点P 标定′距离图像底边缘的像素长度;在对PCM右极耳图像和电芯左极耳图像的焊点坐标进行变换的过程中,预先标定信息的获取是通过额外的程序事先得到的,具体为:输入正常无褶皱极耳的PCM板极耳全局图像和电芯极耳全局图像;通过对比度判断及ROI提取,得到PCM右极耳图像和电芯左极耳图像;在PCM右极耳图像中指定一个焊点的位置( FRx, FRy),求解a,b,计算公式为:在电芯左极耳图像中指定与PCM右极耳图像对应焊点的位置( BLx, BLy),求解a′,b′,计算公式为:将a、b、a′、b′的值保存在xml或txt文件中;在对PCM左极耳图像和电芯右极耳图像的焊点坐标进行变换的过程中,预先标定信息的获取是通过额外的程序事先得到的,具体为:输入正常无褶皱极耳的PCM板极耳全局图像和电芯极耳全局图像;通过对比度判断及ROI提取,得到PCM右极耳图像和电芯左极耳图像;在PCM左极耳图像中指定一个焊点的位置( FLx, FLy),求解c,d,计算公式为:在电芯右极耳图像中指定与PCM左极耳图像对应焊点的位置( BRx, BRy),求解c′,d′,计算公式为:将c、d、c′、d′的值保存在xml或txt文件中。
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