Dr. Fei Gao Profile

Dr. Fei Gao

at Xi’an Jiaotong Univ.

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Proceedings Article | 7 March 2019 Paper

Online vision system for battery FPC connector defect detection based on active shape model template matching

Zhuo Zhao, Bing Li, Fei Gao, Lei Chen, Meiting Xin

Proceedings Volume 11053, 110530Z (2019) https://doi.org/10.1117/12.2511378

KEYWORDS: Connectors, Defect detection, Visual process modeling, Detection and tracking algorithms, Image segmentation, Machine vision, Principal component analysis, Image filtering

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In this paper, a quality detection method for battery FPC (Flexible Printed Circuit) connectors based on active shape model template matching is proposed. It can deal with different kinds of connector appearance defects. Firstly, construct template data set of connector, acquire test images and apply cutting operation to original image, then execute tilt correction and image reconstruction by means of least square method and affine transformation to fulfil the pre-processing stage. Then, match and locate connector region in per-processing image with the help of the active shape model (ASM) based template matching method. To deal with different kinds of defect (soldering offset/tilt, exposed copper clad layer in FPC, broken edge in FPC, defects in center area of connector, defects on metal and plastic components), independent detection algorithm units are integrated in the system. Template can also be real-timely updated according to detection result. Finally, the defects will be classified, located and marked in detection image. In addition, aimed at the need of battery industry, a set of detection system with low cost, high performance and strong stability has been designed. It can be concluded from online and offline experiments that the proposed method is of high detection rate, good real-time performance and strong robustness.

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