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31 December 2010 Detection algorithm for dimensional measurement and damage defect recognition of piston rings
Tao He, Qinghua Wu, Zhen Zeng
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Proceedings Volume 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation; 754439 (2010) https://doi.org/10.1117/12.885430
Event: Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 2010, Hangzhou, China
Abstract
Due to high speed requirement of real-time online inspection, and disturbances in industrial scene such as illumination and vibration, the captured image of piston ring by CCD is not very distinct, interfering following image procedures greatly. Therefore, in this paper, two models of dimensional measurement and damage defect recognition for piston rings are both established and wavelet transform is added in the process to analysis the edge image to ensure the precision and accuracy of detection results. A series of detection algorithms are elaborated in detail. The first step in the algorithms is to make image-preprocess to original images of piston rings by extracting interested area, image-filtering, and image erosion, with the aim of obtaining precise edge of piston rings' images for defect recognition. In the next step, wavelet transform method is used to calculate accurate edge of piston rings, thus dimension parameters of piston rings could be calculated after calibration of pixel. Then the least squares method is applied to fit a relative datum curve of the edge of piston rings. Based on defect recognition algorithm model and the procedures above, the detection algorithm can distinguish the upper and lower surface of piston rings, recognize piston rings' breakages and justify whether piston rings are conforming or not. The application of detection algorithm has been used to actualize non-contact automatic online inspection system.
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Tao He, Qinghua Wu, and Zhen Zeng "Detection algorithm for dimensional measurement and damage defect recognition of piston rings", Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 754439 (31 December 2010); https://doi.org/10.1117/12.885430
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KEYWORDS
Detection and tracking algorithms
Image processing
Inspection
Wavelet transforms
Wavelets
Image analysis
Machine vision
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