High dynamic online detection method for surface defects of small diameter reflective inner wall

被引:0
|
作者
Yuan, Shuaipeng [1 ]
Yan, Ning [1 ]
Zhu, Linlin [3 ]
Hu, Jianghong [2 ]
Li, Zexiao [1 ]
Liu, Haoyue [1 ]
Zhang, Xiaodong [1 ]
机构
[1] State Key Laboratory of Precision Measuring Technology and Instruments, Laboratory of Micro/Nano Manufacturing Technology (MNMT), Tianjin University, Tianjin,300072, China
[2] Fitow (Tianjin) Detection Technology Company Limited, Tianjin,300457, China
[3] Standard Optics Technology Tianjin (SOPT) Company Limited, Tianjin,300457, China
关键词
Inspection - Light reflection - Bearings (machine parts) - Image processing;
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中图分类号
学科分类号
摘要
Small diameter inner wall surface reflective linear bearing sleeve, in the manufacturing, transportation, and other processes. The inner wall surface will inevitably produce minor height difference surface defects, resulting in gaps or wear problems in the use of products, affecting the overall life of the equipment and even causing a significant security risk. However, auto-detection is challenging to achieve because of the small space during the inspection and comprehensive inspection requirements. At the same time, it is required to have high accuracy and fast efficiency during the inspection, etc., to avoid causing the increase of the industrial production cycle and limit the yield. Based on the physical characteristics of the light reflection on the inner wall surface of such parts, this paper proposes a high-dynamic online detection method for small-diameter internal wall surface defects. The reflective fringes are used to enhance and magnify the minor surface defects of the inner wall, and the new spiral fringes are derived by modelling and simulation. The practical reflection of the characteristics of micron defects on the reflective inner wall is realized through the establishment of a mechanical inspection environment, and the use of image processing technology, online rapid and comprehensive detection of micron defects is achieved. Application and production in the actual industrial environment are realized, and the online high precision detection of defects of φ22mm is realized. Experiments prove that the method can detect bulges with only a height of 5 μm, and the detection accuracy rate can reach 99.31%. © 2022
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