SUN Ying， FU Lu-hua， WANG Zhong
（State Key Laboratory of Precision Measuring Technology and Instruments，Tianjin University，Tianjin 300072，China）
Abstract： A ceramic ball is a basic part widely used in precision bearings. There is no perfect testing equipment for ceramic ball surface defects at present. A fast visual detection algorithm for ceramic ball surface defects based on fringe reflection is designed. By means of image preprocessing, grayscale value accumulative differential positioning, edge detection, pixel-value row difference and template matching, the algorithm can locate feature points and judge whether the spherical surface has defects by the number of points. Taking black silicon nitride ceramic balls with a diameter of 6.35 mm as an example, the defect detection time for a single gray scale image is 0.78 s, and the detection limit is 16.5 μm.
Key words： ceramic ball； surface defect； fringe reflection； visual detection algorithm
CLD number： TP391.41 doi： 10.3969/j.issn.1674-8042.2020.01.004
References
［1］Oliver J, Guerrero G, Goldman J. Ceramic bearings for electric motors. In: Proceedings of IEEE Cement Industry Conference, Toronto, Canada, 2015: 1-11．
［2］Wang Y, Hadfield M, Ring crack propagation in silicon nitride under rolling contact. Wear, 2001, 250(1-12): 282-292.
［3］Yang T B, Wang L Q, Gu L, et al. Processing defect analysis and nondestructive evaluation technology for Si3N4 bearing ball. Journal of China Ordnance, 2008, 4(3): 218-224.
［4］Wang X G, Ye Q, Guo Z P, et al. Two typical 3D CT system and application. Computerized Tomography Theory & Applications, 2009, 13(4): 26-33.
［5］Li Z G, Wu N S, Gu B K, et al. Penetrant inspection and automatic sorting system for ceramic bearing balls. Nondestructive Testing, 2003, 25(6): 296-301.
［6］Sun J G, Shirber M, Ellingson W A, et al. Laser-based optical scattering detection of surface and subsurface defects in machined Si3N4 components. In: Proceedings of the 21st Annual Conference on Composites, Advanced Ceramics, Materials, and Structures-B: Ceramic Engineering and Science, Cocoa Beach, US, 1997: 1113-1120.
［7］Petit S, Duquennoy M, Ouaftouh M, et al. Non-destructive testing of ceramic balls using high frequency ultrasonic resonance spectroscopy. Ultrasonics, 2005, 43(10): 802-810.
［8］Martínez S S, Vázquez C O, García J G, et al. Quality inspection of machined metal parts using an image fusion technique. Measurement, 2017, 111: 374-383.
［9］Nagashio M. Visual inspection system for ceramic balls. US Patent: 7889333, 2011-02-15.
［10］Zhang K, Fu L H, Wang Z, et al. Research on surface defect detection of ceramic ball based on fringe reflection. Optical Engineering, 2017, 56(10): 104104.
［11］Bothe T, Li W, Kopylow C V, et al. High-resolution 3d shape measurement on specular surfaces by fringe reflection. In: Proceedings of SPIE, Bellingham, USA, 2004, 5457: 411-422.
［12］Campos-García M, Morenooliva V I, DíazUribe R, et al. Improving fast aspheric convex surface tests with dynamic null screens using LCDs. Applied Optics, 2011, 50(19): 3101-3109.
［13］Canny J. A computational approach to edge-detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, PAMI-8(6): 679-698.
［14］Wang Z, Xing Q， Fu L H, et al. Realtime vision-based surface defect inspection of steel balls. Transactions of Tianjin University, 2015, 21(1): 76-82.
基于条纹反射的陶瓷球表面缺陷快速检测算法
孙 颖， 付鲁华， 王 仲
（天津大学 精密测试技术及仪器国家重点实验室， 天津 300072）
摘 要：陶瓷球是一种广泛应用于精密轴承的基础零件， 目前尚无成熟的陶瓷球表面缺陷检测设备。 为此设计了一种基于条纹反射的陶瓷球表面缺陷快速视觉检测算法。 该算法借助图像预处理、灰度累积差分定位、边缘检测、行间差分及模板匹配等方法来定位特征点， 然后根据其数量评判球面是否存在缺陷。 对直径6.35 mm的黑色氮化硅陶瓷球进行了检测， 单幅灰度图缺陷检测时间0.78秒， 检测极限为16.5 μm。
关键词： 陶瓷球； 面缺陷； 纹反射； 视觉检测算法
引用格式： SUN Ying， FU Lu-hua， WANG Zhong. A fast detection algorithm for ceramic ball surface defects based on fringe reflection. Journal of Measurement Science and Instrumentation, 2020, 11（1）： 28-37. ［doi： 10.3969／j.issn.1674-8042.2020.01.004］
[full text view]
