[3] [3] Wen S, Chen Z, Li C. Vision-based surface inspection system for bearing rollers using convolutional neural networks [J]. Applied Sciences, 2018, 8（12）：1-19.

[7] [7] Luo N, Wang S, Liu G. Indication analysis of magnetic particle testing on PH13-8Mo precipitation hardening stainless steel [J]. IOP Conference Series Earth and Environmental Science, 2021, 772（1）：012060.

[8] [8] Javier Garca-Martn, Jaime Gmez-Gil, Ernesto Vzquez-Snchez. Non-destructive techniques based on eddycurrent testing [J]. Sensors, 2011, 11（3）：2525-2565.

[9] [9] Efremov A, Karpenko O, Udpa L. Generalized multifrequency fusion algorithm for defect detection in eddy current inspection data [J]. NDT & E International：Independent Nondestructive Testing and Evaluation, 2022（129）：129.

[10] [10] Liu Y, Guo L, Gao H, et al. Machine vision based condition monitoring and fault diagnosis of machine tools using information from machined surface texture：A review [J]. Mechanical Systems and Signal Processing, 2022, 164（11）：108068.

[11] [11] Chang C L, Chen H W, Chen Y H, et al. Drip-tape-following approach based on machine vision for a two-wheeled robot trailer in strip farming [J]. Agriculture, 2022, 12（3）：1-18.

[12] [12] Pelletier M G, Holt G A, Wanjura J D. Cotton gin stand machine-vision inspection and removal system for plastic contamination：Software design [J]. AgriEngineering, 2021, 3（3）：494-518.

[13] [13] Lou W, Cao P, Zhang D H, et al. Optical element surface defect size recognition based on decision regression tree [J]. Applied Sciences-Basel, 2020, 10（18）：1-14.

[14] [14] Wang F, Yang Y, Lou W. Fast path planning algorithm for large-aperture aspheric optical elements based on minimum object depth and a self-optimized overlap coefficient [J]. Applied optics, 2022, 61（11）：3123-3133.

[15] [15] Pichate K and Pitikhate S. A practical low-cost machine vision sensor system for defect classification on air bearing surfaces [J], Sensors and Materials, 2017, 29（6）：629-644.

[16] [16] Liu B Y, Wang Y Q, Bai S S, et al. An automatic system for bearing surface tiny defect detection based on multi-angle illuminations [J]. Optik, 2020, 208（17）：1-5.

[17] [17] Choudhary A, Goyal D, Letha S S. Infrared thermography-based fault diagnosis of induction motor bearings using machine learning [J]. IEEE Sensors Journal, 2020, 21（1）：1727-1734.