Application research of fault diagnosis expert system for photoelectric tracking device based on BP NN

Mingliang Hou; Yong Zhang; Feng Liu; Jian Zhang; Liyun Su

doi:10.1117/12.865714

22 October 2010 Application research of fault diagnosis expert system for photoelectric tracking device based on BP NN

Mingliang Hou, Yong Zhang, Feng Liu, Jian Zhang, Liyun Su

Proceedings Volume 7658, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology; 76584E (2010) https://doi.org/10.1117/12.865714
Event: 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies, 2010, Dalian, China

Abstract

In order to overcome the deficiencies of poor adaptive capacity, lack of inspiration and narrow domain knowledge of expert system and fundamentally improve the diagnostic efficiency, an intelligent fault diagnosis expert system for photoelectric tracking devices, based on BP neural network, is put forward. Firstly, in this paper, some key basic concepts and principles of intelligent fault diagnosis technology are proposed. Secondly, according to the difficulty of multiple and coupling fault diagnosis, after making a comparative analysis of the related BP neural network algorithms, such as the quasi-Newton method, the stretch BP method and the conjugate gradient method, a neural network fault diagnosis reasoning method based on the Levenberg-Marquardt is designed, which combined the implementation of the diagnosis expert system. Finally, several interrelated essential implementation issues, such as the architecture of the system and the VR technology based on OpenGL, are also discussed. Practical experiments and applications demonstrate that the proposed approach is effective, robust and universal.

Citation Download Citation

Mingliang Hou, Yong Zhang, Feng Liu, Jian Zhang, and Liyun Su "Application research of fault diagnosis expert system for photoelectric tracking device based on BP NN", Proc. SPIE 7658, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology, 76584E (22 October 2010); https://doi.org/10.1117/12.865714

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