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Smart Structures and Systems Volume 6, Number 4, May 2010 , pages 389-403 DOI: https://doi.org/10.12989/sss.2010.6.4.389 |
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Image recognition technology in rotating machinery fault diagnosis based on artificial immune |
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Zhu Dachang, Feng Yanping, Chen Qi ang and Cai Jinbao
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| Abstract | ||
| By using image recognition technology, this paper presents a new fault diagnosis method for rotating machinery with artificial immune algorithm. This method focuses on the vibration state parameter image. The main contribution of this paper is as follows: firstly, 3-D spectrum is created with raw vibrating signals. Secondly, feature information in the state parameter image of rotating machinery is extracted by using Wavelet Packet transformation. Finally, artificial immune algorithm is adopted to diagnose rotating machinery fault. On the modeling of 600MW turbine experimental bench, rotor normal rate, fault of unbalance, misalignment and bearing pedestal looseness are being examined. It demonstrated from the diagnosis example of rotating machinery that the proposed method can improve the accuracy rate and diagnosis system robust quality effectively. | ||
| Key Words | ||
| rotating machinery; fault diagnosis; image recognition technology; artificial immune algorithm. | ||
| Address | ||
| Zhu Dachang, Feng Yanping and Chen Qiang: College of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Ganzhou, P.R. China Cai Jinbao: Faculty of Foreign Studies, Jiangxi University of Science and Technology, Ganzhou, P.R. China | ||