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Proceedings Paper

Fault detection and analysis of electric generator based on wavelet transform and fuzzy logic technology
Author(s): Guangbin Ding; Peilin Pang
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Paper Abstract

A new method combining wavelet transform with fuzzy theory is proposed to improve the limitation of traditional fault diagnosis technology of electric generator. In order to determine the threshold of each order of wavelet space and the decomposition level adaptively, the statistic rule is brought forward to increase the signal-noise-ratio. The wavelet transform is used to acquire the effective feature components and the proposed fuzzy diagnosis equation is used to complete classify fault pattern. The fault diagnosis model of electric generator is established and the network parameters training are fulfilled by the improved least squares algorithm. The input nodes include the information representing the fault characters. On basis of experiments data to train the fault diagnosis mode, the accurate classification results can be achieved in accordance with expert experience. In view of actual applications, the proposed method can effectively diagnose the fault pattern of electric generator.

Paper Details

Date Published: 13 October 2008
PDF: 4 pages
Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 71280E (13 October 2008); doi: 10.1117/12.806450
Show Author Affiliations
Guangbin Ding, Hebei Univ. of Engineering (China)
Peilin Pang, Hebei Univ. of Engineering (China)


Published in SPIE Proceedings Vol. 7128:
Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment

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