Paper
13 October 2008 Fault detection and analysis of electric generator based on wavelet transform and fuzzy logic technology
Guangbin Ding, Peilin Pang
Author Affiliations +
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guangbin Ding and Peilin Pang "Fault detection and analysis of electric generator based on wavelet transform and fuzzy logic technology", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 71280E (13 October 2008); https://doi.org/10.1117/12.806450
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Fuzzy logic

Wavelets

Wavelet transforms

Fuzzy systems

Pattern recognition

Detection and tracking algorithms

Diagnostics

Back to Top