DocumentCode :
3471823
Title :
Fault diagnosis and trend forecast of transformer based on acoustic recognition
Author :
Zhao, Shutao ; Pan, Liangliang ; Li, Baoshu
Author_Institution :
North China Electr. Power Univ., Baoding
fYear :
2008
fDate :
6-9 April 2008
Firstpage :
1371
Lastpage :
1374
Abstract :
After discussed the difficulty of monitoring transformer fault online, this paper proposes a fault diagnosis scheme based on acoustic wave analysis. The time and frequency domain signal processing is utilized to analyze acoustic signal so that equipments´ running status can be identified and the trend of development be predicted. Firstly, a new scheme of transformer fault diagnosis and trend forecast is designed. Transformer acoustic signal acquisition, noise elimination method in diagnosis system is represented. Secondly, the new algorithm of the signal strangeness detection and trend-based forecasting based on wavelet analysis is put forward. Lastly, the wavelet packet algorithm is utilized to analyze acoustic signal and extract frequency & time-domain features which relative with its development trend, and then the predicting consequence can be use to assess the fault type. The actual measurement test demonstrated that the serial wavelet packet transformation (WPT) algorithms have high availability and feasibility to diagnosis and forecast the transformer faults accuracy.
Keywords :
acoustic signal processing; fault diagnosis; frequency-domain analysis; power transformers; signal denoising; time-domain analysis; wavelet transforms; acoustic recognition; acoustic signal acquisition; acoustic wave analysis; fault diagnosis; frequency domain signal processing; noise elimination method; time domain signal processing; transformer; trend forecasting; wavelet analysis; wavelet packet algorithm; wavelet packet transformation algorithms; Acoustic signal processing; Acoustic waves; Algorithm design and analysis; Fault diagnosis; Frequency domain analysis; Monitoring; Signal analysis; Signal processing algorithms; Wavelet analysis; Wavelet packets; Device diagnosis; Signal processing; Strangeness measuring; Trend forecasting; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
Conference_Location :
Nanjuing
Print_ISBN :
978-7-900714-13-8
Electronic_ISBN :
978-7-900714-13-8
Type :
conf
DOI :
10.1109/DRPT.2008.4523619
Filename :
4523619
Link To Document :
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