A fault diagnosis method based on AWA-SVM of complicated equipment

Owing to the diversity and uncertainty of the faults of complicated equipment, applying the Adaptive Wavelet Analysis to pick up the characteristics of the circuit measured and to get the feature vector of the signal is a effective way to match the characteristics of the wavelet's time frequenc...

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Bibliographic Details
Main Authors: Shi Lianyan, Chen Lin, Song Wenyuan, Wang Hongyun
Format: Conference Proceeding
Language:English
Subjects:
adaptive wavelet analysis
Circuit faults
complicated equipmen
Fault diagnosis
support vector machine
Support vector machines
Time frequency analysis
Training
Wavelet analysis
Wavelet transforms
Online Access:Request full text
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Summary:Owing to the diversity and uncertainty of the faults of complicated equipment, applying the Adaptive Wavelet Analysis to pick up the characteristics of the circuit measured and to get the feature vector of the signal is a effective way to match the characteristics of the wavelet's time frequency and the circuit's response time frequency. Combined with fault diagnosis of the support vector machine, it's feasible to overcome the difficulty caused by small-scaled samples, nonlinearity and multi dimension. It has been testify effective and accurate in fault diagnosis of complicated equipment.
DOI:10.1109/MEC.2011.6025827