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《Automation of Electric Power Systems》 2004-02
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WAVELET PACKET-MAXIMUM ENTROPY SPECTRUM ESTIMATION AND ITS APPLICATION IN TURBINE'S FAULT DIAGNOSIS

Gui Zhonghua, Han Fengqin (South China University of Technology, Guangzhou 510640, China)  
The paper takes advantage of the time-frequency localization of wavelet packet (WP) and the frequency spectrum subdivision of maximum entropy spectrum estimation (MESE), puts forward a new method of the wavelet packet-maximum entropy spectrum estimation (WP-MESE). This method can carry out multi-resolution signal decomposition and extract feature information of different machine parts as monitoring and fault diagnosis of machinery, then analyses exactly its spectrum. As an example, the dynamic specific property information of the shaft system of the turbine can be extracted effectively by using WP-MESE method. It is demonstrated that this novel method is very effective for extracting weak fault feature information and early diagnosing latent mechanical faults.
【Fund】: 国家自然科学基金(59979007)
【CateGory Index】: TP277
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