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《Acta Armamentarii》 2008-02
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Equipment Degradation State Recognition Method and Its Applications Based on Wavelet Feature Scale Entropy and Hidden Semi-Markov Models

ZENG Qing-hu,QIU Jing,LIU Guan-jun,TAN Xiao-dong(Institute of Mechantronics Engineering,National University of Defense Technology,Changsha 410073,Hunan,China)  
The failure process of mechanical equipments usually consists of a series of degraded states,correctly recognizing and estimating the current state of the equipment has important meaning for farther preventing equipment from degrading and failing.The equipment degradation state recognition method based on wavelet feature scale entropy and HSMM was proposed.It is the procedures of the method that the signal is decomposed by wavelet transform,the wavelet feature scale entropy is extracted,the wavelet feature scale entropy vectors of the signals which are inputted to the HSMM for training are constructed,the running state classified model of the equipment based on HSMM is constructed to recognizing the equipment degradation states.A roller bearing was taken as an example and several states of roller with normal state and different fault severity states were recognized by the proposed method.Experiment results show that the proposed method is very effective.
【CateGory Index】: TH17
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