Online Monitoring of Chemical Engineering Explosion-proof Motor Based on Acoustic Features

doi:10.3969/j.issn.1006-2475.2014.12.022

Abstract

Abstract: There are various problems appearing in normal work process of explosion-proof motor. In order to eliminate these uncertainties, this paper puts forward a fault monitoring technique based on acoustic characteristics. In this paper, we use the method of Mel frequency cepstrum coefficient for feature extraction, with the purpose of improving the recognition rate of fault detection. In addition, we adopt hidden Markov models to identify the state. Thus the training fault model and the audio signal will achieve the best match.

Key words: explosion-proof motor, signal processing, feature extraction, state recognition

CLC Number:

TP273

LI Jun, LI Wei-xin, LI Jian-ping. Online Monitoring of Chemical Engineering Explosion-proof Motor Based on Acoustic Features[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.12.022.

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