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| A study on the method of rotor vibration fault diagnosis based on KL-HVD |
| ZHU Xiaoxun, ZHOU Pei, YUAN Yiming, XU Bochao, HAN Zhonghe |
| Department of Power Engineering, North China Electric Power University, Baoding 071003, China |
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Abstract The false components of HVD have seriously restricted its application in practical fault diagnosis.To solve this problem, Kullback-leibler (K-L) divergence was employed, which is the concept of information theory with HVD (KL-HVD).Components of HVD were treated as signals with various probability distributions, supposing that the probability distributions of real components are similar to the original signal.The false component identification method is based on K-L divergence (KL-HVD).KL-HVD, used in K-L divergence as a distinguishing index, was proposed to solve this problem.Based on the original HVD method, KL-HVD first calculates the K-L divergence values between the HVD components and the original signal and then clustered these values according to the Gaussian mixture model.Finally, the trues and the falses could automatically be separated from each other because of their intrinsic differences, and the false components will be eliminated.The results of the rotor fault signal analysis verify that KL-HVD divergence is more suitable for identifying the HVD false components than mutual information and the correlation coefficient method, and it could extract the faults’ time-frequency characteristics more clearly.
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Received: 28 March 2017
Published: 15 August 2018
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