Gearbox Fault Diagnosis based on LMD Approximate Entropy and PSO-ELM

For the detection and identification problems of common faults in the use of gearbox,considering the nonlinear,non-stationary properties of the gearbox vibration response signal,a method for the gearbox fault diagnosis based on local mean decomposition（ LMD） approximate entropy and PSO-ELM is propos...

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Bibliographic Details
Published inJixie Chuandong Vol. 41; pp. 109 - 113
Main Authors Zhang Yuxue, Pan Hongxia
Format Journal Article
LanguageChinese
Published Editorial Office of Journal of Mechanical Transmission 01.01.2017
Subjects
Gearbox;LMD;Approximate entropy;PSO-ELM;Fault diagnosis
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Summary:For the detection and identification problems of common faults in the use of gearbox,considering the nonlinear,non-stationary properties of the gearbox vibration response signal,a method for the gearbox fault diagnosis based on local mean decomposition（ LMD） approximate entropy and PSO-ELM is proposed.Firstly,the LMD decomposition method is used for gearbox vibration signal,with correlation coefficient method extracted the first four PF components which contain the main fault information. By using the approximate entropy to describe quantitatively,and the feature vector is formed. Finally,the input weights of ELM and the threshold value of the hidden layer neurons are optimized by the particle swarm optimization algorithm,the model of PSO-ELM is established,and the approximate entropy values are input into the ELM and PSO-ELM models to recognize and classify the fault types of the gearbox of different conditions. The results show that based on LMD approximate entropy and PSO-ELM has the higher classification
ISSN:1004-2539