Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (12): 258-261.doi: 10.11896/jsjkx.200700039

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Elevator Boot Fault Diagnosis Method Based on Gabor Wavelet Transform and Multi-coreSupport Vector Machine

ZHU Xiao-ling1, LI Kun1, ZHANG Chang-sheng1, DU Fu-xin2   

  1. 1 Faculty of Information Engineering and AutomationKunming University of Science and Technology Kunming 650504,China
    2 School of Mechanical Engineering Shandong UniversityJinan 250061,China
  • Received:2020-07-07 Revised:2020-09-18 Published:2020-12-17
  • About author:ZHU Xiao-ling,born in 1996postgra-duate.Her main research interests include lift fault diagnosis and so on.
    LI Kun,born in 1970Ph.Dassociate professorpostgraduate tutor.His main research interests include elevator fault diagnosiscontrol theory and control engineering.
  • Supported by:
    National Natural Science Foundation(51705289).

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Abstract: As an important part of the elevator carthe elevator boot has a direct impact on the safety of the elevator.In order to make a more accurate comprehensive diagnosis of the elevator boot failurea diagnosis method based on Gabor wavelet transform and multi-core support vector machine is proposed.Firstthe vibration signal of the main body of the device is collected by an acceleration sensorand the eigenmode function component is obtained by empirical mode decomposition.Thena Gabor filter is used to filter and denoise the low frequency components to achieve the feature enhancement of the extracted data at low frequencies.Finallythe local and global kernel functions are linearly added using weights to form a multi-core support vector machine to classify the data.Experimental results verify the effectiveness of the proposed method.Compared with the fault diagnosis method based on wavelet transform and least squares support vector machinethe fault diagnosis accuracy of the proposed method is improved by about 5%reaching 87.6%.

Key words: Elevator boot, Empirical mode decomposition, Fault diagnosis, Gabor wavelet, Multi-core support vector machine

CLC Number: 

  • TU857
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