• Title of article

    Fault Diagnosis of a Hydraulic Pump Based on the CEEMD-STFT Time-Frequency Entropy Method and Multiclass SVM Classifier

  • Author/Authors

    Zhao,Wanlin Science & Technology Laboratory on Reliability & Environmental Engineering, China , Wang,Zili Science & Technology Laboratory on Reliability & Environmental Engineering, China , Ma,Jian Science & Technology Laboratory on Reliability & Environmental Engineering, China , Li, Lianfeng Science & Technology Laboratory on Reliability & Environmental Engineering, China

  • Pages
    9
  • From page
    1
  • To page
    9
  • Abstract
    The fault diagnosis of hydraulic pumps is currently important and significant to ensure the normal operation of the entire hydraulic system. Considering the nonlinear characteristics of hydraulic-pump vibration signals and the mode mixing problem of the original Empirical Mode Decomposition (EMD) method, first, we use the Complete Ensemble EMD (CEEMD) method to decompose the signals. Second, the time-frequency analysis methods, which include the Short-Time Fourier Transform (STFT) and time-frequency entropy calculation, are applied to realize the robust feature extraction. Third, the multiclass Support Vector Machine (SVM) classifier is introduced to automatically classify the fault mode in this paper. An actual hydraulic-pump experiment demonstrates the procedure with a complete feature extraction and accurate mode classification.
  • Keywords
    Multiclass SVM Classifier , Fault Diagnosis , Hydraulic Pump Based , CEEMD-STFT , Time-Frequency Entropy Method
  • Journal title
    Shock and Vibration
  • Serial Year
    2016
  • Record number

    2615209