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

  • Wanlin Zhao
  • , Zili Wang
  • , Jian Ma*
  • , Lianfeng Li
  • *Corresponding author for this work
  • Science and Technology on Reliability and Environmental Engineering Laboratory
  • Beihang University

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number2609856
JournalShock and Vibration
Volume2016
DOIs
StatePublished - 2016

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