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

Joint Authors

Wang, Zili
Zhao, Wanlin
Ma, Jian
Li, Lianfeng

Source

Shock and Vibration

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-09-26

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Zhao, Wanlin& Wang, Zili& Ma, Jian& Li, Lianfeng. 2016. Fault Diagnosis of a Hydraulic Pump Based on the CEEMD-STFT Time-Frequency Entropy Method and Multiclass SVM Classifier. Shock and Vibration،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1118915

Modern Language Association (MLA)

Zhao, Wanlin…[et al.]. Fault Diagnosis of a Hydraulic Pump Based on the CEEMD-STFT Time-Frequency Entropy Method and Multiclass SVM Classifier. Shock and Vibration No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1118915

American Medical Association (AMA)

Zhao, Wanlin& Wang, Zili& Ma, Jian& Li, Lianfeng. Fault Diagnosis of a Hydraulic Pump Based on the CEEMD-STFT Time-Frequency Entropy Method and Multiclass SVM Classifier. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1118915

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1118915