Quantitative Diagnosis of Rotor Vibration Fault Using Process Power Spectrum Entropy and Support Vector Machine Method
To improve the diagnosis capacity of rotor vibration fault in stochastic process, an effective fault diagnosis method (named Process Power Spectrum Entropy (PPSE) and Support Vector Machine (SVM) (PPSE-SVM, for short) method) was proposed. The fault diagnosis model of PPSE-SVM was established by fus...
Main Authors: | Cheng-Wei Fei, Guang-Chen Bai, Wen-Zhong Tang, Shuang Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2014-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2014/957531 |
Similar Items
-
Rotor Fault Diagnosis Based on Characteristic Frequency Band Energy Entropy and Support Vector Machine
by: Bin Pang, et al.
Published: (2018-12-01) -
Wavelet Correlation Feature Scale Entropy and Fuzzy Support Vector Machine Approach for Aeroengine Whole-Body Vibration Fault Diagnosis
by: Cheng-Wei Fei, et al.
Published: (2013-01-01) -
Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine
by: Jian-Jiun Ding, et al.
Published: (2012-07-01) -
Fault Diagnosis of Oil Pumping Machine Retarder Based on Sound Texture-Vibration Entropy Characteristics and Gray Wolf Optimization-Support Vector Machine
by: Shutao Zhao, et al.
Published: (2020-01-01) -
Fault Diagnosis System of Induction Motors Based on Multiscale Entropy and Support Vector Machine with Mutual Information Algorithm
by: Shuang Pan, et al.
Published: (2016-01-01)