Rotor Fault Diagnosis Based on Characteristic Frequency Band Energy Entropy and Support Vector Machine
Rotor is a widely used and easily defected mechanical component. Thus, it is significant to develop effective techniques for rotor fault diagnosis. Fault signature extraction and state classification of the extracted signatures are two key steps for diagnosing rotor faults. To complete the accurate...
Main Authors: | Bin Pang, Guiji Tang, Chong Zhou, Tian Tian |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-12-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/20/12/932 |
Similar Items
-
FULL VECTOR LOCAL CHARACTERISTIC DECOMPOSITION AND ITS APPLICATION IN ROTOR RUB FAULT FEATURE EXTRACTION
by: HUANG ChuanJin, et al.
Published: (2017-01-01) -
Compound Fault Diagnosis of Rolling Bearing Based on Singular Negentropy Difference Spectrum and Integrated Fast Spectral Correlation
by: Guiji Tang, et al.
Published: (2020-03-01) -
The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults
by: Tian Tian, et al.
Published: (2023-11-01) -
Rolling Bearing Fault Diagnosis Based on Optimal Notch Filter and Enhanced Singular Value Decomposition
by: Bin Pang, et al.
Published: (2018-06-01) -
Rolling bearing fault diagnosis method based on modified fourier mode decomposition and band entropy
by: Junfeng LIU, et al.
Published: (2022-02-01)