A Roller Bearing Fault Diagnosis Method Based on LCD Energy Entropy and ACROA-SVM
This study investigates a novel method for roller bearing fault diagnosis based on local characteristic-scale decomposition (LCD) energy entropy, together with a support vector machine designed using an Artificial Chemical Reaction Optimisation Algorithm, referred to as an ACROA-SVM. First, the orig...
Saved in:
Main Authors: | HungLinh Ao, Junsheng Cheng, Kenli Li, Tung Khac Truong |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2014/825825 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of LCD-SVD Technique and CRO-SVM Method to Fault Diagnosis for Roller Bearing
by: Songrong Luo, et al.
Published: (2015-01-01) -
Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis
by: Jinde Zheng, et al.
Published: (2014-01-01) -
Degradation Assessment and Fault Diagnosis for Roller Bearing Based on AR Model and Fuzzy Cluster Analysis
by: Lingli Jiang, et al.
Published: (2011-01-01) -
Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm
by: Yuanyuan Li, et al.
Published: (2022-01-01) -
Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM
by: Jiang Xingmeng, et al.
Published: (2016-01-01)