Fault Diagnosis of Rolling Bearing Based on Probability box Theory and GA-SVM
For an intelligent detection of bearing failure in rotating machinery, this paper proposed a fault diagnosis method based on a probability box (p-box) and support vector machine (SVM) with a genetic algorithm (GA) algorithm. Firstly, based on vibration signals of the bearing, the different p-boxes a...
Saved in:
Main Authors: | Hong Tang, Zhengxing Yuan, Hongliang Dai, Yi Du |
---|---|
Format: | article |
Language: | EN |
Published: |
IEEE
2020
|
Subjects: | |
Online Access: | https://doaj.org/article/dcdde715913a4975990c9ccf80a90ee0 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Unmanned Aerial Vehicle Troubleshooting Mode Selection Method Based on SIF-SVM with Fault Phenomena Text Record
by: Linchao Yang, et al.
Published: (2021) -
Fault detection algorithm of industrial process based on DW-ICA-SVM
by: Jinyu GUO, et al.
Published: (2021) -
Research on vibration monitoring and fault diagnosis of rotating machinery based on internet of things technology
by: Zhang Xiaoran, et al.
Published: (2021) -
Mapping Mineral Prospectivity Using a Hybrid Genetic Algorithm–Support Vector Machine (GA–SVM) Model
by: Xishihui Du, et al.
Published: (2021) -
Fault Diagnosis of Permanent Magnet DC Motors Based on Multi-Segment Feature Extraction
by: Lixin Lu, et al.
Published: (2021)