Rolling Bearing Fault Diagnosis Based on Time-Frequency Feature Extraction and IBA-SVM
Author:
Affiliation:
1. College of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan, China
Funder
Natural Science Foundation of the Higher Education Institute of Anhui Province
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09856613.pdf?arnumber=9856613
Reference35 articles.
1. Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations;ali;Eng Appl Artif Intell,2015
2. Fault diagnosis of rolling bearing based on wavelet transform and envelope spectrum correlation
3. Based on fault diagnosis method of rolling bearing based on FFT and CNN;wenzhe;Applied Technology,2021
4. Locust optimization algorithm with perturbation mechanism and enhanced Lévy flight;wenzhen;Minitype Microcomputer System,2022
5. Diagnostics of gear deterioration using EEMD approach and PCA process
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A novel framework for bearing fault diagnosis across working conditions based on time-frequency fusion and multi-sensor data fusion;Measurement Science and Technology;2024-09-13
2. Research on distribution position of chip-split groove of discrete-edge end mills based on structural dynamic stability;The International Journal of Advanced Manufacturing Technology;2024-09-06
3. Rolling Bearing Fault Diagnosis Based on SABO–VMD and WMH–KNN;Sensors;2024-08-02
4. Research on feature extraction method for underwater acoustic signal using secondary decomposition;Ocean Engineering;2024-08
5. Research on a Fault Feature Extraction Method for an Electric Multiple Unit Axle-Box Bearing Based on a Resonance-Based Sparse Signal Decomposition and Variational Mode Decomposition Method Based on the Sparrow Search Algorithm;Sensors;2024-07-17
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3