Fault Diagnosis of Bearing Based on Conjugate Gradient BP Algorithm

Author:

Lu Li Xin1,Zhao Yan1,Li Gui Qin1,Li Zheng1,Yuan Xiao2,Li Hong Bo2

Affiliation:

1. Shanghai University

2. East China University of Science and Technology

Abstract

Largely used in industry field, bearing is one of the most vulnerable components in an equipment. Owing to the complicated and nonlinear relationship between features and corresponding specific fault, it is less efficient to diagnosis the faults in tradition ways ,especially to deal with the fault of a mega machine. BP neural network whose strength is to solve the nonlinear problems makes it more precise and efficient to determine the fault of bearing. Conjugate gradient algorithm is proposed as the training method of the BP neural network. Compared with standard training method, conjugate gradient has the advantage of training speed and generalization ability, which is confirmed by the results of neural network model whose inputs are common bearing fault samples.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference13 articles.

1. L. M. R. BACCARINI, et al. SVM practical industrial application for mechanical faults diagnostic,J. Expert Systems with Applications, 2011. 38(6): 6980-6984.

2. P. JAYASWAL, S. VERMA,A. WADHWANI. Development of EBP-Artificial neural network expert system for rolling element bearing fault diagnosis,J. Journal of Vibration and Control, 2011. 17(8): 1131-1148.

3. T. -C. LIN. Analog circuit fault diagnosis under parameter variations based on type-2 fuzzy logic systems,J. International Journal of Innovative Computing, Information and Control, 2010. 6(5): 2137-2158.

4. L. MAO, L. XIAOQUAN,S. YANG. Research on faults diagnosis of distribution network based on adaptive immune genetic algorithm,J. Application of Electronic Technique, 2012. 8: 031.

5. Z. Z. LIU, et al. Measure and analysis about vibration characteristic of roller bearing fault,J. Machinery Design & Manufacure, 2009(3): 103-105.

Cited by 2 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

同舟云学术

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