BP神经网络在机械故障分类中的应用

Fang Zhou, Jianheng Ji, De-zhen Feng
{"title":"BP神经网络在机械故障分类中的应用","authors":"Fang Zhou, Jianheng Ji, De-zhen Feng","doi":"10.1109/IWISA.2009.5073165","DOIUrl":null,"url":null,"abstract":"Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"92 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Application of BP Neural Network on Mechanical Failure Classification\",\"authors\":\"Fang Zhou, Jianheng Ji, De-zhen Feng\",\"doi\":\"10.1109/IWISA.2009.5073165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation\",\"PeriodicalId\":6327,\"journal\":{\"name\":\"2009 International Workshop on Intelligent Systems and Applications\",\"volume\":\"92 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2009.5073165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2009.5073165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在模糊分类方法的基础上,提出了一种反向传播神经网络诊断算法。对于一些复杂的环境,传统的反向传播神经网络在分类上存在一定的局限性。本文将模糊模型应用于神经网络结构,利用分类方差和能量函数来调节神经网络的收敛性。利用改进的非线性映射特性,该诊断处理的准确率达到100%,而传统方法的识别率仅为65%。关键词:分类,神经网络,诊断,反向传播
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of BP Neural Network on Mechanical Failure Classification
Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信