Fault Diagnosis of CNC Machine Tool Based on Bayesian Formula

Ying Yu, Ming Chen, Ying Lei Li
{"title":"Fault Diagnosis of CNC Machine Tool Based on Bayesian Formula","authors":"Ying Yu, Ming Chen, Ying Lei Li","doi":"10.4028/www.scientific.net/AMM.271-272.1765","DOIUrl":null,"url":null,"abstract":"Bayesian formula is used to determine diagnosis sequence when several fault trees meet requirements. Bayesian prior probability is usually determined through expert or the user's subjective judgment and historical experience. If there is lack of expert experience, the determination of priori probability is very difficult. A real-time priori probability calculation method is proposed, which needn’t any priori-knowledge and can regulate automatic on the monitoring parameters. It takes into account the multiple diagnosis impact and more flexible than fixed priori probability according application.","PeriodicalId":8039,"journal":{"name":"Applied Mechanics and Materials","volume":"49 1","pages":"1765 - 1769"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mechanics and Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/www.scientific.net/AMM.271-272.1765","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Bayesian formula is used to determine diagnosis sequence when several fault trees meet requirements. Bayesian prior probability is usually determined through expert or the user's subjective judgment and historical experience. If there is lack of expert experience, the determination of priori probability is very difficult. A real-time priori probability calculation method is proposed, which needn’t any priori-knowledge and can regulate automatic on the monitoring parameters. It takes into account the multiple diagnosis impact and more flexible than fixed priori probability according application.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于贝叶斯公式的数控机床故障诊断
当多个故障树满足要求时,采用贝叶斯公式确定诊断顺序。贝叶斯先验概率通常是通过专家或用户的主观判断和历史经验确定的。如果缺乏专家经验,先验概率的确定是非常困难的。提出了一种实时先验概率计算方法,该方法不需要任何优先级知识,可以对监测参数进行自动调节。它考虑了多重诊断的影响,根据应用比固定的先验概率更灵活。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Analysis and Design of Steel Cement Storage Silo Study on Influence of Core Structure on Catalytic Converter Performance Using CFD Structural and Geochemistry of Air Piau Gold Mineralisation in Kelantan, North-East Peninsular Malaysia A Novel Powder Addition Method for Improving Tensile Strength of Polylactic-Acid Prepared by Using Fused Filament Fabrication (FFF) Monitoring of Building Services Using Artificial Intelligence
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1