变速箱故障的鲁棒故障检测

N. Haloui, M. Abbas-Turki, T. Rodet
{"title":"变速箱故障的鲁棒故障检测","authors":"N. Haloui, M. Abbas-Turki, T. Rodet","doi":"10.1109/ICSTCC55426.2022.9931829","DOIUrl":null,"url":null,"abstract":"This contribution presents a methodology to detect material deterioration in periodic systems using model identification. To detect the failure, the relation between the model's parameters and failure's characteristics are analyzed. Thus, a robust and an efficient algorithm is proposed to detect failures. The algorithm leads to a residual parameter to identify anomaly, which allows an intuitive failure detection. The convexity of criterion, the variation of parameters within interval and the residual's expression allow to use optimisation algorithm or step evaluation of criterion, where the last procedure allows to simplify the implementation of the algorithm and aims to online utilization. The proposed approach is applied to gearbox system, where the classical analysis cannot bring clear information about deterioration. The efficiency of the proposed method is as well proved and the application is used to benchmark the algorithm's parameters.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust fault detection for gearbox failure\",\"authors\":\"N. Haloui, M. Abbas-Turki, T. Rodet\",\"doi\":\"10.1109/ICSTCC55426.2022.9931829\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This contribution presents a methodology to detect material deterioration in periodic systems using model identification. To detect the failure, the relation between the model's parameters and failure's characteristics are analyzed. Thus, a robust and an efficient algorithm is proposed to detect failures. The algorithm leads to a residual parameter to identify anomaly, which allows an intuitive failure detection. The convexity of criterion, the variation of parameters within interval and the residual's expression allow to use optimisation algorithm or step evaluation of criterion, where the last procedure allows to simplify the implementation of the algorithm and aims to online utilization. The proposed approach is applied to gearbox system, where the classical analysis cannot bring clear information about deterioration. The efficiency of the proposed method is as well proved and the application is used to benchmark the algorithm's parameters.\",\"PeriodicalId\":220845,\"journal\":{\"name\":\"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSTCC55426.2022.9931829\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTCC55426.2022.9931829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

这一贡献提出了一种方法来检测材料劣化的周期性系统使用模型识别。为了检测故障,分析了模型参数与故障特征之间的关系。因此,提出了一种鲁棒、高效的故障检测算法。该算法利用残差参数识别异常,实现了直观的故障检测。判据的凸性、参数在区间内的变化和残差的表达式允许使用优化算法或判据的阶跃评估,其中阶跃评估允许简化算法的实现并旨在在线使用。该方法适用于齿轮箱系统,传统的分析方法不能提供清晰的劣化信息。该方法的有效性得到了验证,并对算法参数进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust fault detection for gearbox failure
This contribution presents a methodology to detect material deterioration in periodic systems using model identification. To detect the failure, the relation between the model's parameters and failure's characteristics are analyzed. Thus, a robust and an efficient algorithm is proposed to detect failures. The algorithm leads to a residual parameter to identify anomaly, which allows an intuitive failure detection. The convexity of criterion, the variation of parameters within interval and the residual's expression allow to use optimisation algorithm or step evaluation of criterion, where the last procedure allows to simplify the implementation of the algorithm and aims to online utilization. The proposed approach is applied to gearbox system, where the classical analysis cannot bring clear information about deterioration. The efficiency of the proposed method is as well proved and the application is used to benchmark the algorithm's parameters.
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