基于自适应神经模糊算法的机械密封面摩擦状态识别

Wenge Zhang
{"title":"基于自适应神经模糊算法的机械密封面摩擦状态识别","authors":"Wenge Zhang","doi":"10.1109/ICVRIS.2018.00117","DOIUrl":null,"url":null,"abstract":"In order to ensure the compatibility and balance of the low friction and small leakage of mechanical seal, a kind of friction state recognition of mechanical seal face dependent on adaptive neuro fuzzy (hereinafter referred to as ANFA for short) is put forward. In this algorithm, the variable neighborhood algorithm is combined with the PM mechanical seal face friction state recognition, which has overcome the defects that are existing in the traditional mechanical seal face frictional state recognition. Finally, simulation comparison is carried out on the proposed algorithm and the VNM algorithm, which has verified that the algorithm put forward in this paper can quickly identify the friction state of the mechanical seal face in the working process.","PeriodicalId":152317,"journal":{"name":"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Friction State Recognition of Mechanical Seal Face Dependent on Adaptive Neuro Fuzzy Algorithm\",\"authors\":\"Wenge Zhang\",\"doi\":\"10.1109/ICVRIS.2018.00117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to ensure the compatibility and balance of the low friction and small leakage of mechanical seal, a kind of friction state recognition of mechanical seal face dependent on adaptive neuro fuzzy (hereinafter referred to as ANFA for short) is put forward. In this algorithm, the variable neighborhood algorithm is combined with the PM mechanical seal face friction state recognition, which has overcome the defects that are existing in the traditional mechanical seal face frictional state recognition. Finally, simulation comparison is carried out on the proposed algorithm and the VNM algorithm, which has verified that the algorithm put forward in this paper can quickly identify the friction state of the mechanical seal face in the working process.\",\"PeriodicalId\":152317,\"journal\":{\"name\":\"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRIS.2018.00117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS.2018.00117","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

为了保证机械密封低摩擦、小泄漏的相容性和平衡性,提出了一种基于自适应神经模糊的机械密封面摩擦状态识别方法(以下简称ANFA)。该算法将变邻域算法与永磁机械密封面摩擦状态识别相结合,克服了传统机械密封面摩擦状态识别存在的缺陷。最后,将本文提出的算法与VNM算法进行仿真比较,验证了本文提出的算法能够快速识别机械密封面在工作过程中的摩擦状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Friction State Recognition of Mechanical Seal Face Dependent on Adaptive Neuro Fuzzy Algorithm
In order to ensure the compatibility and balance of the low friction and small leakage of mechanical seal, a kind of friction state recognition of mechanical seal face dependent on adaptive neuro fuzzy (hereinafter referred to as ANFA for short) is put forward. In this algorithm, the variable neighborhood algorithm is combined with the PM mechanical seal face friction state recognition, which has overcome the defects that are existing in the traditional mechanical seal face frictional state recognition. Finally, simulation comparison is carried out on the proposed algorithm and the VNM algorithm, which has verified that the algorithm put forward in this paper can quickly identify the friction state of the mechanical seal face in the working process.
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:604180095
Book学术官方微信