{"title":"基于二类模糊逻辑系统的声发射信号特征分析","authors":"Qun Ren, L. Baron, M. Balazinski, K. Jemielniak","doi":"10.1109/NAFIPS.2010.5548197","DOIUrl":null,"url":null,"abstract":"In this paper, type-2 fuzzy logic system is applied to analyse acoustic emission signal feature for tool condition monitoring in a tool micromilling process. To make the comparison and evaluation of AE signal features easier and more transparent, Type-2 fuzzy analysis is used as not only a powerful tool to model AE SFs, but also a great estimator for the ambiguities and uncertainties associated with them. Depend on the estimation of root-mean-square error (RMSE) and variations in modeling results of all signal features, reliable ones are selected and integrated into tool wear evaluation. A discussion and comparison of results is given.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Acoustic emission signal feature analysis using type-2 fuzzy logic System\",\"authors\":\"Qun Ren, L. Baron, M. Balazinski, K. Jemielniak\",\"doi\":\"10.1109/NAFIPS.2010.5548197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, type-2 fuzzy logic system is applied to analyse acoustic emission signal feature for tool condition monitoring in a tool micromilling process. To make the comparison and evaluation of AE signal features easier and more transparent, Type-2 fuzzy analysis is used as not only a powerful tool to model AE SFs, but also a great estimator for the ambiguities and uncertainties associated with them. Depend on the estimation of root-mean-square error (RMSE) and variations in modeling results of all signal features, reliable ones are selected and integrated into tool wear evaluation. A discussion and comparison of results is given.\",\"PeriodicalId\":394892,\"journal\":{\"name\":\"2010 Annual Meeting of the North American Fuzzy Information Processing Society\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Annual Meeting of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2010.5548197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2010.5548197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Acoustic emission signal feature analysis using type-2 fuzzy logic System
In this paper, type-2 fuzzy logic system is applied to analyse acoustic emission signal feature for tool condition monitoring in a tool micromilling process. To make the comparison and evaluation of AE signal features easier and more transparent, Type-2 fuzzy analysis is used as not only a powerful tool to model AE SFs, but also a great estimator for the ambiguities and uncertainties associated with them. Depend on the estimation of root-mean-square error (RMSE) and variations in modeling results of all signal features, reliable ones are selected and integrated into tool wear evaluation. A discussion and comparison of results is given.
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