{"title":"基于时间间隔分裂的标记时间Petri网诊断","authors":"Baisi Liu, M. Ghazel, A. Toguyéni","doi":"10.3182/20140824-6-ZA-1003.02336","DOIUrl":null,"url":null,"abstract":"Abstract This paper deals with fault diagnosis of timed discrete event systems (TDESs), using a nondeterministic model named labeled time Petri net (LTPN). Thanks to a skillful splitting of time intervals assigned to the LTPN transitions, analyzing diagnosability in such a timed context can be performed using techniques from the untimed context. Moreover, a deterministic structure called augmented state class set graph (ASG) is built on the fly, for both analyzing (Δ-)diagnosability and deriving an online diagnoser.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"19 1","pages":"1784-1789"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Diagnosis of Labeled Time Petri Nets Using Time Interval Splitting\",\"authors\":\"Baisi Liu, M. Ghazel, A. Toguyéni\",\"doi\":\"10.3182/20140824-6-ZA-1003.02336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This paper deals with fault diagnosis of timed discrete event systems (TDESs), using a nondeterministic model named labeled time Petri net (LTPN). Thanks to a skillful splitting of time intervals assigned to the LTPN transitions, analyzing diagnosability in such a timed context can be performed using techniques from the untimed context. Moreover, a deterministic structure called augmented state class set graph (ASG) is built on the fly, for both analyzing (Δ-)diagnosability and deriving an online diagnoser.\",\"PeriodicalId\":13260,\"journal\":{\"name\":\"IFAC Proceedings Volumes\",\"volume\":\"19 1\",\"pages\":\"1784-1789\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IFAC Proceedings Volumes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3182/20140824-6-ZA-1003.02336\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Proceedings Volumes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3182/20140824-6-ZA-1003.02336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of Labeled Time Petri Nets Using Time Interval Splitting
Abstract This paper deals with fault diagnosis of timed discrete event systems (TDESs), using a nondeterministic model named labeled time Petri net (LTPN). Thanks to a skillful splitting of time intervals assigned to the LTPN transitions, analyzing diagnosability in such a timed context can be performed using techniques from the untimed context. Moreover, a deterministic structure called augmented state class set graph (ASG) is built on the fly, for both analyzing (Δ-)diagnosability and deriving an online diagnoser.