{"title":"基于动态故障树的机械异常运行状态检测方法研究","authors":"Meixuan Li","doi":"10.1109/ICVRIS51417.2020.00183","DOIUrl":null,"url":null,"abstract":"Because of the low sensitivity of the traditional method, the error of the detection result is large. In view of the above problems, the detection method of mechanical abnormal operation state based on dynamic fault tree is studied. The dynamic fault tree of mechanical operation state is established, and the dynamic fault tree is modularized, decomposed and quantitatively analyzed. The dynamic fault tree is input into the computer, and combined with the characteristics of mechanical fault signal, the detection of mechanical abnormal operation state is realized. The experimental results show that the proposed method has smaller detection error and higher sensitivity.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study on dynamic fault tree based mechanical abnormal running state detection method\",\"authors\":\"Meixuan Li\",\"doi\":\"10.1109/ICVRIS51417.2020.00183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Because of the low sensitivity of the traditional method, the error of the detection result is large. In view of the above problems, the detection method of mechanical abnormal operation state based on dynamic fault tree is studied. The dynamic fault tree of mechanical operation state is established, and the dynamic fault tree is modularized, decomposed and quantitatively analyzed. The dynamic fault tree is input into the computer, and combined with the characteristics of mechanical fault signal, the detection of mechanical abnormal operation state is realized. The experimental results show that the proposed method has smaller detection error and higher sensitivity.\",\"PeriodicalId\":162549,\"journal\":{\"name\":\"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRIS51417.2020.00183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS51417.2020.00183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on dynamic fault tree based mechanical abnormal running state detection method
Because of the low sensitivity of the traditional method, the error of the detection result is large. In view of the above problems, the detection method of mechanical abnormal operation state based on dynamic fault tree is studied. The dynamic fault tree of mechanical operation state is established, and the dynamic fault tree is modularized, decomposed and quantitatively analyzed. The dynamic fault tree is input into the computer, and combined with the characteristics of mechanical fault signal, the detection of mechanical abnormal operation state is realized. The experimental results show that the proposed method has smaller detection error and higher sensitivity.