{"title":"通过 ANFIS 对非线性三油箱系统进行故障诊断","authors":"Kemal Uçak, F. Caliskan, Gulay Oke","doi":"10.1109/ELECO.2013.6713910","DOIUrl":null,"url":null,"abstract":"In this paper, two intelligent methods namely Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), are implemented to diagnose the leakage faults in a nonlinear three tank system. Two separate structures are utilized for fault diagnosis. One is to identify the dynamics of the plant and the other is to construct the residual logic mechanism. The performance of the proposed methods are evaluated by simulations carried out on a three tank system (TTS). The leakages in tanks are considered as faults in the tank system.","PeriodicalId":108357,"journal":{"name":"2013 8th International Conference on Electrical and Electronics Engineering (ELECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fault diagnosis in a nonlinear three-tank system via ANFIS\",\"authors\":\"Kemal Uçak, F. Caliskan, Gulay Oke\",\"doi\":\"10.1109/ELECO.2013.6713910\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, two intelligent methods namely Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), are implemented to diagnose the leakage faults in a nonlinear three tank system. Two separate structures are utilized for fault diagnosis. One is to identify the dynamics of the plant and the other is to construct the residual logic mechanism. The performance of the proposed methods are evaluated by simulations carried out on a three tank system (TTS). The leakages in tanks are considered as faults in the tank system.\",\"PeriodicalId\":108357,\"journal\":{\"name\":\"2013 8th International Conference on Electrical and Electronics Engineering (ELECO)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Conference on Electrical and Electronics Engineering (ELECO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELECO.2013.6713910\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Conference on Electrical and Electronics Engineering (ELECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELECO.2013.6713910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault diagnosis in a nonlinear three-tank system via ANFIS
In this paper, two intelligent methods namely Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), are implemented to diagnose the leakage faults in a nonlinear three tank system. Two separate structures are utilized for fault diagnosis. One is to identify the dynamics of the plant and the other is to construct the residual logic mechanism. The performance of the proposed methods are evaluated by simulations carried out on a three tank system (TTS). The leakages in tanks are considered as faults in the tank system.