{"title":"基于ANFIS的汽车发动机性能参数故障诊断","authors":"Jianhua Zhang, Li-fang Kong, Z. Tian, Wei Hao","doi":"10.1109/WISM.2010.149","DOIUrl":null,"url":null,"abstract":"In order to solve the fault diagnosis problem of performance Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 84.38% to 98.81%, training error falling from 0.001683 to 0.0011526. Simulation results show that the fitting ability, convergence speed and recognition accuracy of improved ANFIS model are all superior to ANFIS. So a contingent fault of automobile engine can be identified effectively. Moreover, it can effectively detect the performance parameter failure for the automobile engine.","PeriodicalId":119569,"journal":{"name":"2010 International Conference on Web Information Systems and Mining","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"The Performance Parameter Fault Diagnosis for Automobile Engine Based on ANFIS\",\"authors\":\"Jianhua Zhang, Li-fang Kong, Z. Tian, Wei Hao\",\"doi\":\"10.1109/WISM.2010.149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the fault diagnosis problem of performance Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 84.38% to 98.81%, training error falling from 0.001683 to 0.0011526. Simulation results show that the fitting ability, convergence speed and recognition accuracy of improved ANFIS model are all superior to ANFIS. So a contingent fault of automobile engine can be identified effectively. Moreover, it can effectively detect the performance parameter failure for the automobile engine.\",\"PeriodicalId\":119569,\"journal\":{\"name\":\"2010 International Conference on Web Information Systems and Mining\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Web Information Systems and Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISM.2010.149\",\"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 International Conference on Web Information Systems and Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISM.2010.149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Performance Parameter Fault Diagnosis for Automobile Engine Based on ANFIS
In order to solve the fault diagnosis problem of performance Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 84.38% to 98.81%, training error falling from 0.001683 to 0.0011526. Simulation results show that the fitting ability, convergence speed and recognition accuracy of improved ANFIS model are all superior to ANFIS. So a contingent fault of automobile engine can be identified effectively. Moreover, it can effectively detect the performance parameter failure for the automobile engine.