{"title":"空气弹簧剩余使用寿命预测","authors":"F. Ahmadzadeh, Jonas Biteus, O. Steinert","doi":"10.1109/ICPHM.2019.8819413","DOIUrl":null,"url":null,"abstract":"The remaining useful life estimation is an important function of an efficient prognostics and health management (PHM) system and can be used preventively to replace the component with the aim of avoiding a breakdown. The prediction of remaining life time of the air spring as one of the critical component of truck is the main goal of this research. A specific statistical model called mean residual life of Gompertz (MRL-Gompertz) has been considered to predict the remaining life time of the air spring, given that it has survived until a specific time. A set of sensors has been used to collect input variables for model. The time difference between start of usage and failure dates has been considered as life time of the air spring which is output of the model. The accuracy of the model prediction based on confusion matrix is more than 94%. This solution can be a basis for preventive maintenance because it reduces down time, vehicle off road (VOR) and use the components until the maximum life time before renewals takes place. It means huge saving in term of reducing cost of unplanned maintenance and increasing benefit by optimizing preventive maintenance.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Remaining useful life Prediction of air spring\",\"authors\":\"F. Ahmadzadeh, Jonas Biteus, O. Steinert\",\"doi\":\"10.1109/ICPHM.2019.8819413\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The remaining useful life estimation is an important function of an efficient prognostics and health management (PHM) system and can be used preventively to replace the component with the aim of avoiding a breakdown. The prediction of remaining life time of the air spring as one of the critical component of truck is the main goal of this research. A specific statistical model called mean residual life of Gompertz (MRL-Gompertz) has been considered to predict the remaining life time of the air spring, given that it has survived until a specific time. A set of sensors has been used to collect input variables for model. The time difference between start of usage and failure dates has been considered as life time of the air spring which is output of the model. The accuracy of the model prediction based on confusion matrix is more than 94%. This solution can be a basis for preventive maintenance because it reduces down time, vehicle off road (VOR) and use the components until the maximum life time before renewals takes place. It means huge saving in term of reducing cost of unplanned maintenance and increasing benefit by optimizing preventive maintenance.\",\"PeriodicalId\":113460,\"journal\":{\"name\":\"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPHM.2019.8819413\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPHM.2019.8819413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The remaining useful life estimation is an important function of an efficient prognostics and health management (PHM) system and can be used preventively to replace the component with the aim of avoiding a breakdown. The prediction of remaining life time of the air spring as one of the critical component of truck is the main goal of this research. A specific statistical model called mean residual life of Gompertz (MRL-Gompertz) has been considered to predict the remaining life time of the air spring, given that it has survived until a specific time. A set of sensors has been used to collect input variables for model. The time difference between start of usage and failure dates has been considered as life time of the air spring which is output of the model. The accuracy of the model prediction based on confusion matrix is more than 94%. This solution can be a basis for preventive maintenance because it reduces down time, vehicle off road (VOR) and use the components until the maximum life time before renewals takes place. It means huge saving in term of reducing cost of unplanned maintenance and increasing benefit by optimizing preventive maintenance.