{"title":"电子产品剩余使用寿命预测的融合预测方法","authors":"Shunfeng Cheng, M. Pecht","doi":"10.1109/COASE.2009.5234098","DOIUrl":null,"url":null,"abstract":"Prognostics and health management methods can provide advance warning of failure; reduce the life cycle cost of a product by decreasing inspection costs, downtime, and inventory; and assist in the design and logistical support of fielded and future electronic products. Traditional prognostic methods, such as data-driven methods and physics of failure methods have some limitations. This paper presents a fusion prognostics method, which fuses data-driven methods and physics of failure methods to predict the remaining useful life of electronic products. This method integrates the advantage and overcome the limitations of the data-driven methods and the physics of failure methods to provide better predictions.","PeriodicalId":386046,"journal":{"name":"2009 IEEE International Conference on Automation Science and Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"102","resultStr":"{\"title\":\"A fusion prognostics method for remaining useful life prediction of electronic products\",\"authors\":\"Shunfeng Cheng, M. Pecht\",\"doi\":\"10.1109/COASE.2009.5234098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prognostics and health management methods can provide advance warning of failure; reduce the life cycle cost of a product by decreasing inspection costs, downtime, and inventory; and assist in the design and logistical support of fielded and future electronic products. Traditional prognostic methods, such as data-driven methods and physics of failure methods have some limitations. This paper presents a fusion prognostics method, which fuses data-driven methods and physics of failure methods to predict the remaining useful life of electronic products. This method integrates the advantage and overcome the limitations of the data-driven methods and the physics of failure methods to provide better predictions.\",\"PeriodicalId\":386046,\"journal\":{\"name\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"102\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COASE.2009.5234098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2009.5234098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fusion prognostics method for remaining useful life prediction of electronic products
Prognostics and health management methods can provide advance warning of failure; reduce the life cycle cost of a product by decreasing inspection costs, downtime, and inventory; and assist in the design and logistical support of fielded and future electronic products. Traditional prognostic methods, such as data-driven methods and physics of failure methods have some limitations. This paper presents a fusion prognostics method, which fuses data-driven methods and physics of failure methods to predict the remaining useful life of electronic products. This method integrates the advantage and overcome the limitations of the data-driven methods and the physics of failure methods to provide better predictions.