Mohamed Salim Bidou, Sylvain Verron, L. Perez, L. Autrique
{"title":"Kalman smoother for detection of heat sources defects","authors":"Mohamed Salim Bidou, Sylvain Verron, L. Perez, L. Autrique","doi":"10.1109/ICCAD55197.2022.9853959","DOIUrl":null,"url":null,"abstract":"This work is devoted to an application of the Kalman smoother method for the detection of failure times for a system of linear parabolic partial differential equation. For complex processes whose evolution is described by partial differential equations, the detection of failures is often difficult. In thermal systems, for example, when one or more heating sources fail, the sensors placed at a distance perceive the effect with delay. The Kalman smoother is then applied when the classical Kalman filter is used for the estimation of intensity of our sources. From these estimation, it is then necessary to determine the moment of failure and the possible restart of the heating. In the following, the whole problematic and the method of resolution is presented.","PeriodicalId":436377,"journal":{"name":"2022 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Control, Automation and Diagnosis (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD55197.2022.9853959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This work is devoted to an application of the Kalman smoother method for the detection of failure times for a system of linear parabolic partial differential equation. For complex processes whose evolution is described by partial differential equations, the detection of failures is often difficult. In thermal systems, for example, when one or more heating sources fail, the sensors placed at a distance perceive the effect with delay. The Kalman smoother is then applied when the classical Kalman filter is used for the estimation of intensity of our sources. From these estimation, it is then necessary to determine the moment of failure and the possible restart of the heating. In the following, the whole problematic and the method of resolution is presented.