{"title":"A STATE-PARAMETER ESTIMATION IN TWO ENGINEERING DOMAINS: AN EXTENDED KALMAN FILTER APPROACH","authors":"L. Cot, S. Déjean, Carole Saudejaud","doi":"10.12783/shm2021/36286","DOIUrl":null,"url":null,"abstract":"This paper intends to present a synthesis of works based on the study of the behavior of the Kalman filters in two different domains. The first area is dedicated to the flocculation process occurring in water treatment. The second one covers aircraft structural damage based on SHM approach. The general methodology consists in modeling a state-parameter observer to perform estimations using the joint EKF. The robustness and efficiency of the Kalman filters is addressed in order to allow a cross-fertilization in the two area. Model propagation and accurate prognostics are therefore allowed due to the improvement of model parameter knowledge. In the context of the flocculation, the prediction of the time evolution of the characteristic diameters is much more efficient than QMOM. For fatigue damage prognostic, the best initial conditions leading to accurate estimation are highlighted according to materials. Whatever the problem is, the estimation error magnitude is known.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th International Workshop on Structural Health Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12783/shm2021/36286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper intends to present a synthesis of works based on the study of the behavior of the Kalman filters in two different domains. The first area is dedicated to the flocculation process occurring in water treatment. The second one covers aircraft structural damage based on SHM approach. The general methodology consists in modeling a state-parameter observer to perform estimations using the joint EKF. The robustness and efficiency of the Kalman filters is addressed in order to allow a cross-fertilization in the two area. Model propagation and accurate prognostics are therefore allowed due to the improvement of model parameter knowledge. In the context of the flocculation, the prediction of the time evolution of the characteristic diameters is much more efficient than QMOM. For fatigue damage prognostic, the best initial conditions leading to accurate estimation are highlighted according to materials. Whatever the problem is, the estimation error magnitude is known.