{"title":"Damage Identification Using Static and Dynamic Responses Based on Topology Optimization and Lasso Regularization","authors":"Ryo Sugai, A. Saito, H. Saomoto","doi":"10.1115/detc2020-22279","DOIUrl":null,"url":null,"abstract":"\n This paper presents a damage identification method based on topology optimization and Lasso regularization. The method uses static displacements or dynamic responses to identify damages of structures. The method has the potential to identify damages with high fidelity, in comparison with ordinary damage identification method based on optimization with parameterized geometry of the damages. However, it is difficult to precisely detect damage using topology optimization due mostly to the large number of design variables. Therefore, supposing that the damage is sufficiently small, we propose a method adding Lasso regularization to the objective functions to suppress active design variables during topology optimization process. To verify the effectiveness of the proposed method, we conducted a set of numerical experiments for static and dynamic problems. We have succeeded in suppressing active design variables and delete artificially generated damages and the location and shape of damage have been precisely identified.","PeriodicalId":398186,"journal":{"name":"Volume 7: 32nd Conference on Mechanical Vibration and Noise (VIB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 7: 32nd Conference on Mechanical Vibration and Noise (VIB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2020-22279","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 paper presents a damage identification method based on topology optimization and Lasso regularization. The method uses static displacements or dynamic responses to identify damages of structures. The method has the potential to identify damages with high fidelity, in comparison with ordinary damage identification method based on optimization with parameterized geometry of the damages. However, it is difficult to precisely detect damage using topology optimization due mostly to the large number of design variables. Therefore, supposing that the damage is sufficiently small, we propose a method adding Lasso regularization to the objective functions to suppress active design variables during topology optimization process. To verify the effectiveness of the proposed method, we conducted a set of numerical experiments for static and dynamic problems. We have succeeded in suppressing active design variables and delete artificially generated damages and the location and shape of damage have been precisely identified.