James Wilson, Graeme Manson, Paul Gardner, Robert J Barthorpe
{"title":"Hierarchical verification and validation in a forward model-driven structural health monitoring strategy","authors":"James Wilson, Graeme Manson, Paul Gardner, Robert J Barthorpe","doi":"10.1177/14759217231206698","DOIUrl":null,"url":null,"abstract":"This paper presents a demonstrative application of a forward model-driven approach to structural health monitoring (SHM), incorporating hierarchical validation methods. A key tenet of the approach is that an SHM system can be constructed that is capable of diagnosing damage at the full system level, without full system damage-state data having been used in its development; achieving this would be highly impactful as the system-level damage state data is generally not feasible to acquire (previous SHM methods such as data-driven SHM have been hindered by their dependence on these data). This is achieved by carrying out validation activities on the damage model at the subassembly level of the structure. The particular focus of the present paper is on damage detection and assessment, although the approach offers a natural basis for extension to other damage identification activities such as damage location and prognosis. The present study focuses on two of the key elements of the model-driven approach: validation of the predictive substructure models and their application in the assembled model. The ideas discussed are demonstrated in a case study based on a laboratory-scale truss bridge structure.","PeriodicalId":51184,"journal":{"name":"Structural Health Monitoring-An International Journal","volume":null,"pages":null},"PeriodicalIF":5.7000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Health Monitoring-An International Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/14759217231206698","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a demonstrative application of a forward model-driven approach to structural health monitoring (SHM), incorporating hierarchical validation methods. A key tenet of the approach is that an SHM system can be constructed that is capable of diagnosing damage at the full system level, without full system damage-state data having been used in its development; achieving this would be highly impactful as the system-level damage state data is generally not feasible to acquire (previous SHM methods such as data-driven SHM have been hindered by their dependence on these data). This is achieved by carrying out validation activities on the damage model at the subassembly level of the structure. The particular focus of the present paper is on damage detection and assessment, although the approach offers a natural basis for extension to other damage identification activities such as damage location and prognosis. The present study focuses on two of the key elements of the model-driven approach: validation of the predictive substructure models and their application in the assembled model. The ideas discussed are demonstrated in a case study based on a laboratory-scale truss bridge structure.
期刊介绍:
Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.