Towards Population-Based Structural Health Monitoring, Part I: Homogeneous Populations and Forms

• Published in: Model Validation and Uncertainty Quantification, Volume 3 pp. 287 - 302
• Main Authors: Bull, Lawerence A., Gardner, Paul A., Gosliga, Julian, Dervilis, Nikolaos, Papatheou, Evangelos, Maguire, Andrew E., Campos, Carles, Rogers, Timothy J., Cross, Elizabeth J., Worden, Keith
• Format: Book Chapter
• Language: English
• Published: Switzerland River Publishers 2020; Springer International Publishing AG; Springer International Publishing
• Edition: 1
• Series: Conference Proceedings of the Society for Experimental Mechanics Series
• Subjects: Homogeneous populations; Population-based structural health monitoring; Homogeneous populations; Population-based structural health monitoring
• ISBN: 3030476375; 3030487784; 9783030487782; 9783030476373
• ISSN: 2191-5644; 2191-5652
• DOI: 10.1007/978-3-030-47638-0_32

Data-driven models in Structural Health Monitoring (SHM) generally require comprehensive datasets, recorded from systems in operation, which are rarely available. One potential solution to this problem, considers that information might be transferred, in some sense, between similar systems. As a result, a population-based approach to SHM suggests methods to both model and transfer this valuable information, by considering different groups of structures as populations. Specifically, in this work, a method is proposed to model a population of nominally-identical systems, where (complete) datasets are only available from a subset of members. The framework attempts to build a general model, referred to as the population form, which can be used to make predictions across a group of homogeneous systems. First, the form is demonstrated through applications to a simulated population - with a single experimental (test-rig) member; secondly, the form is applied to data recorded from a group of operational wind turbines.