期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 148, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.107141
关键词
Population-based structural health monitoring; Pattern recognition; Wind turbine monitoring
资金
- UK Engineering and Physical Sciences Research Council (EPSRC) [EP/R003645/1, EP/R004900/1, EP/R006768/1, EP/S001565/1]
- EPSRC [EP/R003645/1, EP/R006768/1] Funding Source: UKRI
This study introduces a population-based approach to Structural Health Monitoring (SHM) which aims to model and transfer missing information by considering data collected from groups of similar structures. The strategy defines a general model, referred to as the population form, to monitor homogeneous group systems.
In Structural Health Monitoring (SHM), measured data that correspond to an extensive set of operational and damage conditions (for a given structure) are rarely available. One potential solution considers that information might be transferred, in some sense, between similar systems. A population-based approach to SHM looks to both model and transfer this missing information, by considering data collected from groups of similar structures. Specifically, in this work, a framework is proposed to model a population of nominally-identical systems, such that (complete) datasets are only available from a subset of members. The SHM strategy defines a general model, referred to as the population form, which is used to monitor a homogeneous group of systems. First, the framework is demonstrated through applications to a simulated population, with one experimental (test-rig) member; the form is then adapted and applied to signals recorded from an operational wind farm. (C) 2020 The Author(s). Published by Elsevier Ltd.
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