Foundations of population-based SHM, Part I: Homogeneous populations and forms

被引：87

作者：

Bull, L. A. ^{[1
]}

Gardner, P. A. ^{[1
]}

Gosliga, J. ^{[1
]}

Rogers, T. J. ^{[1
]}

Dervilis, N. ^{[1
]}

Cross, E. J. ^{[1
]}

Papatheou, E. ^{[2
]}

Maguire, A. E. ^{[3
]}

Campos, C. ^{[3
]}

Worden, K. ^{[1
]}

机构：

[1] Univ Sheffield, Dept Mech Engn, Dynam Res Grp, Mappin St, Sheffield S1 3JD, S Yorkshire, England

[2] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England

[3] New Renewables, Vattenfall Res & Dev, Tun Bldg,Holyrood Rd, Edinburgh EH8 8AE, Midlothian, Scotland

来源：

MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2021年 / 148卷

基金：

英国工程与自然科学研究理事会;

关键词：

Population-based structural health monitoring; Pattern recognition; Wind turbine monitoring;

D O I：

10.1016/j.ymssp.2020.107141

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

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.

引用

页数：19

共 31 条

[1]

[Anonymous], 2007, P INT C FIELD SERV R

[2] Variational Inference: A Review for Statisticians [J].