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Identifiability based sensor configuration analysis for Bayesian structural identification

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conference contribution
posted on 2022-06-07, 14:38 authored by Andre JesusAndre Jesus, Y Zhu, K Koo, J Brownjohn, I Laory
When performing structural health monitoring, the design of an optimal sensor configuration aims at improving the effectiveness of structural identification (st-id) and anomaly detection while reducing costs/redundant data. Since this activity takes place when only simulated data is available, model uncertainties have a great impact on the results. This paper studies the application of a hybrid Bayesian methodology for optimal sensor configuration improvement of st-id. It exhibits a comprehensive formulation for uncertainty quantification, aided with multiple response Gaussian processes, and a reduced computational effort relatively to previous works. Information of the optimal sensor position, amount and diversity of data that should be collected, before the actual monitoring phase, can be obtained. An aluminium bridge scale model instrumented with strain gauges/thermocouples, and supported at one end with springs, whose stiffness have to be identified, is used as a case-study. The methodology is applied to a finite element model of the actual structure, and the optimal location of strain gauges is obtained. Validation is carried out by comparison of these results against a subsequent st-id of the bridge supports stiffness, when measurements are made available. Results show that: the used performance criterion is a reliable index of how accurate the identification is (identifiability); the computational effort of the method can be three times less than previous works; and even with poorly informative responses it is possible to design a reliable and cost-effective sensor configuration.

Funding

DTP 2016-2017 University of Warwick

Engineering and Physical Sciences Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings

Pages

883 - 892

Source

8th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2017)

Publisher

International Society for Structural Health Monitoring of Intelligent Infrastructure (SHMII)

Version

  • AM (Accepted Manuscript)

Rights holder

© International Society for Structural Health Monitoring of Intelligent Infrastructure

Publisher statement

This paper appears here with the permission of the publisher. This paper was accepted for publication in SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings and the definitive published version is available at https://www.proceedings.com/39899.html

Publication date

2018-08-31

Copyright date

2017

ISBN

9781925553055; 9781510864573

Language

  • en

Editor(s)

Tommy Chan; Saeed Mahini

Location

Brisbane, Australia

Event dates

5th December 2017 - 8th December 2017

Depositor

Dr Andre Jesus. Deposit date: 4 June 2022

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