Review of methods used for outlier detection in structural health monitoring

Connor O'Higgins, D. Hester, W. K. Ao, P. McGetrick, D. Robinson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identification of outliers is a vital step in a large number of structural health monitoring systems. If the system is designed to detect the occurrence of damage, then outlier detection will most likely comprise a part of its methodology. The general procedure for damage detection can be described in the following way: firstly, establish a healthy baseline for the structure, based on measured data for example, and then any future monitoring data can be compared to this baseline to check if it shows normal behaviour. This process of determining whether or not the data falls within the parameters of the baseline can be categorised as outlier detection. Outlier detection is not only used at the final stage of damage detection, but also in the training of the baseline, as outliers at this stage of the process could mask the existence of damage in future data. In this paper, the effectiveness of various outlier detection methods are reviewed. Reviewed methods include the most commonly used in structural health monitoring (e.g. Minimum Covariance Determinant), as well as some that are more commonly found in econometrics. A selection of these methods are applied to real world frequency data obtained from a short span bridge over a period of 19 days. This study informs the design of structural health monitoring systems and aids in making a decision on the most appropriate outlier detection method to use for particular applications and circumstances.

Original languageEnglish
Title of host publication9th International Conference on Structural Health Monitoring of Intelligent Infrastructure
Subtitle of host publicationTransferring Research into Practice, SHMII 2019 - Conference Proceedings
EditorsGenda Chen, Sreenivas Alampalli
PublisherInternational Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII
Pages908-913
Number of pages6
ISBN (Electronic)9780000000002
Publication statusPublished - 2019
Event9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - St. Louis, United States
Duration: 04 Aug 201907 Aug 2019

Publication series

Name9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - Conference Proceedings
Volume2

Conference

Conference9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019
CountryUnited States
CitySt. Louis
Period04/08/201907/08/2019

Bibliographical note

Funding Information:
The authors acknowledge the support of DfI Roads and the EPSRC for their financial support through EPSRC grant EP/R009635/1.

Publisher Copyright:
Copyright © SHMII 2019. All rights reserved.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Building and Construction

Fingerprint Dive into the research topics of 'Review of methods used for outlier detection in structural health monitoring'. Together they form a unique fingerprint.

Cite this