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.
|Title of host publication||9th International Conference on Structural Health Monitoring of Intelligent Infrastructure|
|Subtitle of host publication||Transferring Research into Practice, SHMII 2019 - Conference Proceedings|
|Editors||Genda Chen, Sreenivas Alampalli|
|Publisher||International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII|
|Number of pages||6|
|Publication status||Published - 2019|
|Event||9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - St. Louis, United States|
Duration: 04 Aug 2019 → 07 Aug 2019
|Name||9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - Conference Proceedings|
|Conference||9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019|
|Period||04/08/2019 → 07/08/2019|
Bibliographical noteFunding Information:
The authors acknowledge the support of DfI Roads and the EPSRC for their financial support through EPSRC grant EP/R009635/1.
Copyright © SHMII 2019. All rights reserved.
Copyright 2020 Elsevier B.V., All rights reserved.
ASJC Scopus subject areas
- Artificial Intelligence
- Civil and Structural Engineering
- Building and Construction
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Development of a Minimal Information Data - modelling approach for the monitoring of short and medium span bridgesAuthor: O'Higgins, C., Jul 2022
Supervisor: McGetrick, P. (Supervisor), Robinson, D. (Supervisor) & Hester, D. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of PhilosophyFile