A DATA DRIVEN BASED METHODOLOGY FOR STURCTURAL HEALTH MONITORING WITH DISTRIBUTED OPTICAL FIBRE SENSORS

Zhangquan Shen, Yiding Liu, Anubhav Singh, Wenhao Li, Tianyu Chen, Shijun Guo, Darren J. Hughes

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

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Abstract

Structural health monitoring (SHM) is a means for maintaining structural integrity, safety and reliability by analysing various structural responses (i.e., mechanical signals) to pinpoint the anomalies of the structures due to damage. It is not an easy task to filter the noise and fluctuation of mechanical signals to successful find the damage-induced anomalies, but it might be achieved by machine learning algorithms. However, the successful implementation of a machine learning requires a large amount of training data, which is always available. In this work, a novel machine learning (ML) model, combining k-nearest neighbors kernel (KNN) and deep neural network (DNN), was proposed that can be trained by insufficient/incomplete SHM data. In addition, the damage states can be identified by Kernel Principle Component Analysis (KPCA). To demonstrate the accuracy of this model, training and validation data were taken from the strains of the braided composite beam under progressive three-point bending. The strain signals were measured by embedded distributed optical fibre sensors (DOFS). The prediction of the proposed novel ML model demonstrates a good agreement with the experimental observations for validation, which provides a novel approach for sufficient/incomplete training data. © 2023 International Committee on Composite Materials. All rights reserved.
Original languageEnglish
Title of host publicationProceedings of the 2023 ICCM International Conferences on Composite Materials
EditorsBrian Falzon, Conor McCarthy
Place of PublicationBelfast
PublisherQueen's University Belfast
Number of pages18
Publication statusPublished - 4 Aug 2023
Event23rd International Conference on Composite Materials - Belfast, United Kingdom
Duration: 30 Jul 20234 Aug 2023
Conference number: 23
https://www.iccm-central.org/Proceedings/ICCM23proceedings/index.htm

Conference

Conference23rd International Conference on Composite Materials
Abbreviated titleICCM 2023
Country/TerritoryUnited Kingdom
CityBelfast
Period30/07/234/08/23
Internet address

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