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  4. Adaptive fault diagnosis for simultaneous sensor faults in structural health monitoring systems
 
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Adaptive fault diagnosis for simultaneous sensor faults in structural health monitoring systems

Citation Link: https://doi.org/10.15480/882.4960
Publikationstyp
Journal Article
Date Issued
2023-02-22
Sprache
English
Author(s)
Al-Zuriqat, Thamer 
Chillón Geck, Carlos  
Dragos, Kosmas  
Smarsly, Kay  
Institut
Digitales und autonomes Bauen B-1  
TORE-DOI
10.15480/882.4960
TORE-URI
http://hdl.handle.net/11420/14907
Journal
Infrastructures  
Volume
8
Issue
3
Article Number
39
Citation
Infrastructures 8 (3): 39 (2023)
Publisher DOI
10.3390/infrastructures8030039
Scopus ID
2-s2.0-85151123989
Publisher
Multidisciplinary Digital Publishing Institute
Structural health monitoring (SHM) is a non-destructive testing method that supports the condition assessment and lifetime estimation of civil infrastructure. Sensor faults may result in the loss of valuable data and erroneous structural condition assessments and lifetime estimations, in the worst case with structural damage remaining undetected. As a result, the concepts of fault diagnosis (FD) have been increasingly adopted by the SHM community. However, most FD concepts for SHM consider only single-fault occurrence, which may oversimplify actual fault occurrences in real-world SHM systems. This paper presents an adaptive FD approach for SHM systems that addresses simultaneous faults occurring in multiple sensors. The adaptive FD approach encompasses fault detection, isolation, and accommodation, and it builds upon analytical redundancy, which uses correlated data from multiple sensors of an SHM system. Specifically, faults are detected using the predictive capabilities of artificial neural network (ANN) models that leverage correlations within sensor data. Upon defining time instances of fault occurrences in the sensor data, faults are isolated by analyzing the moving average of individual sensor data around the time instances. For fault accommodation, the ANN models are adapted by removing faulty sensors and by using sensor data prior to the occurrence of faults to produce virtual outputs that substitute the faulty sensor data. The proposed adaptive FD approach is validated via two tests using sensor data recorded by an SHM system installed on a railway bridge. The results demonstrate that the proposed approach is capable of ensuring the accuracy, reliability, and performance of real-world SHM systems, in which faults in multiple sensors occur simultaneously.
Subjects
structural health monitoring (SHM)
fault diagnosis (FD)
multiple sensor faults
simultaneous sensor faults
artificial neural network (ANN)
adaptive fault diagnosis
MLE@TUHH
DDC Class
600: Technik
620: Ingenieurwissenschaften
690: Hausbau, Bauhandwerk
720: Architektur
Funding Organisations
Deutsche Forschungsgemeinschaft (DFG)  
Bundesministerium für Digitales und Verkehr  
Bundesministerium für Bildung und Forschung (BMBF)  
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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