Titlebook: Structural Health Monitoring Based on Data Science Techniques; Alexandre Cury,Diogo Ribeiro,Michael D. Todd Book 2022 The Editor(s) (if ap

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Real-Time Unsupervised Detection of Early Damage in Railway Bridges Using Traffic-Induced Responsesonses. To achieve this goal a hybrid combination of wavelets, PCA, and cluster analysis is implemented. Damage-sensitive features from train-induced dynamic responses are extracted and allow taking advantage not only of the repeatability of the loading, but also, of its large magnitude, thus enhanci

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Fault Diagnosis in Structural Health Monitoring Systems Using Signal Processing and Machine Learninnsor data into decisions. Faulty sensors may compromise the reliability of SHM systems, causing data corruption, data loss, and erroneous judgment of structural conditions. Fault diagnosis (FD) of SHM systems encompasses the detection, isolation, identification, and accommodation of sensor faults, a

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Predictive Monitoring of Large-Scale Engineering Assets Using Machine Learning Techniques and Reducous consequences in terms of fatalities, environmental pollution, and economic loss. To assess the state of damage of a complex structure, this paper proposes to fully characterize its behavior under multiple environmental and operational scenarios and compare new sensor measurements with the baseli

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Unsupervised Data-Driven Methods for Damage Identification in Discontinuous Media,or structural stability. Approaches combining nondestructive evaluation and finite element modeling have been successful in producing qualitative diagnoses for damage to existing structures. However, the real-world impact of such methods will hinge upon a reduced computational burden and improved ac