Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals

The lack of anomaly detection methods during mechanized tunnelling can cause financial loss and deficits in drilling time. On-site excavation requires hard obstacles to be recognized prior to drilling in order to avoid damaging the tunnel boring machine and to adjust the propagation velocity. The ef...

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Bibliographic Details
Published inarXiv.org
Main Authors Trapp, Maximilian, Bogoclu, Can, Nestorović, Tamara, Roos, Dirk
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 18.01.2024
Subjects
Algorithms
Anomalies
Boring machines
Computer Science - Learning
Drilling machines (tools)
Earthquake damage
Machine learning
Optimization
Parameter estimation
Physics - Applied Physics
Propagation velocity
Tunnel construction
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Summary:The lack of anomaly detection methods during mechanized tunnelling can cause financial loss and deficits in drilling time. On-site excavation requires hard obstacles to be recognized prior to drilling in order to avoid damaging the tunnel boring machine and to adjust the propagation velocity. The efficiency of the structural anomaly detection can be increased with intelligent optimization techniques and machine learning. In this research, the anomaly in a simple structure is detected by comparing the experimental measurements of the structural vibrations with numerical simulations using parameter estimation methods.
ISSN:2331-8422
DOI:10.48550/arxiv.2401.10355