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

• URL: http://arxiv.org/abs/2401.10355v1
• Date: Thu, 18 Jan 2024 19:48:53 GMT
• Title: Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals
• Authors: Maximilian Trapp and Can Bogoclu and Tamara Nestorovi\'c and Dirk Roos
• Abstract 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.
• Score: 0.9285295512807729
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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