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Evolutionary Computation Modelling for Structural Health Monitoring of Critical Infrastructure

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Abstract

Monitoring of critical infrastructure for Structural Health Monitoring (SHM) is vital for the detection of structural damage (cracks or voids) at an initial stage, thus increasing the structures’ serviceable life. The traditional methods of visual inspection to detect damages are time-consuming and less efficient. Sensor based Non-Destructive Techniques (S-NDTs) such as ground-penetration radar, acoustic emission, laser scanning, etc. for detection and analysis are extensively used to monitor structural health but are expensive and time-consuming. Recent advancements in Artificial Intelligence (AI) techniques such as Computer Vision (CV) assisted with Convolutional Neural Network (CNN), Machine Learning (ML) and Deep Learning (DL) in Structural Health Monitoring (SHM) provide more accurate data classification and damage detection systems. This paper provides a state-of-the-art review of the applications of AI-based techniques in SHM. A detailed study on vision data collection, processing techniques, and segmentation (feature, model, and pattern) is discussed, along with their limitations. The application of AI techniques for SHM to detect, isolate, and identify data anomalies, along with biomimetic algorithms are reviewed to assist in future research directions for life critical infrastructure monitoring.

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Acknowledgements

For this review, we are grateful for the resources provided by the Multiscale Simulation Research Center at Manipal University Jaipur.

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Authors and Affiliations

  1. Department of Civil Engineering, Manipal University Jaipur, Jaipur, India

    Charanjeet Singh Tumrate

  2. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, India

    Dinesh Kumar Saini

  3. School of Computer Science, University College Dublin, Dublin, Ireland

    Punit Gupta

  4. Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, India

    Dhaneshwar Mishra

  5. Multiscale Simulation Research Center, Manipal University Jaipur, Jaipur, India

    Charanjeet Singh Tumrate & Dhaneshwar Mishra

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Tumrate, C.S., Saini, D.K., Gupta, P. et al. Evolutionary Computation Modelling for Structural Health Monitoring of Critical Infrastructure. Arch Computat Methods Eng 30, 1479–1493 (2023). https://doi.org/10.1007/s11831-022-09845-1

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