Computational Algorithms for Structural Health Monitoring Systems

Dr. Amina Khalid

doi:10.71465/ajem689

journal article Apr 30, 2021

Computational Algorithms for Structural Health Monitoring Systems

Dr. Amina Khalid

American Journal Of Engineering Mathematics Vol. 2 No. 2 pp. 11-16 · International Study Counselor

View at Publisher Save 10.71465/ajem689

Abstract

Structural Health Monitoring (SHM) systems play a critical role in ensuring the safety, reliability, and longevity of civil infrastructure. This article reviews advanced computational algorithms deployed in SHM systems for effective damage detection, diagnosis, and prognosis of structural components. Various algorithmic approaches, including machine learning, signal processing, and model-based methods, are discussed with their applications in real-time monitoring frameworks. Emphasis is placed on the integration of data-driven and physics-based models to enhance accuracy and reduce false positives. Challenges related to sensor noise, data fusion, and computational efficiency are also highlighted. Finally, future research directions are proposed to further optimize SHM algorithms for smart infrastructure.

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Published: Apr 30, 2021
Vol/Issue: 2(2)
Pages: 11-16

Authors

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Dr. Amina Khalid

Cite This Article

Dr. Amina Khalid (2021). Computational Algorithms for Structural Health Monitoring Systems. American Journal Of Engineering Mathematics, 2(2), 11-16. https://doi.org/10.71465/ajem689

Computational Algorithms for Structural Health Monitoring Systems

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