Structural Health Monitoring for Civil Engineering Infrastructure

Authors

  • Ankit Negi

DOI:

https://doi.org/10.17762/msea.v70i1.2527

Abstract

Structural health monitoring (SHM) plays a vital role in ensuring the integrity, safety, and reliability of civil engineering infrastructure. With the increasing complexity and aging of structures, the need for effective monitoring systems has become paramount. This abstract presents an overview of the field of structural health monitoring, highlighting its significance in civil engineering and exploring various techniques and technologies used for monitoring the health of infrastructure.The objective of structural health monitoring is to detect, assess, and predict the condition of structures in real-time, enabling proactive maintenance and minimizing the risk of catastrophic failures. Traditional inspection methods, such as visual inspection, have limitations in terms of cost, accuracy, and coverage. SHM provides continuous and automated monitoring, enabling the collection of data from various sensors installed on the structure. These sensors capture data related to structural behaviour, environmental conditions, and loading conditions, among others.This abstract delves into the different types of sensors employed in SHM for civil engineering infrastructure. These sensors include strain gauges, accelerometers, displacement transducers, temperature sensors, and corrosion sensors. Strain gauges measure the strain or deformation experienced by the structure, while accelerometers detect vibrations and dynamic responses. Displacement transducers monitor the movement or displacement of specific points, providing valuable information about structural deformations. Temperature sensors help in understanding the effect of temperature variations on the structural behaviour. Corrosion sensors detect the presence of corrosion, a significant issue in infrastructure deterioration.

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Published

2021-01-31

How to Cite

Negi, A. . (2021). Structural Health Monitoring for Civil Engineering Infrastructure. Mathematical Statistician and Engineering Applications, 70(1), 698–705. https://doi.org/10.17762/msea.v70i1.2527

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Section

Articles