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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65895
Volume:
10 |
7 |
Jul 2026
Pages:
1-13
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of Civil Engineering
Shri Venkateshwara University, Gajraula (up)
Department of Civil Engineering
Shri Venkateshwara University, Gajraula (UP) 244236
Department of Civil Engineering
Shri Venkateshwara University, Gajraula (up)
Department of Civil Engineering
Shri Venkateshwara University, Gajraula (up)
Department of Civil Engineering
Shri Venkateshwara University, Gajraula (up)
Department of Civil Engineering
Shri Venkateshwara University, Gajraula (up)
Structural Health Monitoring (SHM) is an essential approach for assessing the safety, performance, and durability of civil infrastructure. It enables early detection of structural damage, helping to prevent failures and reduce maintenance costs. This dissertation presents the fundamentals and application of SHM, focusing on sensor-based monitoring and vibration analysis techniques. Various sensing methods, including accelerometers and strain gauges, are discussed along with data analysis approaches used to identify structural anomalies. A case study is included to demonstrate the practical implementation of SHM in monitoring structural behavior under operational conditions. The study highlights the effectiveness of SHM in improving reliability and supporting informed maintenance decisions.
KEYWORDS
In the dissertation, it is established that SHM is a significant development in the field of civil engineering since it changes the periodic and reactive scrutiny of structures to a form of continuous, information-driven to proactive assessments. Contrary to the traditional methods usually used to determine the damage after the deterioration is seen, SHM enables the engineers to monitor the structural behaviour over time and identify the abnormal behaviour at an earlier stage. This renders it useful in bridges, buildings and other structure systems that are subjected to the effects of aging, repetitive loading and environmental influences. The paper also finds that SHM is not just an important monitoring technology but also a decision-support structure. SHM enhances the realization of structural condition and condition-based maintenance by connecting the process of sensing, data interpretation, and maintenance planning. This way, it helps in the infrastructure safety, service life extension and more efficient control of assets. Nevertheless, the dissertation also concludes that SHM also contains limitations. Structural response can be influenced by environmental and operational variability and result in hard interpretation of damage. Moreover, there is a significant gap between research development and the routine fields implementation, which is still a significant problem. Its high price, non-standardization, and difficulty in interpreting the data, as well as the insufficient institutional preparedness, still limit its broader application, particularly in developing nations.
Aktan, E., Bartoli, I., Glišić, B. and Rainieri, C., 2024. Lessons from bridge structural health monitoring (SHM) and their implications for the development of cyber-physical systems. Infrastructures, 9(2), p.30.Bhandari, R., 2020. Case study of structural health monitoring in India and its benefits. Journal of Civil Engineering, Science and Technology, 11(1), pp.1-7.Civera, M. and Surace, C., 2022. Non-destructive techniques for the condition and structural health monitoring of wind turbines: A literature review of the last 20 years. Sensors, 22(4), p.1627.Figueiredo, E. and Brownjohn, J., 2022. Three decades of statistical pattern recognition paradigm for SHM of bridges. Structural Health Monitoring, 21(6), pp.3018-3054.Ghaedi, K., Gordan, M., Ismail, Z., Hashim, H. and Talebkhah, M., 2021. A literature review on the development of remote sensing in damage detection of civil structures. Journal of Engineering Research and Reports, 20(10), pp.39-56. Gharehbaghi, V.R., Noroozinejad Farsangi, E., Noori, M., Yang, T.Y., Li, S., Nguyen, A., Málaga-Chuquitaype, C., Gardoni, P. and Mirjalili, S., 2022. A critical review on structural health monitoring: Definitions, methods, and perspectives. Archives of computational methods in engineering, 29(4), pp.2209-2235.Hassani, S. and Dackermann, U., 2023. A systematic review of advanced sensor technologies for non-destructive testing and structural health monitoring. Sensors, 23(4), p.2204.Hassani, S., Dackermann, U., Mousavi, M. and Li, J., 2024. A systematic review of data fusion techniques for optimized structural health monitoring. Information Fusion, 103, p.102136.
Publication Date
7/7/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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