Overview of SHM
SHM is based on the continuous, real-time assessment of integrity by advanced sensors, data collection, and analysis technologies. It plays a critical role in ascertaining changes or anomalies in materials or structural behavior that might indicate degradation. By doing this, it plays a significant role in civil engineering today to keep structures safe and durable, and any maintenance is scheduled so that cost is minimized. (Farrar & Worden 2013; Rojas et al. 2021) As the infrastructure is getting older and the loads are increasing, SHM becomes indispensable in view of risk mitigation and proactive asset management of different structures like bridges, buildings, tunnels, and dams. Aktan et al., 2024.
SHM can give way to real-time monitoring and predictive maintenance, as it is now integrated with digital technologies such as IoT and artificial intelligence. In general, SHM-based decision-making provides more actionable data for early detection and intervention in various critical infrastructures, such as long-span bridges and tall buildings.
History and Evolution of SHM
The earliest roots of SHM are from NDT and visual inspections during the first half of the 20th century. Naturally, these techniques were really just periodic in nature and highly subjective, depending on human judgment. These techniques naturally evolved during the mid-20th century with advances in technologies like ultrasonic and radiographic testing. It was only during the late 20th century that SHM began to have the dramatic impact brought about by the digital revolution. Today, SHM systems leverage real-time data from advanced sensors, such as fiber optics, MEMS, and accelerometers integrated with data analytics, cloud computing, and artificial intelligence (Xue & Tan, 2022; Zhu et al., 2020; Shahriaree et al., 2021).
Another major milestone in the evolution of SHM has been the development of wireless sensor networks capable of enabling monitoring over large areas remotely. These and similar kinds of advances have brought the civil engineer closer to understanding how continuous variations occur in complex structures and gather data regarding stress, vibration, and environmental factors without intrusive ocular inspections (Gao et al., 2021; Yang et al., 2021). In this respect, state-of-the-art SHM systems are increasingly recognized as an enabler for “smart infrastructure,” offering advanced data-driven asset management and lifecycle cost optimization opportunities, according to Lee et al. (2022) and Liu et al. (2022).
Applications of SHM
SHM has widespread applications across multiple sectors of civil engineering. Below are key examples:
- Bridges: In particular, large-scale bridges, which are often expected to receive time-dependent dynamic loading with increasing volumes of traffic and variations in weather conditions, are commonly monitored using SHM techniques. Advanced state-of-the-art SHM systems on structures such as the Queensferry Crossing in Scotland have provided immediate feedback associated with vibrations, strain, and thermal variations. Enabling these immediately allows the owner to detect any anomalies arising much earlier than in the past (Aktan et al., 2024).
- High-rise Buildings: In the case of high-rise structures, SHM is done to reinforce their structural stability by observing its responses to a wind load, seismic events, and even temperature changes. An installed SHM system in Dubai’s Burj Khalifa, for example, could monitor building sway and vibration for both safety and comfort.
- Tunnels and Dams: Tunnels are also geotechnical structures that are subjected to ground conditions in most cases, whereas SHM systems observe any ground movement or structural failure that might take place on these structures. Other structures that are extremely important and are usually exposed to water pressure and natural environmental conditions include dams; SHM systems installed on them also exist. For instance, the Three Gorges Dam includes SHM to monitor deformation and seepage in real time to guarantee operational safety.
- Offshore Structures: Other safety-critical applications include the monitoring of structural integrity and stability of offshore wind turbines and oil platforms under unsteady wave, wind, and current dynamic loading. The SHM systems detect structural fatigue, foundation integrity, and corrosion-all important data for maintenance planning and reducing costly downtimes (Fang et al., 2023).
- Heritage Structures: SHM plays an essential role in the maintenance of heritage structures, most of which are aging and require continuous monitoring. As an example, historical building monitoring in earthquake-prone areas is one of those cases where SHM protects the cultural heritage and reduces risks accordingly (Alvarez et al., 2021).
The Effect of SHM on the Construction Industry
The construction industry has been undergoing a paradigm shift with the integration of SHM technologies into asset management. SHM enables continual, real-time capture of information pertaining to the performance of structures, enhancing the safety and durability of the structures. This helps in preventing catastrophic failures, besides making sure resources for maintenance are optimized to attain minimum life-cycle cost (Rojas et al., 2021).
SHM has been transformative, especially for predictive maintenance. Instead of fixed schedules of maintenance, SHM allows for condition-based maintenance in a very efficient and cost-effective manner. By monitoring the fatigue life of a bridge, for example, operators can predict when repairs will be required, thereby avoiding unnecessary disruptions and minimizing costs
Furthermore, SHM aligns with the growing sustainability goals of the construction industry by reducing material usage and improving the long-term resilience of structures. In doing so, it supports global efforts to reduce the carbon footprint of construction activities.
Conclusion
SHM is a serious technological stride in construction, purposed for the real-time data-driven approach in managing infrastructure health. From its inception through traditional inspection techniques to today’s advanced digital solutions, SHM has evolved into a crucial tool for civil engineers in ensuring safety, performance, and longevity in infrastructure. It spans from bridge applications to skyscrapers, tunnels, and even dams-SHM continuously shapes the future for safe and smart infrastructure management. SHM will contribute further in making infrastructure resilient, cost-effective, and sustainable worldwide with advances in SHM technologies.
References
- Aktan, E., Bartoli, I., Glišić, B., & Rainieri, C. (2024). Lessons from bridge structural health monitoring (SHM) and their implications for the development of cyber-physical systems. Infrastructures, 9(2), 30. https://doi.org/10.3390/infrastructures9020030
- Alvarez, J., Camacho, R., & López, A. (2021). Structural health monitoring of cultural heritage: Methodologies and case studies. Sensors, 21(20), 6794. https://doi.org/10.3390/s21206794
- Farrar, C. R., & Worden, K. (2013). An introduction to structural health monitoring. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1851), 303-315. https://doi.org/10.1098/rsta.2006.1928
- Fang, X., Qiu, J., & Zhang, H. (2023). A comprehensive study on structural health monitoring of offshore wind turbines: Current status and future trends. Renewable and Sustainable Energy Reviews, 171, 112885. https://doi.org/10.1016/j.rser.2022.112885
- Lynch, J. P., & Loh, K. J. (2006). A summary review of wireless sensors and sensor networks for structural health monitoring. Shock and Vibration Digest, 38(2), 91-130. https://doi.org/10.1177/0583102406061499
- Ou, J., & Li, H. (2010). Structural health monitoring in mainland China: Review and future trends. Structural Health Monitoring, 9(3), 219-231. https://doi.org/10.1177/1475921710365269
- Shahriaree, N., Emamgholizadeh, S., & Jaafari, A. (2021). A comprehensive review of wireless sensor networks for structural health monitoring: Current status and future directions. Sensors, 21(15), 5198. https://doi.org/10.3390/s21155198