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The global population is growing. The United Nations estimates the count to hit 8.5 billion in 2030, increasing the need for reliable infrastructure to house and transport citizens worldwide.1
Bridges of all kinds are part of this essential infrastructure, helping goods and people to move through previously inaccessible corridors. Bridge maintenance and repair to stay on top of unfolding problems and fix them before severe damage occurs are complex processes that various electronic sensors help facilitate.
The thesis of ongoing structural health monitoring (SHM) is that by the time periodic visual inspections find any problems, it might already be too late to forestall significant damage. SHM keeps a pulse on the varying conditions that might not be readily visible to the naked eye. SHM promises that it can catch problems early and avoid expensive repairs, road closures, and more. The cost of SHM is also not insignificant but is favored as an approach that keeps business humming and potentially saves lives.
Engineers field data from two fronts to keep bridges going: repairs and ongoing maintenance. Sensors play a role in each of these categories. Keeping bridges safe requires a systematic, ongoing analysis combined with detection if something does go wrong. In essence, the goal of bridge analysis is to prevent problems and troubleshoot when failures do occur. Advanced computing capabilities and artificial intelligence that feeds on data from sensors have also accelerated the move toward continuous monitoring.
To get a clear picture of bridge health, industry professionals need to measure a few different parameters. These include:
Cracking, tilt of decks and panels, water levels around bridges that might affect the foundation's strength on which bridges rest, settlement, vibration, and fatigue are all important considerations. The exact combination of parameters that engineers measure depends on the specific geographies of the area in which the bridge is situated. In rainy regions, for example, we might need more frequent monitoring of rain-driven corrosion, while bridges over rivers might need to pay attention to riverbed scouring that accompanies erosion.
The long list of potential sensors to use for measuring these different parameters might include:
Bridge engineering is moving toward making the routine maintenance aspects a more rigorous technology-driven solution. The growth of artificial intelligence—data over a period of time can inform us about potential breakdowns or find patterns of abnormal behavior—is leading to a revised approach toward sensor data collection and processing.
Contemporary bridge monitoring solutions use the Internet of Things (IoT) technology to frequently sample data and relay them to a data-processing model in the cloud. Bridge engineering borrows a page from manufacturing, creating a digital twin from all the data inputs to understand how the different parameters affect each other and how modifying one could affect the rest.
Sensors often feed on solar energy or might use batteries that only wake up periodically when needed, thereby conserving energy.
As infrastructure maintenance is a high-priority task for many state and local governments, they are working on using the most efficient solutions to get the job done right. Advanced sensors that measure various crucial parameters will continue to be an essential part of a technology-driven solution, both for ongoing monitoring and repairs as needed.
In the future, expect bridge engineering to continue to include advanced technologies such as machine learning and artificial intelligence as it increasingly embraces cloud-based IoT-driven monitoring solutions.
For more in-depth information on Bridge Monitoring Solutions, see the companion article Sensors for Bridge Monitoring.
1. United Nations. Accessed May 24, 2022. https://www.un.org/en/global-issues/population.
Poornima Apte is an engineer turned writer with B2B specialties in robotics, AI, cybersecurity, smart technologies and digital transformation. Find her on Twitter @booksnfreshair.
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