Large and expensive structures, such as tunnels, bridges, and pipelines, need regular, cost-effective monitoring of their structural integrity. This ensures safety and reliability.
Structural health monitoring (SHM) plays a critical role here [1], because it takes a proactive approach to maintenance and monitoring, rather than waiting for damage to happen and then repairing it. This proactive method can save money and prevent unplanned downtime of the structure.
But the need for reliable and accurate SHM installation in major infrastructure is often ignored for reasons such as cost, confusion over which sensors to use, and difficulty interpreting strain data. This becomes a problem when strain-induced structural damage happens. And it does happen regularly, since civil infrastructure is exposed to constant loads and environmental agents that cause wear and degradation over time.
For instance, bridges suffer from structural deterioration due to rising traffic demands, as well as climate changes and adverse weather conditions [2-3]. Poor construction methods, seismic activity, and nearby construction also play a part [4]. And without consistent monitoring, malfunctions and structural issues cannot be detected or predicted, resulting in disasters. In fact, in the United States, every bridge is required to undergo a visual inspection once every two years to help prevent such structural issues from cropping up [5].
But according to the ASCE 2017 Infrastructure Report Card, nearly 10% of bridges in the United States have some sort of structural problem, which makes them vulnerable [6]. And in Canada, almost one third of the approximately 75,000 highway bridges have structural deficiencies [7]. Failure to identify and deal with these structural deficiencies can result in high maintenance costs, shut down of local infrastructure, and −worst-case scenario – structural collapse and fatalities. As a result, there is a huge market for technology that helps to easily and cost-effectively monitor infrastructural wear and tear [8].