Structural health monitoring (SHM) is the process of observing and analyzing a system over time, utilizing periodic sampling response measurements to track changes in the material and geometric attributes of engineering structures such as bridges and buildings.
Structural health monitoring is vital for both economic profit and public safety. Sudden structural collapses can endanger lives and property. The primary goal of structural health monitoring is to provide quantifiable performance data to the appropriate authorities.
Structural health monitoring can be useful throughout the following stages of construction:
Critical structures such as bridges, tunnels, dams, and wind turbines are closely monitored since they are essential components of the national infrastructure.
Data collection refers to the number and kind of sensors, sensor activation, and data storage systems. The behavior of the structure should be unaffected by sensor location. This may be achieved by arranging the placement of wires, boxes, and other components during the design stage.
Sensors must be appropriate and durable enough to fulfill their function for a set amount of time. Each sensor may examine a specific component of the structure. They assess strain, deflection, rotation, temperature, corrosion, prestressing, and other characteristics.
Data can be delivered by a wire, which is common and affordable but may not be practical for large structures. Wireless transmission, while suitable for large structures, is slower and more expensive than traditional connections. Telephone lines are another way to transfer data from the site to the offshore offices. These data transfer systems reduce the need for field visits to collect and deliver data.
After the data has been transferred, digital processing is done to eliminate any unwanted effects, such as noises. It should be finished before the data is saved. Digital processing will make data interpretation simpler, faster, and more precise.
The processed data can be retained for a long time and retrieved later for further analysis and interpretation.
Converting abstract data into practical information regarding a structure's state and load response. As a result, the final data supplied by structural health monitoring should be complete and tangible, allowing engineers to make sound and informed judgments.
The diagnostic technique is defined by the structure type, sensor position and type, monitoring purpose, and structural reaction being studied.
Sensor technology is a key area of structural testing and monitoring research. SHM systems use various sensors, including strain gages, vibration sensors, and displacement sensors, to track structure stresses and movement. Emerging technologies like non-destructive testing and fiber-optic technology are also being used. Structural engineers benefit from systems that can adapt to multiple measurement types and technologies, be modular, and be scalable for lab design, short-term measurements, and field deployment.
Continuous monitoring of real-time structural performance data is developing as an essential technique for the long-term maintenance of bridges, buildings, stadiums, and other major structures. These applications need robust, intelligent data collecting systems that can run reliably in distant, unattended areas without losing measurement performance or adaptability in order to give dependable, correct sensor data.
Continuous, long-term monitoring applications necessitate a system that can function autonomously for extended periods of time. This necessitates a real-time embedded system that can collect sensor data, log it locally, and periodically transfer it to a host system. The system's ability to function independently and unattended safeguards vital sensor data from network disruptions or PC system failures.
Monitoring bridges requires remote communication capabilities such as Wi-Fi, cellular data, specialized long-range radios, and satellite communications. CompactRIO (see https://www.ni.com/en/shop/compactrio.html) facilitates integration with third-party devices and modems by including libraries for TCP/IP, UDP, Modbus/TCP, and serial protocols, as well as built-in servers for web surfing and internet access.
Monitoring the health of buildings may need a large number of sensors distributed across a large area. A distributed measurement system that uses several networked data collecting devices, each coupled to a cluster of sensors, can drastically reduce the amount of sensor cable and make installation easier. However, because most health monitoring systems require a reliable, system-wide time reference, distributed systems must be able to accurately and consistently synchronize sensor results throughout the whole structure. Most communication networks lack such synchronization capabilities; however, more contemporary systems can use GPS or new deterministic networking technologies to achieve system-wide synchronization.
Software is a critical component of SHM systems. When performing a portable structural test or developing a long-term monitoring system, consider your software application needs for inline and offline data analysis, ease of use, and data postprocessing and administration.
Graphical programming, a new approach for application development, significantly reduces the learning curve by employing more intuitive design notations than text-based coding. The tools and functions are available through interactive palettes, dialogs, menus, and hundreds of Vis-style function blocks. Drag and drop these Vis onto a diagram to specify your application's functionality. This point-and-click approach shortens the time necessary to get from basic setup to final outcome.
Three essential SHM application processes are data preparation, numerical approaches and algorithms for data analysis, and open- and closed-loop simulations to test models against real-world data.
For almost 30 years, engineers and scientists have created technical data using NI hardware and software, with little care for what happens to the data thereafter. The reality is that data may be expensive, particularly for structural and seismic applications. In structural and seismic monitoring, the transitory event that must be captured is difficult, if not impossible, to recreate. To solve this issue, NI provides a three-stage data management solution that combines flexible and organized file storage, powerful search capabilities, and an interactive postprocessing environment.
LiDAR's applications in SHM are numerous. Bridge monitoring can detect structural deformations, displacement, and vibration of load-bearing components. For building inspections, it detects settlement, tilt, and facade damage. Dam monitoring uses LiDAR to identify changes or fissures that may indicate a failure. Tunnel structural health is measured using LiDAR, which detects fractures and deformations. Accurate 3D modeling and the detection of structural changes over time also assist to conserve historic sites.
The advantages of LiDAR include its high precision and accuracy, non-destructive nature, efficiency in scanning large buildings quickly, and the availability of complete data via exact 3D models. However, issues include the computational intensity of data processing, meteorological conditions such as fog and rain that degrade performance, and the high initial cost of equipment and software.
In the future, LiDAR technology is anticipated to be merged with other technologies, including UAVs, AI, and machine learning, to improve data analysis and damage prediction. Real-time data processing advancements will enable continuous monitoring and rapid response to identified changes. Furthermore, as automated inspection technologies advance, routine infrastructure monitoring will become more efficient. Thus, LiDAR is revolutionizing structural health monitoring by delivering precise and accurate data required for the repair and preservation of critical infrastructure.
OPSIS software was created to tackle the obstacles previously mentioned. The concept at its heart is to execute operations on the raw data given by LiDAR to produce a substantially smaller data collection.
To guarantee that the findings received from analyzing this sub-dataset are identical to those acquired from assessing the original, the processes involved must retain the spatial information included within the input data.
OPSIS monitors deformations or displacements in scanned objects, processes subsequent point clouds, and displays a linear diagram of each grid cell's deformation history.
OPSIS features include unlimited point cloud comparison, full surface deformation maps, time-displacement plots, time-lapse animation, customizable projection templates, multiple templates, scalable graphs, custom color scales, warning levels, export options, OEM noise filtering, and fast import and read process.
OPSIS may be used to monitor a variety of structures, including roads, airport runways, nuclear power plants, tall chimneys, buildings, hydropower stations, open pits, oil tanks, high-rise buildings, tunnels, mines, and bridges.
The test categories for the structural health monitoring system are as follows:
Structural Health Monitoring is no doubt beneficial to your building lifecycle assessment. With benefits like improved understanding and great cost savings on a building's structure, one should definitely opt for SHM if project stakes are quite high. However, it does come with challenges as well.
Monitoring Solution: Online Cloud-Based Web Data Monitoring Service
Technologies Used:
Surveying Methods:
Deformation Monitoring:
Monitoring Solutions for Concrete Dams:
Monitoring Solutions for Earth and Rockfill Dams:
Monitoring Applications:
Monitoring Solutions:
Monitoring Solutions:
While the field of Structural Health Monitoring is already well-served by technology, as described in this article, the future of SHM promises to be even more precise and efficient. Software like OPSIS will help in processing out a large volume of data, and AI-intelligence laden with LiDAR scanning will help in creating a smaller-precise data set, ensuring that the results preserve the spatial information within the input data.
Preetie Ghotra is the Founder and CEO of Tejjy Inc., a women-oriented minority business specializing in BIM-VDC services for the AEC sector. She champions diversity and empowerment, particularly in women-oriented businesses, and focuses on collaboration on sustainable AEC values.
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