Local scour is arguably the most pressing issue regarding the safety and longevity of overwater civil infrastructure. Many modern scour detection techniques do not provide continuous scour depth measurements, nor can they function under extreme flow conditions, which is when scour monitoring becomes most critical. Thus, the objective of this study was to develop scour depth monitoring sensors using ultrasonic time domain reflectometry (UTDR). The scour sensor was based on an aluminum strip with two piezoelectric macro fiber composites (MFCs) bonded at one end. The aluminum strip or rod-like sensor is intended to be driven and buried at the location where scour depth measurements are desired. The two MFCs were used to either generate or sense ultrasonic Lamb wave pulses propagating in the aluminum strip. During scour, as sediment is eroded from around the base of the strip, the distance (i.e., scour depth) between the MFCs and the soil interface would increase. The hypothesis was that increasing scour depth would change the mechanical impedance of the system to cause measurable and unique signatures in the residual Lamb wave signals. To test this hypothesis, different interfaces (i.e., metal-metal, polymer-metal, and soil-metal) were applied at different locations along the aluminum strip and MFC system. The MFC sensor-actuator pair was actuated to propagate and measure the corresponding Lamb waves during each test. The results showed clear changes in the residual signal, which were well-correlated to the changing locations of the artificial interface. In particular, the time-of-flight of the response pulse within the residual signature could be used to accurately determine the location of the soil interface or scour depth. Overall, this study demonstrated feasibility of an UTDR sensor for scour monitoring.
The ability to measure, monitor, and prevent catastrophic failure has made structural health monitoring crucial for aerospace, civil, and marine structures. Spatial strain sensing is necessary for quantifying distributed damage in structural systems. Previous studied that coupled electrical impedance tomography (EIT) algorithms with piezoresistive coatings opened up vast opportunities for distributed strain sensing. However, these approaches could not extract strain directionalities from the reconstructed EIT conductivity maps, and sensing resolution remained rather low. Therefore, this study aims to develop next-generation “sensing meshes” capable of resolving both spatial strain magnitudes and directionalities for distributed strain field monitoring. The approach is to design and fabricate piezoresistive graphenebased thin films and then patterning them to form a grid or mesh. The nanocomposite grid lines were designed to be of a high-aspect ratio so that each grid element could sense distributed strain along its length and direction. Various sensing mesh specimens were fabricated, and a load frame was employed to strain them in a controlled manner. Similar to conventional EIT, boundary voltage measurements were acquired when electrical current was applied between two boundary electrodes. The boundary voltage dataset was then used as inputs to the EIT inverse algorithm to reconstruct the conductivity distribution of the sensing mesh. For verification, these experimental results were compared to an elastic finite element model subjected to the same strain states. Good agreement between the experimental tests and numerical simulations were observed, thereby demonstrating the potential of this technology for distributed strain field monitoring.
Inland navigation infrastructure is critical to local and global economies, and unplanned or extended down time for maintenance and repairs can have significant social and economic consequences. The extensive collection of navigation related infrastructure maintained by the US Army Corps of Engineers (USACE) is in a state of degraded performance, with some components presently being used well beyond their design life. To provide data-driven decision-support for operation, maintenance, and repair/replacement of these components, the Engineer Research and Development Center (ERDC) is developing structural health monitoring (SHM) and damage prognosis (DP) tools and techniques. ERDC has deployed the Structural Monitoring and Analysis in Real-Time of lock Gates (SMART Gate) program at several sites for long-term monitoring of hydraulic steel navigation and flood control gates. When SMART Gate systems are deployed, a significant effort and percentage of the cost is spent installing conduit to protect wires that extend from the sensors, which are typically underwater during operation, to the data logger. To reduce installation time and cost, the ERDC developed a system for energy efficient sensor data transmission underwater. The system was successfully field tested, sending data the height of the lock chamber using low nominal power, with a relatively low data loss. This paper will describe the SHM framework developed by ERDC and the development and deployment of the wireless data transmission system.
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