Dylan Burns

Concrete bridge deck condition assessment with automated multisensor techniques

Early and accurate detection, location and assessment of damage in reinforced concrete bridge decks may be beneficial in the scheduling and performance of maintenance and rehabilitation activities. This article presents the results of a multiple sensor study of the condition of the reinforced concrete deck of the Van Buren Road Bridge in Dumfries, VA. The tests compared the following five different methods: (1) visual inspection and photographic recording; (2) half-cell electrochemical potential; (3) impulse type multipoint scanning ground penetrating radar; (4) chain drag and (5) impact echo. The bridge was tested on two separate occasions. The results of the tests were that each instrument nominally performed and collected data as expected, but that the condition assessments did not necessarily agree. The data are registered, overlaid and compared. The potential for developing automated multisensor systems that fuse data for efficient and effective bridge deck measurements is discussed.

Design of UWB Antenna for Air-Coupled Impulse Ground-Penetrating Radar

This letter presents a new transverse electromagnetic flared horn antenna for the demanding requirement of an air-coupled impulse ground-penetrating radar. Structure anatomy is performed focusing on achieving good impedance matching throughout the wide frequency band. The design procedure starts with constructing an analytic model to evaluate the preliminary physical dimensions to achieve minimum reflections. Structural fine tunings are then performed for optimization. The antennas are fabricated and tested. Experimental results validate the design effectiveness.

Hierarchical actuator systems

Mechanical actuators are integral components of many engineered systems. Many of the presently available actuator systems lack the desired stroke, power, controllability and reliability. The hierarchical actuator is a natural extension of the trend toward improving the performance of actuators through increments in geometric complexity and control. The hierarchical concept is to build integrated actuators out of a combination of smaller actuators. The smaller actuators are arranged geometrically and controlled so as to extend the performance of the total actuator into ranges that are not possible with actuators that are based on a few active elements and levels of control. Precision, speed increase, force output, load sharing, efficiency under smooth load/displacement control, smooth motion, stroke amplification/reduction and redundancy are all possible. Mechanics and mechanisms of hierarchical actuators are examined, along with a few experiments to demonstrate the operating principles.

Sand moisture assessment using instantaneous phase information in ground penetrating radar data

In this paper, a method using the instantaneous phase information of the reflection ground penetrating radar (GPR) signal to detect the variation of sand moisture is developed. The moisture changes the permittivity of the medium, which results in different speed when the GPR electromagnetic (EM) wave propagates in the medium. In accordance to this principle, we develop an analytical method to extract GPR reflection signal’s instantaneous phase parameters utilizing Hilbert Transform for sand moisture characterization. For test evaluation, Finite Difference Time Domain (FDTD) numerical simulations using a 3rd party open source program GprMax V2.0, and laboratory experiments on sand samples are conducted using a commercial GPR (2.3 GHz Mala CX) as the data acquisition system.

Integration of Automated and Robotic Systems with BIM for Comprehensive Structural Assessment

This paper presents a conceptual framework of how some recent efforts aimed at using data gained from automated and robotic structural sensing systems can be incorporated into Building Information Modeling (BIM) systems leading to a comprehensive, intelligent structural health management system. Robotic and similar automated systems may extend the reach of structural sensing systems to realms and modes that are impractical with other systems. This paper begins with a brief discussion of the operational principles of the following automated inspections systems: (1) Multisensor assessment of concrete corrosion damage; (2) Low-cost high-quality image processing for structural condition; (3) Quadcopter UAV for remote imaging of structural condition; (4) Suction foot robot for climbing on brick and concrete walls; (5) Wheeled robot with active stereo imaging system that measures structural shapes; and (6) Lidar imaging system with integration into BIM. These systems carry onboard sensors, such as 3-D optical imagers and ground penetrating radar. Issues when using these systems include: (1) Position registration and navigation; (2) Sensing system performance and operational procedures; (3) Safety; and (4) Intelligent integration of sensing data into structural database. The present state of the art is that these types of systems work reasonably well and can generate large data streams that quickly overwhelm manual management methods. A possible path of automated data management is to tie the data directly to a structural database. BIM is presented as a potential framework for data integration, synthesis, retrieval and rapid display of data in graphical formats tied to the structure, in a level of detail hierarchy.

New GPR System Integration with Augmented Reality Based Positioning

The development of modern cities heavily relies on the availability and quality of underground utilities that provide drinking water, sewage, electric power, and telecommunication services to sustain its growing population. However, the information of localization and condition of subterranean infrastructures is generally not readily available, especially in areas with congested pipes, which impacts urban development, as poorly documented pipes may be hit during construction, affecting services and causing costly delays. Furthermore, aging components are prone to failure and may lead to resources waste or the interruption of services. Ground penetrating radar (GPR) is a promising remote sensing technique that has been recently used for mapping and assessment of underground infrastructure. However, current commercial GPR survey systems are designed with wheel-encoders or GPS for positioning. Wheel-encoder based GPR surveys are restrained to linear-route only, preventing the use of GPR for accurate localization of city wide underground infrastructure inspection. While GPS signal is degraded in urban canyons and unavailable in city tunnels. In this work, we present a new GPR system integration with augmented reality (AR) based positioning that can overcome the limitations of current GPR systems to enable arbitrary-route scanning with a high fidelity. It has the potential for automation of GPR survey and integration with AR smartphone applications that could be used for better planning in urban development.

Underground utility sensing network using LoRa and magnetic telemetry (Conference Presentation)

Many cities seek utilities monitoring with centrally managed Internet of Things (IoT) systems. This requires the development of many reliable low-cost wireless sensors, such as water temperature and flow meters, that can transmit information from subterranean pipes to surface-mounted receivers. Traditional radio communication systems are either unable to penetrate through multiple feet of earthen and manmade material, or have impractically large energy requirements which necessitate either frequent replacement of batteries, or a complex (and expensive) built-in energy harvesting system. Magnetic signaling systems do not suffer from this drawback: low-frequency electromagnetic waves are shown to penetrate well through several feet of earth and water. In the past, these signals were too weak for practical use; however, this has changed with the recent proliferation of high-sensitivity magnetometers and compact antennas using mechanically actuated rare-earth magnets. A permanent magnet can be either rotated or vibrated to create an oscillating magnetic field. Utilizing this phenomenon, two flow meter designs are proposed: one which uses a propeller to directly rotate a diametrically magnetized neodymium magnet; and, another which uses an oscillating tail to move a permanent magnet back-and-forth across a novel soft-magnet Y-stator, which projects a switching magnetic field. These oscillating magnetic fields are used to send water flow rate information to an above ground LoRa-capable Arduino receiver equipped with a magnetometer. Simulation software is used to model the oscillating electromagnetic fields. Complete system performance with remote datalogging is tested, with the aim of integrating many sensors and surface receivers into a single LoRa wireless IoT network.

3D tomography for multistatic GPR subsurface sensing

Ground penetrating radar (GPR) subsurface sensing is a promising nondestructive evaluation (NDE) technique for inspecting and surveying underground utilities in complex urban environments, as well as for monitoring other key infrastructure such as bridges and railroads. A challenge of such technique lies on image formation from the recorded GPR data. In this work, a fast back projection algorithm (BPA) for three-dimensional GPR image construction is explored. The BPA is a time-domain migration method that has been effectively used in GPR image formation. However, most of the studies in the literature apply a computationally intensive BPA to a two-dimensional dataset under the assumption that an in-plane scattering occurs underneath the GPR antennas. This assumption is not precise for 3D GPR image formation as the GPR radiation scatters in multiple directions as it reaches the ground. In this study, a generalized form for an approximation to determine the scattering point in an air-coupled GPR system is developed which considerably reduces the required computations and can accurately localize the scattering point position. The algorithm is evaluated by applications on GPR data synthesized using GprMax, a finite-difference time domain (FDTD) simulator.

Mechano-Magnetic Telemetry for Underground Water Infrastructure Monitoring

This study reports on the theory of operation, design principles, and results from laboratory and field tests of a magnetic telemetry system for communication with underground infrastructure sensors using rotating permanent magnets as the sources and compact magnetometers as the receivers. Many cities seek ways to monitor underground water pipes with centrally managed Internet of Things (IoT) systems. This requires the development of numerous reliable low-cost wireless sensors, such as moisture sensors and flow meters, which can transmit information from subterranean pipes to surface-mounted receivers. Traditional megahertz radio communication systems are often unable to penetrate through multiple feet of earthen and manmade materials and have impractically large energy requirements which preclude the use of long-life batteries, require complex (and expensive) built-in energy harvesting systems, or long leads that run antennas near to the surface. Low-power magnetic signaling systems do not suffer from this drawback: low-frequency electromagnetic waves readily penetrate through several feet of earth and water. Traditional magnetic telemetry systems that use energy-inefficient large induction coils and antennas as sources and receivers are not practical for underground IoT-type sensing applications. However, rotating a permanent magnet creates a completely reversing oscillating magnetic field. The recent proliferation of strong rare-earth permanent magnets and high-sensitivity magnetometers enables alternative magnetic telemetry system concepts with significantly more compact formats and lower energy consumption. The system used in this study represents a novel combination of megahertz radio and magnetic signaling techniques for the purposes of underground infrastructure monitoring. In this study, two subterranean infrastructure sensors exploit this phenomenon to transmit information to an aboveground radio-networked magnetometer receiver. A flow meter uses a propeller to directly rotate a diametrically magnetized neodymium magnet. A moisture sensor rotates a magnet with a low-power electric motor. Laboratory performance and field tests establish the capabilities of magnetic telemetry for IoT-linked leak-detection sensors. Remote datalogging with encryption demonstrates the viability of integrating sensors and surface receivers into a LoRa wireless IoT network.

Rough ground surface clutter removal in air-coupled ground penetrating radar data using low-rank and sparse representation

This paper explores a low-rank and sparse representation based technique to remove the clutter produced by rough ground surface for air-coupled ground penetrating radar (GPR). For rough ground surface, the surface clutter components in different A-Scan traces are not aligned on the depth axis. To compensate for the misalignment effect and facilitate clutter removal, the A-Scan traces are aligned using cross-correlation technique first. Then the low-rank and sparse representation approach is applied to decompose the GPR data into a low-rank matrix whose columns record the ground clutter in A-Scan traces upon alignment adjustment, and a sparse matrix that features the subsurface object under test. The effectiveness of the proposed clutter removal method has been evaluated through simulations.