Modern improvised explosive device (IED) and mine detection sensors using microwave technology are based on
ground penetrating radar operated by a ground vehicle. Vehicle size, road conditions, and obstacles along the troop
marching direction limit operation of such sensors. This paper presents a new conceptual design using a rotary unmanned
aerial vehicle (UAV) to carry subsurface imaging radar for roadside IED detection. We have built a UAV flight
simulator with the subsurface imaging radar running in a laboratory environment and tested it with non-metallic and
metallic IED-like targets. From the initial lab results, we can detect the IED-like target 10-cm below road surface while
carried by a UAV platform. One of the challenges is to design the radar and antenna system for a very small payload
(less than 3 lb). The motion compensation algorithm is also critical to the imaging quality. In this paper, we also
demonstrated the algorithm simulation and experimental imaging results with different IED target materials, sizes, and
The use of microwave and radar sensors in the nondestructive evaluation (NDE) of damaged materials and
structures has been proven to be a promising approach. In this paper, a portable imaging radar sensor utilizing
10 GHz central frequency and stripmap synthetic aperture radar (SAR) imaging was applied to steel and wood
specimens for size and range determination. Relationships between range and properties of SAR images (e.g.
maximum amplitude and total SAR amplitude) were developed and reported for various specimens including a
steel bar (2.5 cm by 2.5 cm by 28.5 cm), a wood bar (2.5 cm by 2.5 cm by 28.5 cm), a steel plate (39.7 cm by
57.9 cm by 1.75 cm), and a wood board (30.5 cm by 30.5 cm by 1.8 cm). Various ranges from 30 cm to 100 cm
were used on these specimens. In our experiment, attenuation of radar signals collected by the imaging radar
system on different material specimens was measured and modeled. Change in the attenuation of maximum SAR
amplitude was observed in different materials. It is found that SAR images can be used to distinguish materials
of different compositions and sizes.
Corrosion of steel reinforcing bars (rebars) is the primary cause for the deterioration of reinforced concrete structures. Traditional corrosion monitoring methods such as half-cell potential and linear polarization resistance can only detect the presence of corrosion but cannot quantify it. This study presents an experimental investigation of quantifying degree of corrosion of steel rebar inside cement mortar specimens using ultrasonic testing (UT). A UT device with two 54 kHz transducers was used to measure ultrasonic pulse velocity (UPV) of cement mortar, uncorroded and corroded reinforced cement mortar specimens, utilizing the direct transmission method. The results obtained from the study show that UPV decreases linearly with increase in degree of corrosion and corrosion-induced cracks (surface cracks). With respect to quantifying the degree of corrosion, a model was developed by simultaneously fitting UPV and surface crack width measurements to a two-parameter linear model. The proposed model can be used for predicting the degree of corrosion of steel rebar embedded in cement mortar under similar conditions used in this study up to 3.03%. Furthermore, the modeling approach can be applied to corroded reinforced concrete specimens with additional modification. The findings from this study show that UT has the potential of quantifying the degree of corrosion inside reinforced cement mortar specimens.
In the structural health monitoring (SHM) of civil infrastructure, dynamic methods using mass, damping, and stiffness for characterizing structural health have been a traditional and widely used approach. Changes in these system parameters over time indicate the progress of structural degradation or deterioration. In these methods, capability of predicting system parameters is essential to their success. In this paper, research work on the development of a dynamic SHM method based on perturbation analysis is reported. The concept is to use externally applied mass to perturb an unknown system and measure the natural frequency of the system. Derived theoretical expressions for mass and stiffness prediction are experimentally verified by a building model. Dynamic responses of the building model perturbed by various masses in free vibration were experimentally measured by a mobile device (cell phone) to extract the natural frequency of the building model. Single-degreeof- freedom (SDOF) modeling approach was adopted for the sake of using a cell phone. From the experimental result, it is shown that the percentage error of predicted mass increases when the mass ratio increases, while the percentage error of predicted stiffness decreases when the mass ratio increases. This work also demonstrated the potential use of mobile devices in the health monitoring of civil infrastructure.