Search

Precise characterization of reinforcing bars (rebars) in a concrete structure is of significant importance for construction quality control and post-disaster safety evaluation. This paper integrates ground-penetrating radar (GPR) and electromagnetic induction (EMI) methods for simultaneous estimation of rebar diameter and cover thickness. A prototype of GPR-EMI dual sensor is developed, and a calibration experiment is conducted to collect a standard EMI dataset corresponding to various rebar diameters and cover thicknesses. The handheld testing cart can synchronously collect both GPR and EMI data when moving on the concrete surface, from which a data processing algorithm is proposed to simultaneously estimate the rebar diameter and cover thickness. Firstly, by extracting the apex of the hyperbolic reflection from the rebar in the preprocessed GPR profile, the rebar position is determined and further used to extract the effective EMI curve. Then, the rebar diameter and cover thickness are simultaneously estimated from the minimum mean square error between the measured and calibrated EMI data under the constraint of the GPR-estimated cover thickness. A laboratory experiment is performed using four casted concrete specimens with 11 embedded steel rebars. The results show that the diameters of 10 rebars are correctly estimated out of the 11 rebars, and the maximum estimation error for the cover thickness is 6.7%. A field trial is carried out in a newly-constructed building, and the diameters of four tested rebars are all accurately estimated while the estimation errors of the cover thickness are less than 5%. It is concluded that the developed GPR-EMI dual sensor and the proposed algorithm can estimate the rebar diameter and cover thickness accurately by a single scan.

Ground penetrating radar (GPR), as a nondestructive testing tool, is suitable for estimating the thickness and permittivity of layers within the pavement. However, it would become problematic when the layer is thin with respect to the probing pulse width, in which case overlapping between the reflected pulses occurs. In order to deal with this problem, a hybrid method based on multilayer perceptrons (MLPs) and a local optimization algorithm is proposed. This method can be divided into two stages. In the first stage, the MLPs roughly estimate the thickness and the permittivity of the GPR signal. In the second stage, these roughly estimated values are used as the initial solution of the full-waveform inversion algorithm. The hybrid method and the conventional global optimization algorithm are respectively used to perform the full-waveform inversion of the simulated GPR data. Under the same inversion precision, the objective function needs to be calculated for 450 times and 30 times for the conventional method and the hybrid method, respectively. The hybrid method is also applied to a measured data, and the thickness estimation error is 1.2 mm. The results show the high efficiency and accuracy of such hybrid method to resolve the problem of estimating the thickness and permittivity of a “thin layer”.

An aeromagnetic survey is an important method in magnetic anomaly detection and geophysical prospecting. The magnetic field is typically measured by optically pumped magnetometers (OPM) installed on the aircraft. The measurement accuracy of the OPM is easily affected by the platform-generated magnetic fields. Therefore, aeromagnetic compensation is necessary. The traditional compensation model only considers the permanent, induced, and eddy current interference magnetic field of the aircraft platform. However, the interference field produced by the avionics system, and the relative motion between the aircraft and the magnetometer, are still not taken into account. To address this issue, we proposed a novel strategy to eliminate the additional interference of the platform with two OPMs. Among them, the OPM located farther away from the aircraft serves as a sensing magnetometer, whereas the near OPM serves as a reference magnetometer. The coherent noise suppression method is used to process the residual magnetic field interference after compensation. By establishing the interference magnetic transfer function between the two sensors, the interference field can be suppressed. The results of the experiments demonstrate the effectiveness of the novel strategy, and the standard deviation of residual interference drops from 0.065 nT to 0.045 nT.

Low-frequency coded ground penetrating radar (GPR) with a pair of wire dipole antennas has some advantages for deep detection. Due to the large distance between the two antennas, the synchronization design is a major challenge of implementing the GPR system. This paper proposes a simple and stable wireless automatic synchronization method based on our developed GPR system, which does not need any synchronization chips or modules and reduces the cost of the hardware system. The transmitter omits the synchronization preamble and pseudorandom binary sequence (PRBS) at an appropriate time interval, while receiver automatically estimates the synchronization time and receives the returned signal from the underground targets. All the processes are performed in a single FPGA. The performance of the proposed synchronization method is validated with experiment.

A novel ultra-wideband (UWB) TEM horn antenna fed by a microstrip-type transition is designed. The feeding structure is directly realized by a microstrip line with the merit of compact size and UWB. To broaden the low frequency band, an arc surface is added at the end of the flare plates. Numerical simulation is applied to discuss the effect of the geometry construction which contains the microstrip-type transition and the circular arc surface at the end of radiating arm. Return loss, radiation pattern, and gain of the fabricated antennas are measured. The measured results show that the antenna yields a wide bandwidth ranging from 1 GHZ to 10.3 GHz with return loss less than −10 dB. The antenna also achieves unidirectional radiation patterns with stable antenna gain. These characteristics imply that the compact antenna may be used for detecting buried objects in the wall or UWB communication systems of band like GSM, Wi-Fi, and so forth.

It is a technical challenge to effectively remove the influence of magnetic noise from the vicinity of the receiving sensors on low-frequency magnetic communication. The traditional denoising methods are difficult to extract high-quality original signals under the condition of low SNR (the signal-to-noise ratio). In this paper, we analyze the numerical characteristics of the low-frequency magnetic field and propose the algorithms of the fast optimization of blind source separation (FOBSS) and the frequency-domain correlation extraction (FDCE). FOBSS is based on blind source separation (BSS). Signal extraction of low SNR can be implemented through FOBSS and FDCE. This signal extraction method is verified in multiple field experiments which can remove the magnetic noise by about 25 dB or more.

A generalized folded transformation procedure is presented for the space with arbitrary shapes. General expressions for the constitute parameters of complementary media are deduced, which can be readily applied to design complementary media based transformation optics devices (CMTOD) with arbitrary shapes. It's no longer limited to the situation when the inner and outer boundaries of the CMTOD are conformal or similar shapes, and can be available for the non-conformal situations. Three kinds of CMTOD are designed and studied, which involves a super-lens, an external cloak that hides object outside the cloaking shell, and an illusion optics device that transforms one object to another. Full-wave simulations are carried out to validate the proposed approach. The generalization introduced here makes a step forward for the flexible design of CMTOD with arbitrary geometries.

We describe the architecture of a time-to-digital converter (TDC), specially intended to measure the delay resolution of a programmable delay line (PDL). The configuration, which consists of a ring oscillator, a frequency divider (FD), and a period measurement circuit (PMC), is implemented in a field programmable gate array (FPGA) device. The ring oscillator realized in loop containing a PDL and a look-up table (LUT) generates periodic oscillatory pulses. The FD amplifies the oscillatory period from nanosecond range to microsecond range. The time-to-digital conversion is based on counting the number of clock cycles between two consecutive pulses of the FD by the PMC. Experiments have been conducted to verify the performance of the TDC. The achieved relative errors for four PDLs are within 0.50%–1.21% and the TDC has an equivalent resolution of about 0.4 ps.

The thickness estimation of the top surface layer and surface layer, as well as the detection of road defects, are of great importance to the quality conditions of asphalt pavement. Although ground penetrating radar (GPR) methods have been widely used in non-destructive detection of pavements, the thickness estimation of the thin top surface layer is still a difficult problem due to the limitations of GPR resolution and the similar permittivity of asphalt sub-layers. Besides, the detection of some road defects, including inadequate compaction and delamination at interfaces, require further practical study. In this paper, a newly-developed vehicle-mounted GPR detection system is introduced. We used a horizontal high-pass filter and a modified layer localization method to extract the underground layers. Besides, according to lab experiments and simulation analysis, we proposed theoretical methods for detecting the degree of compaction and delamination at the interface, respectively. Moreover, a field test was carried out and the estimated results showed a satisfactory accuracy of the system and methods.

The Scalar Triangulation and Ranging (STAR) method, which is based upon the unique properties of magnetic gradient contraction, is a high real-time ferromagnetic target localization method. Only one measurement point is required in the STAR method and it is not sensitive to changes in sensing platform orientation. However, the localization accuracy of the method is limited by the asphericity errors and the inaccurate value of position leads to larger errors in the estimation of magnetic moment. To improve the localization accuracy, a modified STAR method is proposed. In the proposed method, the asphericity errors of the traditional STAR method are compensated with an iterative algorithm. The proposed method has a fast convergence rate which meets the requirement of high real-time localization. Simulations and field experiments have been done to evaluate the performance of the proposed method. The results indicate that target parameters estimated by the modified STAR method are more accurate than the traditional STAR method.