In sinusoidal eddy-current (EC) nondestructive testing (NDT) of thick ferromagnetic tubes, such as oil-well casings, average wall thickness is measured with an exciter coil and a detector coil displaced by more than two tube diameters [remote field eddy current (RFEC) technique]. Since RFEC cannot differentiate outer from inner defects, the average tube inner diameter is determined at higher frequency with another pair of coils displaced by around one tube diameter (electrical caliper). It is expected that the key drawbacks of such EC tools (several coils, complex transducer electronics, relatively high power consumption, and length) can be overcome with the application of pulse excitation. In this paper, we give a thorough analysis of the effect of the excitation frequency and the distance between the coils on the detected signal sensitivity to the tube properties, as a basis for usage of pulsed eddy current (PEC). We show that pulse excitation, thanks to its continuous frequency spectrum and time separation of direct and remote zone signals, allows simultaneous measurement of average wall thickness and inner diameter with one detector coil separated from the exciter by one to two tube diameters. The results of our experimental work confirm that PEC technique provides a significant improvement on present EC tools for NDT of ferromagnetic tubes.

Discriminating metal parts of buried hazardous targets from ordinary metallic clutter is a very difficult and time-consuming task. For that purpose, electromagnetic induction (EMI) sensors composed of multiple transmitter/receiver coils in multiaxis arrangements are commonly used. In this way, data of high fidelity and spatial diversity are obtained so that the target can be characterized in terms of its geometric and electromagnetic properties. However, this often increases sensor size and reduces its portability, which is a problem for humanitarian demining applications, where compact, robust, and lightweight sensors are needed. If such sensors are to be used for target characterization, robust estimation algorithms are required, capable of coping with limited spatial information content and uncertainties related to sensor positioning and its coil geometry model. In this paper, we present a robust concept for estimating the general shape of magnetic metal targets using time-domain EMI sensors with single-axis coil geometries. We introduce the signature matrix, a parameter derived from time-dependent eigenvalues of the target's magnetic polarizability tensor, and use it for shape estimation. The proposed method was evaluated both through simulations and experiments, using two different sensor platforms (laboratory-based experimental sensor platform and a commercial metal detector mounted on a mobile robot). The obtained results clearly indicate that the target shape can be estimated from sensor data of limited spatial diversity and under the uncertainties of sensor positioning and coil geometry.

In eddy-current nondestructive testing of conductive tubes such as oil-well casings, the measured tube wall thickness and inner diameter must be compensated for variations of electromagnetic properties of a tube material -magnetic permeability and electrical conductivity. Commercial systems for eddy-current nondestructive testing of oil-well casings incorporate multiple coils and multifrequency excitation for measurement of the inner diameter and the electromagnetic properties. This paper investigates the feasibility of the electromagnetic properties and inner diameter measurement with only one coil excited at one frequency. The authors have derived a coil impedance model and developed an inversion procedure for the determination of tube properties. Measurements have been performed on several tubes made of different materials. In order to validate the model and the optimization algorithm, measurement results were compared with the predictions of the model and finite-element analysis. Applicability of the method has been confirmed for the investigated frequency range (1-50 kHz).

A bounded domain of eddy-current problems leads to discrete eigenvalues and it allows one to satisfy the interface conditions between coupled regions simultaneously along two coordinates. The eigenvalues are zeros of complex domain functions that, for many eddy-current applications, have the same trigonometric form due to the sine and cosine terms in a corresponding general solution of the governing Helmholtz equation. We examine the functions' properties: 1) pole locations and multiplicity; 2) zero levelsets; and 3) region enclosing the zeros. These properties allow the construction of reliable and efficient algorithms for the eigenvalue computation, which are essential for bounded domain eddy-current models with coupled regions. We propose such an algorithm based on Cauchy's argument principle. We verify the algorithm using dimensions and materials typically encountered in diverse practical applications. The proposed algorithm performance is compared with the performance of an algorithm based on the Netwton-Raphson method.

In a context of buried objects detection using electromagnetic induction (EMI), dipole inversion refers to the estimation of object’s location and magnetic polarizability tensor from EMI and sensor’s positional data. In case of planar coil sensors, dipole inversion may become a surprisingly difficult and potentially ill-posed problem due to non-uniform distribution of directional sensitivities, nonlinear nature of target localization, as well as strong correlations between tensor elements and target’s depth. In this paper, we evaluate inversion performances of two categories of planar coil sensors; single-receiver sensors used in conventional metal detection (MD), and multi-receiver sensors aimed at metal characterization (MC). We use three different inversion methods; nonlinear least squares (NLS), HAP method featuring novel auxiliary source model for improved object localization, and differential evolution (DE). Comparative study is performed using synthetic EMI and sensor’s positional data under realistic scenarios involving different targets, depths and signal-to-noise ratios (SNRs). Our results suggest that relatively simple planar MC sensors clearly outperform conventional MD sensors, especially at greater depths. On average, DE method notably improves the invertibility of MD sensors, while a denser scan pattern may help to tackle lower SNR at greater depths.