In this paper, an inverse method was developed which can, in principle, reconstruct arbitrary permeability, conductivity, thickness, and lift-off with a multi-frequency electromagnetic sensor from inductance spectroscopic measurements.Both the finite element method and the Dodd & Deeds formulation are used to solve the forward problem during the inversion process. For the inverse solution, a modified Newton-Raphson method was used to adjust each set of parameters (permeability, conductivity, thickness, and lift-off) to fit inductances (measured or simulated) in a least-squared sense because of its known convergence properties. The approximate Jacobian matrix (sensitivity matrix) for each set of the parameter is obtained by the perturbation method. Results from an industrial-scale multi-frequency sensor are presented including the effects of noise. The results are verified with measurements and simulations of selected cases.The findings are significant because they show for the first time that the inductance spectra can be inverted in practice to determine the key values (permeability, conductivity, thickness, and lift-off) with a relative error of less than 5% during the thermal processing of metallic plates.

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This paper presents the simulation and experimental study of the radiation pattern of a meander-line-coil EMAT. A wholly analytical method, which involves the coupling of two models: an analytical EM model and an analytical UT model, has been developed to build EMAT models and analyse the Rayleigh waves' beam directivity. For a specific sensor configuration, Lorentz forces are calculated using the EM analytical method, which is adapted from the classic Deeds and Dodd solution. The calculated Lorentz force density are imported to an analytical ultrasonic model as driven point sources, which produce the Rayleigh waves within a layered medium. The effect of the length of the meander-line-coil on the Rayleigh waves' beam directivity is analysed quantitatively and verified experimentally.

Gait analysis has been proved to be a powerful and efficient means for health monitoring. Variety of nervous system diseases and emergencies can be detected by interpreting plantar stress distributions. Among gait analysis techniques, piezoelectric insole architectures receive boosting attentions due to its convenience for users to wear and its long-term and real-time monitoring ability. However, the complex integration of piezoelectric insole architecture limits its successful use for massive production for the Internet-of-health things (IoHT). Hence, in this article, we present a flexible printed circuit board and lamination-associated technique, which presents high detection sensitivity at 0.1 N, satisfying the need for assisting nervous system disease diagnosis, and showing strong potential for commercialization.

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This paper presents a method which combines electromagnetic simulation and ultrasonic simulation to build EMAT array models. For a specific sensor configuration, Lorentz forces are calculated using the finite element method (FEM), which then can feed through to ultrasonic simulations. The propagation of ultrasound waves is numerically simulated using finite-difference time-domain (FDTD) method to describe their propagation within homogenous medium and their scattering phenomenon by cracks. Radiation pattern obtained with Hilbert transform on time domain waveforms is proposed to characterise the sensor in terms of its beam directivity and field distribution along the steering angle.

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