Ebook: Selected papers from the International Symposium on Applied Electromagnetics and Mechanics 2023 (ISEM 2023): Part 2

On behalf of the ISEM 2023 Organizing Committee, we are honored to publish selected contributions presented at the 21st International Symposium on Applied Electromagnetics and Mechanics (ISEM 2023), which was held in November 2023 in Hachioji, Tokyo, Japan.

Since its inception in 1988 in Japan, ISEM has been held in various countries, including Korea, the United Kingdom, Germany, Italy, France, Austria, the United States, China, and Canada. Over the years, the symposium series has grown in scale, significance, and international recognition. We are privileged to continue this well-established tradition of presenting cutting-edge research and ideas in the field of applied electromagnetics and mechanics.

For ISEM 2023, a total of 236 papers were submitted to the editorial board, of which 227 were accepted for presentation and were included in the program. The authors represented 10 countries.

After a rigorous peer-review process, 50 of the 131 extended papers were accepted for publication in the International Journal of Applied Electromagnetics and Mechanics (IJAEM). For the volume in the book series Studies in Applied Electromagnetics and Mechanics, 41 extended papers were accepted for publication.

The success of ISEM 2023 was made possible through the dedicated efforts of many individuals. In particular, we would like to extend our deepest gratitude to the members of the local organizing committee, the staff of the Hachioji Convention and Visitors Association, who worked tirelessly to ensure the symposium’s success, and the ISEM International Steering Committee, chaired by Professor Toshiyuki Takagi, for their invaluable guidance and support.

We would also like to express our sincere appreciation to Antonello Tamburrino, Editor-in-Chief of IJAEM, and Gabriela Ricci, Associate Publisher at IOS Press, for their prompt assistance and unwavering support in facilitating the smooth publication of this special issue. Furthermore, we extend our heartfelt thanks to all our colleagues who contributed as reviewers.

Soichiro Ikuno, Tokyo University of Technology

Yiming Deng, Michigan State University

Weiying Cheng, Japan Power Engineering and Inspection Corporation

József Pávó, Budapest University of Technology and Economics

Guest Editors of the ISEM 2023 Special Issue, IJAEM

Energy harvesting, which refers to the generation of electricity from ambient sources using functional materials, has been extensively researched. In this paper, a cylindrical energy harvester that combines anti-vibration rubber and polyvinylidene fluoride piezoelectric film is proposed, and its characteristic evaluation method based on a theoretical model is also proposed. A forced vibration experiment using a servo hydraulic dynamic test system is conducted to determine the power generation characteristics. To evaluate the power generation performance, a characteristic evaluation model is constructed using the transfer matrix method for the governing equation of the longitudinal vibration of a bar. The results are compared with experimental results to verify the accuracy of the characteristic evaluation method.

This work presents the analytical model of H-type linear permanent magnet eddy current brakes (H-type LPMECB). In the presented paper, firstly, the analytical model of the H-type LPMECB was established using the equivalent magnetic circuit method. Secondly, the braking performance of the H-type LPMECB was simulated with the Finite Element Model(FEM) and the analytical model, respectively. The analytical model performance results are consistent with those of the FEM, which validates the analytical model. Hereafter, the nonlinear relationship between the iron foils number of the H-type LPMECB and the braking force was found by the analytical model and the FEM, which provides a guide for the iron foil number selection in future work. Finally, the experimental results are in agreement with the results obtained from the simulations, which also proves the analytical model and the simulation results.

The lift-off effect is a main challenge for the eddy current testing (ECT)-based rail detections. The non-coaxial transmitter-receiver (TR) probes are considered as promising structures, however, the research focused on the transmitter-receiver coil distance optimization is limited. In this study, this coil distance is optimized for the Tx-Rx probe with varying lift-offs in rail inspections. Firstly, the solution for the analytical model of the Tx-Rx probe is given. Based on the model, lo–D integration is introduced, and an optimization method is given. Analytical simulations under different conditions show that the optimized coil distance can reduce the lift-off effect, and is only related to the maximum value of lift-off and the out radius of the coils. This approach can also be applied to specimens with different materials and thicknesses. The proposed method provides an optimization method for coil parameter design.

The wall-thinning defect is one of the critical flaws that have been posing a severe threat to the structural integrity of Glass Fibre Reinforced Polymer (GFRP) employed in the hostile environment. In this paper, a sweep-frequency microwave testing method based on Cross-polarization Microwave Reflectometry (CMR) is proposed for detection and imaging of subsurface wall-thinning defects in the unidirectional GFRP. The simulation model of CMR is established along with the scrutinization of the characteristics regarding the testing signal in Ka band (26.5 GHz∼40 GHz). In experiments, a microwave testing system is built up for inspection of GFRPs together with the CMR probe designed using a pair of Ka-band rectangular waveguides based on the simulation model. Imitative subsurface wall-thinning defects and an actual impact defect in GFRP samples are inspected by using the system, and further imaged by using the time-domain signal and Range Migration Algorithm (RMA). The superiority of the proposed method is quantitatively identified through comparison of the signal-to-noise ratio of the imaging result between the CMR and the single-polarization microwave reflectometry.

The 3-D stray-field loss of the upgraded benchmark model TEAM P21^e with the two-sided excitation (ADH2) under various complex harmonic and DC-biased magnetization is analyzed by the 3-D fixed-point harmonic-balanced finite element method using parallel computing. The calculated results of the stray-field loss are in good agreement compared to the measured results. It is shown that the AC source has a larger effect on the total stray-field loss than the DC source. The efficiency of the 3-D fixed-point harmonic-balanced method with parallel computing is analyzed and can be potentially improved by 60%.

An investigation into the effect of the mass concentration of fine particles on the equivalent ionic mobilities of the system composed of small ions and large ions in the atmosphere is presented. A measurement apparatus is designed using direct current corona discharge at room temperature. Positive and negative ion mobilities are extracted from the electric field strength and ion current density measured in the apparatus. With the presence of fine particles, equivalent ionic mobilities are found to decrease exponentially with the mass concentration of the particles. The distributions of electric field and space charge density, the contributions to the charge density from ions and fine particles are also calculated.

The optically pumped magnetometer (OPM) operating in spin exchange relaxation-free (SERF) regime is a kind of magnetic sensor that has ultra-high sensitivity. SERF OPMs need to operate in a near zero magnetic field environment. In many applications, multi-channel OPMs are utilized to measure the magnetic field at different observation points, where the magnetic fields generated by the OPMs interfere with each other. To suppress the magnetic field interference, this paper proposes a magnetic field compensation method based on an artificial neural network (ANN). The transfer function between the compensation currents and the observed signals is derived, based on which a nonlinear multiparameter optimization problem is derived. Experimental data with different initial magnetic field conditions is collected. Then, an ANN model is employed to optimize the compensation currents of the OPMs to minimize the magnetic field experienced by each sensor. It is demonstrated that this method can effectively reduce the magnetic field crosstalk of multi-channel OPMs.

This article presents a novel rope-driven antagonistic variable stiffness robot elbow joint based on permanent magnet spring and pulley block. The proposed joint enlarges both the range of motion and stiffness. The structure and working principles of the elbow joint are elucidated, along with the joint stiffness model. The changing pattern of joint stiffness is analyzed, and a controller is devised to decouple the stiffness and position of the joint. Experimental results verify the accuracy of decoupling and showcase the energy-saving characteristics of the joint. Furthermore, the paper investigates the impact of joint stiffness variation on joint position control.

This paper aims to propose an improved probe for remote field eddy current testing (ECT) method with a ferromagnetic core inserted into coils, and to verify the effect of the improved detection sensitivity. The remote field eddy current testing method which installs an excitation coil and a search coil inside a pipe is known to be effective in detecting external surface defects in ferromagnetic pipes used in petrochemical or steel industries. In previous research, the phase angle between the flux density due to the excitation current and that due to the eddy current inside the pipe, when a magnetic field of several hundred Hz is applied to the excitation coil, was analyzed. It has been clarified that the detection signal sensitivity is reduced because of the phase angle approaches 180 degrees and cancel each flux density out. In this research, an improved remote field ECT probe with ferromagnetic core inserted in coils is proposed to increase the detection signal sensitivity. The measured sensitivity of the proposed probe is increased compared with the conventional one. The mechanism of different shapes and materials are analyzed in detail by using 3D nonlinear eddy current analysis using finite element method (FEM). It was found that that when a core of S45C was inserted in the excitation coil, the phase angle change became larger at the defect position because the phase angle of the flux density due to excitation current is delayed by eddy current in the core which affected the sensitivity improvement.

Carbon fiber reinforced plastic (CFRP) material is a lightweight, high-strength material that takes advantage of the characteristics of carbon fiber and resin. CFRP is widely used in parts that require high strength, such as aircraft and hydrogen tanks. Although it has high strength, receiving a large impact may cause internal peeling or internal defects. Detection of these delamination and defects is important for the strength and quality assurance of CFRP materials. In this research, an inspection method of the CFRP materials using electromagnetic force vibration is proposed. In this method, electromagnetic force vibration is impressed from the surface of the CFRP material with the internal defects, and the defects are estimated from the vibration intensity. When the proposed inspection method is applied to a CFRP plate with the internal defect, since the vibration intensity at the defect location is increased, the defect can be detected.

In semiconductor manufacturing, the process of manufacturing various components and wiring on silicon wafers requires high cleanliness. While traditional magnetic levitation slider devices are effective in preventing mechanical contact and minimizing dust generation, the suspension and propulsion mechanisms are often separated which can lead to inefficient use of vertical magnetic force. This research presents a new type of bearingless slider that integrates magnetic levitation and propulsion mechanisms through the utilization of a shared magnetic flux from an E-shaped iron core. This configuration maximizes energy utilization while minimizing energy loss caused by the separate use of suspension and drive devices while simplifying the overall structure. The stable point of the slider during the suspension process was analyzed using the finite element method. A dynamic model was developed, and suspension experiments were conducted to validate the model. The device can restore stable suspension within 3 seconds after being subjected to a 1N impact load during driving. The results indicate that the suspension system has good response characteristics and anti-interference characteristics.

We develop a PCR method utilizing carbon-coated iron (Fe@C) nanoparticles. The outer carbon layers of the nanoparticles absorb near-infrared (NIR) light and release energy as heat. We carry out PCR performing thermal cycling via the on/off operation of NIR irradiation to the nanoparticles. We show that the total time of PCR is shortened compared to the conventional method thanks to rapid, efficient heating by Fe@C nanoparticles. We also show that the amount of by-products is smaller than the conventional case, which may be attributed to the rapid thermal cycling.

Multivariate Empirical Mode Decomposition (MEMD) is a powerful tool to analyze nonlinear properties, however, it is very computationally time-consuming. The purpose of this study is to parallelize and accelerate MEMD, and to apply the accelerated MEMD to the analysis of electromagnetic wave propagation in photonic crystals, to improve the efficiency of generation of a demultiplexer. In the proposed method, part of the procedures that do not depend on channels of input signal were parallelized. Speedup which is based on 24 CPU threads of 5.12 times is achieved when 192 threads are adopted.

In this study, the Hilbert-Huang Transform (HHT) and other frequency analysis methods, Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT), are employed to numerically analyze electromagnetic phenomena with strong non-linearity. In the numerical experiments, electromagnetic wave propagation simulations using the Finite-Difference Time-Domain (FDTD) method are performed to reproduce the behavior of electromagnetic shielding effects leaking from the shielding plate. The obtained results were analyzed using the HHT, STFT, and CWT methods; the HHT analysis showed that electromagnetic waves around the input wavelength 2.45 GHz leak significantly from the shielding plate. On the other hand, the STFT did not accurately resolve the signal, and the CWT unexpectedly showed strong amplitudes in the low-frequency region. These results suggest that HHT performs better in analyzing signals with strong non-linearity and provides more accurate results than other methods.

The paper confirms the feasibility of detection of faraway defects in long metal plates, up to 3.5 meters, using EMAT (Electromagnetic Acoustic Transducer) based on a Halbach magnet. The development and optimization of the new EMATs is based on 2D FEM (two-dimensional Finite Element Method) simulations using a physics-coupling formulation of ECT (Eddy Current Testing) and UT (Ultrasonic Testing) in order to increase the EMAT signal amplitude and its signal-to-noise ratio of the defects. The defects are located on the opposite side of the surface where the EMAT is located, with depths exceeding 20% of the plate thickness. Numerical simulations and experimental measurements confirm the feasibility of the method in a frequency range below 1MHz, opening up new possibilities for detecting faraway defects (1-3 meters) in thicker metal plates based on a single (emitter/receiver) EMATs using SH (shear horizontal) waves.

In this study, a novel pre-processing method to improve the prediction accuracy of deep learning (DL) in predicting motor characteristics are proposed. In the proposed method, a frequency decomposition method called empirical mode decomposition is applied to the gap magnetic flux density distribution, which is the input data of the DL.

In this study, the restoring force generated by the superconducting pinning phenomenon was examined in terms of the characteristic change caused by the concave-stage arrangement of the two superconductors. By analyzing the restoring force characteristics in each direction of a superconducting magnetic bearing created using two superconductors, we verified whether the restoring force characteristics change. As a result of the experiment, it was confirmed that the restoring force in each direction is increased by arranging the superconductor with a stepped shape. Experiments have shown the usefulness of applying a concave step arrangement to superconductors.

Power inductors are indispensable in power electronics systems, where they play a critical role in ensuring efficient energy conversion. However, these components contribute to significant inefficiencies and occupy valuable space. Traditional optimization techniques, such as genetic algorithms (GA) and covariance matrix adaptation evolution strategy (CMA-ES), offer promising designs to address these issues but are hindered by high computational costs. This study proposes a novel optimization approach based on the actor-critic (AC) method, a reinforcement learning technique. The AC method not only reduces computational time substantially but also achieves stable convergence toward optimal inductor shapes. Through direct comparisons with GA and CMA-ES, we demonstrate the AC method’s potential to set a new standard for efficient and compact power inductor design.

To improve the cornering performance of a yaw moment control system that assists the self-spinning motion of a competition vehicle, in this paper, we propose a vehicle subjected to electric motor drive torque and brake torque using an actuator. This system is expected to improve the vehicle’s dynamic performance by allowing a rear brake system installed in the right and left tires to be individually actuated. Quasi-static vehicle dynamics analysis of a vehicle equipped with the proposed system was conducted to investigate the improvement of vehicle performance due to active yaw moment changes as a preliminary step to developing control laws for the proposed system. The results of the analysis showed that the maximum steady-state lateral acceleration at a constant vehicle velocity could be improved by 13% by evaluating the cornering performance of the vehicle with and without the system. The required yaw moment change was calculated, and the electric motor torque and actuator force were calculated to satisfy these requirements.

Pipe-wall thinning due to corrosion is an essential problem for piping systems in nuclear power plants. This study aims to characterize periodic rough surfaces on the inside thinned walls of pipes. This paper focuses on the frequency spectrum of the reflected waves to investigate the reflection of ultrasonic waves from periodic rough surfaces. The spectrum dropped at specific frequencies by using block-shaped specimens with parallel flaws. The tendency was observed in both the experiment and simulation. The results indicated that the wavelength calculated from the frequency of amplitude drop roughly corresponded to the flaws’ pitch.

The stability of engineering structures will be greatly affected when they are subjected to stationary random loads. Such loads must be accurately identified to ensure the structural safety. Due to the complexity of stationary random loads and difficulty of solving inverse problems, traditional methods require improvement in identification accuracy. In this work, a stationary random load identification method based on ensemble empirical mode decomposition (EEMD) and deep recurrent neural network (RNN) is proposed. The method designs a deep RNN model consisting of one gated recurrent unit (GRU) layer, one bidirectional long short-term memory (BLSTM) layer, two long short-term memory (LSTM) layers, and two fully connected (FC) layers in sequence. The load and response signals are decomposed into a set of intrinsic mode functions (IMF) from high to low frequencies using EEMD, with the decomposed signals serving as the output and input of the network, respectively. The effectiveness of the proposed method is verified by the simulation data of a three-degree-of-freedom (3DOF) linear system, and the results show that the proposed method is with higher accuracy than using only deep RNN without signal decomposition. The method is verified by the experimental data of a clamped beam as well, with results showing a high accuracy of stationary random load identification.

The optical loads on high-resolution satellites are very sensitive to vibration. Therefore, it is crucial to meet the pointing accuracy and micro-vibration suppression for the optical loads. In this work, a parallel platform with nine legs is designed for integrated micro-vibration and pointing control. The legs include six legs for micro-vibration and three legs for pointing control. Combining the decoupling of micro-vibration and attitude motion, a joint control model is built in Matlab/Simulink. The simulation result shows that the new platform can achieve good performance in both micro-vibration suppression and precision pointing control.

Due to the complex structure of modern systems, large-scale optimization has become the hot spot of practical engineering problems. An improved fireworks algorithm (FWA) is proposed to obtain the global optimal solution of large-scale optimization problems in a fast manner. To promote the ability to jump out of the local optimal solution, a differential sparks generation mechanism and a novel reinitialization mechanism are developed. To speed up the convergence, a dual-channel selection mechanism is proposed, in which an exclusive channel is given for differential sparks. The combination of differential sparks generation and dual-channel selection promotes the usage of known information, balances the diversity and convergence of the fireworks. Typical test suites and unmanned aerial vehicle (UAV) path planning are used to test the effectiveness and efficiency of the proposed algorithm. Simulation results demonstrate that the proposed algorithm can search for the global optimal solution in a large variable space and can obtain a short-distance path for the UAV.

The output performance of stick-slip piezoelectric actuators is comprehensively determined by the electro-mechanical responses of the driving unit, control strategy, and the contact status between the driving unit and the slider. Most previously developed inertial piezoelectric actuators face the problems of frequency dependence, motion speed, excessive volume, step resolution, and loading capacity. To exhaustively improve actuation performance, we propose a compact bi-directional piezoelectric-based rotary actuator incorporating the single excitation source, rhombic amplification mechanism, and adjustable preload. The numerical simulations are implemented based on the LuGre friction model, to guide the system optimization. A prototype is fabricated and examined, which accomplishes the maximum load torques of 27.78 and 30.87 N.mm in clockwise and anticlockwise directions, respectively, at the highest rotational velocity of 0.4720 rad/s. Compared with previously reported inertial actuators, the performance of the proposed actuator is significantly enhanced, promising in applications requiring nanometer resolution, long stroke, large holding, and driving forces.