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For the calculation of corona loss of extra‐/ultra‐high voltage (EHV/UHV) transmission lines, especially the estimation of real‐time corona loss, there exists no accurate method. In this paper, a calculation method of corona loss in the EHV/UHV system based on a distributed parameter characteristic is proposed. Based on the π‐shaped equivalent circuit of the long‐line distributed parameter characteristic, and considering the voltage distribution along the line, a formula for calculating the corona loss under a variety of weather and annual average conditions is derived and the power equation for the corona loss of EHV/UHV system is established by the method. The example results show that the method is quite accurate. The calculation method of this paper can consider different weather conditions of the line sections to calculate the corona loss. It is more in line with the actual weather conditions on the surface of the EHV/UHV transmission lines. And the method can analyze the corona loss and its proportion to the total loss of the system under the annual average and different weather conditions. It is of great significance to the design and operation of an EHV/UHV system. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The design of external insulation for transmission lines is usually based on real‐type experiments. With the increasing voltage level of the transmission lines, in order to better design the experiments and reduce the experiment workload in the future, this paper studies the switching impulse discharge characteristics of air gaps of an ultrahigh‐voltage (UHV) transmission line. A long air gap switching impulse breakdown voltage prediction method based on the leader discharge mechanism is proposed in this paper, and a continuous leader inception model is fitted for the air gaps in UHV transmission lines by calculating the factor R of the conductor–plane gaps. The method and the model can effectively predict the air gap breakdown voltage of transmission lines. The influence of tower width and conductor structure on air gap breakdown characteristics of UHV transmission lines is studied by the method and the model proposed this paper. The results show that, as the width of the tower increases, the breakdown voltage decreases, and as the gap length increases, the influence of the tower width on the breakdown voltage decreases. The conductor structure has no obvious influence on the discharge characteristics of transmission line air gaps. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The electric power propulsion is becoming the important development direction of ship propulsion technology recent years, as it is conducive to the realization of automation, intelligence, reduced noise, enhanced propulsion efficiency, high power density, flexible arrangement, and energy saving. The good fault‐tolerant capacity and robustness of the fault‐tolerant permanent magnet motor (FTPMM) make it a potentially highly effective and economical propulsion motor in the electric power propulsion ship than other alternatives. In this paper, the structure and mathematical model of FTPMM are analyzed and the improved sliding mode observer (SMO) is constructed according to the deviation between the observed currents and actual currents. Combined with model reference adaptive control (MRAC) method and the phase‐lock loop (PLL), the switch function is replaced by the continuous Sigmoid function to reduce the chattering and finally the rotor position estimated accuracy is improved. When the motor winding open‐circuit and short‐circuit fault occur, the current vector fault‐tolerant control strategy is introduced into the improved SMO algorithm, and the rotor position is estimated accurately under faulty conditions. Finally, the proposed improved SMO position estimation algorithm under healthy and faulty conditions is verified in Matlab/Simulink. The FTPMM position sensorless technology would play a critical role in the electric power propulsion ship, and may have a profound impact on the high‐performance advanced ships and green shipping industry as well. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we aim to clarify the effectiveness of a thermal‐based sensor, which applies image recognition technique to thermal image to measure occupancy state. Our experiment, which was conducted at a single private office over 8 days, evaluated both energy‐saving rate of occupancy control and F‐measure, which is the comprehensive metric of measurement accuracy. The thermal‐based sensor increased the F‐measure and energy‐saving rate by 2.23% and 27.91%, respectively, compared with the passive infrared sensor, which measures the occupancy state on the basis of change in infrared temperature. Compared with an image‐based sensor, which applies image recognition technique to visible image, it can provide high privacy and security preserving capability and detect occupants under completely dark environment. However, the F‐measure and energy‐saving rate were decreased by 3.13% and 19.07%, respectively. Further results and discussion are included herein toward analysis and improvement of the thermal‐based sensor. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With increase in the number of photovoltaic system installations, the prospect of voltage deviation from the acceptable range in a distribution system is increasing. Voltage distribution can be controlled using step voltage regulators (SVRs) and static var compensators (SVCs); however, for their coordination, it is necessary to stringently adjust the set value for each distribution line. In this study, a method of applying model predictive control to the coordination between an SVR and an SVC is investigated. In this paper, we first describe the proposed method and subsequently present the results of the performance comparison of the proposed and conventional methods to validate the effectiveness of the proposed method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Asymmetric vibration‐based haptic devices are being developed to apply to various applications such as navigation systems. A mobile‐type three‐dimensional haptic device requires a compact structure. Then, we focused on a three‐degree‐of‐freedom oscillatory actuator (3‐DOFOA). However, conventional 3‐DOFOAs are large in size and weight because they need a large and complicated support mechanism on the outside of the magnetic circuit. Furthermore, they do not satisfy both the requirement of similar force characteristics in each axis and no interference. To address these issues, we propose a novel 3‐DOFOA integrated with a support mechanism that has equal static characteristics in each axis without interference. The proposed structure and operating principle are described in detail in this paper, as well as the force, frequency characteristics, and acceleration responses. As these results, it can be concluded that the proposed actuator is suitable for use as a haptic device. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we propose a modified Lipschitz optimization (LO) method and apply it to maximum power point tracking (MPPT) control for photovoltaic (PV) systems. The standard LO can find a global maximum of a Lipschitz continuous function over a closed interval in a deterministic way. However, the standard LO tends to evaluate low objective function values, and this feature leads to low MPPT efficiency in its application to MPPT control. The proposed method skips the evaluation of low objective function values (i.e., low power points) by using prior information on the output characteristics of a PV array. Moreover, we show theoretically that the proposed method guarantees convergence to a global optimal solution. We compare the proposed method with some of well‐known MPPT methods and verify its effectiveness through simulations. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Compared with traditional power plants, current main stream wind turbines vary in grid connection interfaces, resulting in deficiencies like weak grid voltage and frequency support capability. In order to solve the problem, a synchronous type variable speed wind turbine is proposed in this paper. The wind turbine has the advantages such as the intrinsic properties of maintaining grid voltage and frequency, no harmonic pollution on grid, black start capability. In the wind turbine drive train, an electrically excited synchronous generator is directly coupled to the grid. A power self‐balance type electromagnetic coupling device is used to connect the synchronous generator rotor shaft and a gearbox high speed shaft. The device is composed of a permanent magnet synchronous generator (PMSG), a back‐to‐back converter and an electromagnetic coupler. The converter with small capacity, supplied by the PMSG which is coaxial with the gearbox high speed shaft, is used to apply the electromagnetic torque of the electromagnetic coupler. The matching relationship between the electromagnetic torque and the turbine mechanical torque, and the power flow in the drive train in different wind speeds are analyzed. Control strategies are proposed for the wind turbine normal operation including start, stop, maximum wind power capture, and low voltage ride through (LVRT). Compared with the main stream wind turbines, blade and tower loads can be improved greatly during LVRT. A 2 MW wind turbine model is built in Matlab/Simulink to verify the control strategies proposed and the wind turbine excellent LVRT performance. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Hybrid direct current circuit breakers (DCCBs) have become prominent because of their low on‐state power dissipation and small arc erosion compared with conventional semiconductor and mechanical circuit breakers (CBs). After a fault occurs in a DC circuit, the current commutates from the mechanical contacts to the semiconductor devices of the hybrid DCCB, and finally, the current is interrupted by the semiconductor devices. Thus, a low turn‐on voltage or a low on‐state resistance of the devices is needed to reduce the commutation time and power dissipation of the current interruption. This paper presents a comparison of DCCB performances metrics, such as the maximum interruption current, power dissipation, and junction temperature, using a silicon carbide metal‐oxide‐field‐effect transistor (SiC‐MOSFET) and silicon insulated‐gate‐bipolar transistor (Si‐IGBT) module. An interruption of 1.1 kA was achieved in 4.3 ms using the SiC‐MOSFET module of which rated current was 444 A. The junction temperature after the interruption was determined to be 275°C, which exceeded the maximum junction temperature of 175°C. In the case of the Si‐IGBT module of which rated current was 1110 A, the maximum interrupting current was limited to 900 A; however, the maximum junction temperature was 41°C. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, the three‐dimensional fluid field‐temperature field coupled model of air core reactor is established, the detailed temperature field distributions of reactor can be obtained, and the reason about the temperature rise of reactor is significant increased when adding the rain cover is given by analyzing the flow velocity of fluid in the air ducts. Considering the natural air cooling no longer meets the temperature rise requirement of the reactor, the forced air cooling is performed by installing ventilation duct and fan at the bottom of the reactor, combined with the finite element method and central composite experimental design method (CCD), the influence of structure parameters of rain cover and ventilation duct on the temperature rise of reactor are analyzed, meanwhile, the response surface model is established, which reflects the relationship between the temperature of reactor and the structure parameter of rain cover and ventilation duct, and the optimal design parameters can be obtained based on the quantum genetic algorithm, the maximum temperature of the reactor is only 59.3°C, the difference between the prediction of response surface and simulation result is only 0.1°C, and the correctness of the optimization method is validated, which provides an important guiding significance for the safe and stable operation of reactor in the system. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper introduces a variable magnet switched reluctance motor (VM‐SRM) drive that can be characterized with adjustable performance. It consists of a switched reluctance (SR) motor with low coercive force (LCF) magnets buried on stator yoke and a modified asymmetric half bridge (AHB) converter. Magnetization level of the LCF magnets is adjusted by injecting a current pulse to a phase winding of the VM‐SRM. The magnetization process does not need any extra coil and provides a simplicity owing to modified AHM converter. Possible magnetic saturation that limits the magnetization level is overcome by injecting current pulses to two phase windings at the same time. Thus, LCF magnets can be used with their full capacity. The presented analysis results demonstrate that proposed VM‐SRM drive provides a variable performance and might be a candidate for future variable speed applications. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The database‐driven proportional‐integral‐derivative (PID) control method, which is an online adjustment method of PID parameters for nonlinear systems, has a long calculation time and is difficult to apply to industrial machines. In this paper, a novel practical online adjustment method for PID parameters is proposed. The proposed method can be applied to industrial machines while adopting the database‐driven approach. According to the proposed method, the overall calculation cost can be reduced by performing the online adjustment operation of the PID parameters in a slow cycle different from the calculation of the control output. In addition, PID parameters can be learned offline manner using the one‐shot experimental data group corresponding to each shot. The learning method can adopt the extended fictitious reference iterative tuning (E‐FRIT), which calculates control parameters directly from closed‐loop data. Then, the database is updated while maintaining a certain amount of database size. The learned data are added to the existing database, and similar data are discarded using the cluster analysis method. Finally, the effectiveness of the proposed method is verified by a numerical simulation of the time‐variant system. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Monte Carlo tree search (MCTS) algorithm to solve the protein folding problem in HP model. There are two main challenges. First, the problem is proved to be NP‐complete. The solution space is large and it is hard to find a good solution via a search algorithm without prior knowledge of the HP model. We tackle this challenge by formulating the problem as a deterministic Markov decision process (MDP) and solve it in an AlphaZero's manner. The difference is that we design a MCTS algorithm with two stages: neural exploitation stage and random exploration stage. In the first stage, the search algorithm utilizes the knowledge from previous experience by evaluating the states with a trained neural network, while in the second stage, the states are evaluated by fast and random rollouts. It effectively reduces the number of neural inferences and computational cost. The second challenge is that the evaluation of typical MCTS cannot preserve the correct preference over the actions in our task. To address this challenge, we propose an over‐sampling mechanism that encourages the agent to search more on those actions with high rollout values. The proposed method is tested and compared in a series of experiments. Experimental results have confirmed the effectiveness of the proposed method empirically. Besides, we also visualize the obtained the best conformations and verify the proposed technical designs through an ablation study. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In order to reduce the torsional vibration of the turbo‐generator shaft and improve the stability of the power system, this paper proposed a more stable shafting structure model of Double ended Driving Turbo‐Generator (DDTG) by improving the shafting structure of conventional turbo‐generator set. For DDTG, the mechanical power is supplied symmetrically and synchronously from both ends of the generator. Compared with the conventional Single ended Driving Turbo‐Generator (SDTG), simulation results verify the effectiveness of the proposed shafting structure model, and indicate that DDTG can effectively reduce the torsional vibration of turbo‐generator shafts under the same electrical disturbance. Besides, in order to further suppress the torsional vibration of turbo‐generator shafts and improve the system performance, based on the nonlinear control method with objective holographic feedback, a Coordinated Control law of Excitation and Steam‐Valve (CCESV) is proposed. Under the action of CCESV, the simulation results show that the restraint effect of the DDTG on shafting torsional vibration is more obvious, and the dynamic and static performance of the system can be effectively improved. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper introduces an optical orthogonal frequency division multiplexing (OFDM)‐based hyperchaotic key generation encryption approach that can improve confidentiality in visible light communication (VLC) networks. Using a hyperchaotic four‐dimensional method, the bipolar real‐valued OFDM signal can be used for constructing dynamic cipher keys modified at every frame over the communication time, resulting in a superior degree of protection against malicious attacks. In accordance with our findings, this approach decreases the ratio of peak‐to‐average power of the transmitted signal, and enhances the bit error rate efficiency and secrecy capacity of the OFDM‐based VLC network, which improves confidentiality. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

SF6 is a greenhouse gas. Finding an alternative gas for SF6 has become an urgent problem in the switch field. In order to explore the feasibility of replacing SF6 gas with dry air directly, CO2 and C4F7N/CO2 mixed gas, based on the KYN28‐12 medium voltage switchgear, the finite element method was used to solve the three‐dimensional coupled multi‐physics of the switchgear in this paper. From the angle of the temperature field and flow field, the temperature rise characteristics under different operation conditions were analyzed. The results showed that the temperature field and flow field distribution under the four gases were similar. Among them, the temperature rise of SF6 gas was the smallest, followed by the C4F7N/CO2 mixed gas, CO2 and dry air. The flow rate of SF6 gas was the lowest, about 0.11 m/s. The flow velocities of other gases were relatively close. When the switchgear was filled with the same gas, as the inflation pressure increased, the temperature rise of the switchgear decreased and the gas flow rate also dropped to a certain extent. The temperature field and flow field of the switchgear under the C4F7N/CO2 mixed gas at 0.2 Mpa were similar to those under the 0.1 Mpa SF6 gas. Under the C4F7N/CO2 mixed gas, the contact failure of the plum contact made the temperature rise of the switchgear increase overall. The maximum temperature rise point transferred to the contact failure. The temperature rise further rose with the increase of the contact failure degree. The gas flow rate also greatly increased with the failure degree elevated. From the perspective of temperature rise, the C4F7N/CO2 mixed gas has the possibility of being applied in the electrical equipment under the premise of meeting the insulation conditions. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In order to provide guidance for demand‐side management and improve energy efficiency, the accuracy of residential electricity demand forecasting plays a significant role. Data‐driven methods and deep learning network methods have been proved an effective methods for time series forecasting. In the context, the current research work proposes a novel neural network model based on convolutional neural network (CNN)‐attention‐bidirectional long‐short term memory (BiLSTM) to predict residential energy consumption. The proposed approach combines CNN, attention mechanism, and BiLSTM, initially implementing CNN to extract the effective features of the original data. Subsequently, the extracted segments are employed as the input of attention‐BiLSTM to predict energy consumption, where the attention mechanism comprehensively considers the output of BiLSTM neurons and assigns weights to neurons at each timestamp. In this article, we evaluate the proposed method using household electricity consumption data. This paper selects different input timestamp lengths (10/60/120 min, respectively) to validate the model's performance. We compare evaluation indicators (root mean square error, mean absolute error, mean absolute percentage error [MAPE]) between the proposed method and the state‐of‐the‐art prediction methods. The experimental result shows that the proposed method achieves higher energy consumption forecasting accuracy and has the lowest average MAPE (3.7%). © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper deduces an exact model of analytical calculation for the multilayer rotor eddy current losses of high‐speed permanent magnet machines based on the subdomain method. The analytical calculation model solution domain is divided into six parts of subdomains, including permanent magnet, shielding layer, metal retaining sleeve, air gap, slot openings, and windings. The Laplace equation of the air subdomain and the diffusion equation of the eddy current subdomain and the windings subdomain are established with the vector magnetic potential as the independent variable. The eddy current losses of the permanent magnet, shielding layer, and retaining sleeve of the multilayer rotor are calculated considering the slots effect and eddy current reaction. This analytical model is used to study the interfering factors of the multilayer rotor eddy current losses including the shielding layer thickness, carrier ratio, and modulation ratio. Finally, the correctness and regularity of the analytical calculation model are proved by finite element analysis and machine experiment analysis. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, a new dc to dc boost converter with triple voltage gain and single switch is proposed for low power high voltage applications, analyzed for both ideal and non‐ideal conditions, and compared with the existing topologies. The converter belongs to the family of single‐stage high‐gain non‐isolated dc to dc converter. The design of the inductor, capacitors and the power losses in the circuit are discussed in detail, the output voltage gain of the proposed converter is compared with the output voltage gain of the other recent topologies of high‐gain DC/DC converters. To verify the theoretical results, a laboratory hardware prototype is developed and tested. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The use of PLC (power line communication) is growing as the adoption of IoT technology becomes more widespread. However, the maximum communication distance between PLC modems cannot yet be clearly defined since the communication characteristics of the power lines used for PLC are not formally specified. In this paper, the propagation characteristics in the high‐speed PLC communication band of 2–30 MHz were investigated when equipment is not connected to the power line except both ends. The line constants for five typical types of cables used as single‐phase and two‐wire power lines were measured. Our results showed that different cables have markedly different transmission characteristics. The attenuation constant varied up to fourfold depending on the cable insulator material. We also derived a method of estimating the communication distance for different cables for application of the HD‐PLC system, which is the most commonly used type of high‐speed PLC. The measurement result by using VCT cable was almost agreed with the estimated value. By comparing the estimated distance with the experimental results, we show that the transmission distance can be estimated with sufficient accuracy for practical use. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Jams in the tripping devices are common faults in circuit breakers, which will lead to the failures in circuit breaker. The resist force of the coil plunger in the tripping device could effectively reveal the jam faults. In this paper, a recognition method for the coil plunger motion resist force based on coil current is proposed. The electromagnetic motion model of the coil is established, and the plunger resist force in VS1‐12 is recognized. According to the recognition result and the moving process of the coil plunger, the fitting formula of the resist force is proposed. The resist force from the coil is 5 N, while the force from the latch is 52 N. Based on the fitting formula, the trip coil current of the circuit breaker is simulated. The result is in good agreement with the test result, which verifies the validity of the fitting formula and the recognition method. The method can be applied to the circuit breaker with spring operating mechanism and effectively extract the resist force from the coil current. This research can provide reference for the condition detection and fault warning of coils in circuit breaker. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

There are various structures in the underground space, and the structures are managed as 3D data in underground geospatial information map system (UGIMS). However, there is a problem that takes a long time to load the data into a mobile app from UGIMS because the data are very large. In order to reduce the loading time of 3D data, the number of data vertices should be reduced within a range that can keep the shape of 3D object in a mobile app. In this paper, we try to reduce the number of vertices using a 3D Mesh Simplification method to reduce the loading time of data in a mobile app. The proposed method applies simplification by extracting refined vertex feature information using a deep learning encoder‐decoder based model and performing vertex clustering by grouping similar vertices together with the feature information using K‐means clustering. We were able to reduce the number of vertices by 30% compared with the previous data. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Deep residual network (ResNet), one of the mainstream deep learning models, has achieved groundbreaking results in various fields. However, all neurons used in ResNet are based on the McCulloch‐Pitts model which has long been criticized for its oversimplified structure. Accordingly, this paper for the first time proposes a novel dendritic residual network by considering the powerful information processing capacity of dendrites in neurons. Experimental results based on the challenging COVID‐19 prediction problem show the superiority of the proposed method in comparison with other state‐of‐the‐art ones. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we present a methodology to synthesize bone‐conduced (BC) speech. Without relying on commonly used techniques for speech synthesis, we consider to transform air‐conducted (AC) speech into BC speech. An infinite impulse response (IIR) filter is explored for the transformation. From the concept of system identification, the least squares (LS) method is employed and the IIR filter is designed through the recorded AC and BC speech data. By experiments, it is shown that the BC speech synthesis method is satisfactory. Filter model, order selection and stability in the methodology are discussed and noise‐robustness gained by the BC speech synthesis is also investigated. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Compared with multi‐phase single‐module permanent magnet motors, three‐phase multi‐modularized permanent magnet motors have stronger fault tolerance ability, widely used in aerospace, ship propulsion, and other special fields. Especially in ship direct‐drive propulsion, low speed and high torque modular combined stator fault‐tolerant permanent magnet motor (MCS‐FTPMSM) has high torque density, and fault‐tolerant operation conditions may appear in actual operation, so it is essential to analyze the temperature of the fault‐tolerant motor accurately. This paper analyzes the temperature of MCS‐FTPMSM under different operating conditions and determines the longest operating time of the motor under different fault‐tolerant operating conditions based on the 3D electromagnetic‐temperature bi‐directional coupling method. Among them, the loss of the motor is calculated by the 3D electromagnetic field, which is added to the 3D temperature field as an excitation, and then the material properties in the 3D electromagnetic field are updated according to the calculated temperature distribution. The cyclic iteration method is used to make the calculated temperature deviation less than the given error value. When analyzing the electromagnetic loss of the motor, the field‐circuit coupling method is adopted to consider the influence of the current time‐harmonics of the controller on the loss of the motor during actual operation. Finally, the 12kw100r/min 3 × 3 modular prototype was tested. By comparing the results of experiments, one‐way coupling method (OWCM) and bi‐directional coupling method (BDCM), it is found that the electromagnetic‐thermal bi‐directional coupling can more accurately predict the temperature of the fault‐tolerant motor. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In view of the poor performance of the traditional adaptive filtering algorithm in identifying sparse systems under impulse noise, an affine projection maximum correntropy criterion with compound inverse proportional function (APMCCCIPF) algorithm is proposed in this paper, and the compound inverse proportional function approaching l0 norm is introduced into the traditional affine projection maximum correntropy criterion (APMCC) algorithm. The fixed step‐size APMCCCIPF algorithm cannot obtain faster convergence speed and lower steady‐state error at the same time, and the most effective method to solve this contradiction is to change the fixed step‐size in the algorithm to a variable step‐size. Further, a variable step‐size factor is constructed in the APMCCCIPF algorithm, and a novel variable step‐size APMCCCIPF algorithm is proposed. A modified Gaussian function, which can resist impulse noise interference, is applied to adjust the step‐size change. Besides, the convergence and complexity of the proposed algorithms are analyzed. In the simulation of sparse system identification and echo cancellation under impulsive noise, the proposed algorithms not only achieve a lower and faster convergence rate, but also obtain a lower steady‐state error. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

An expected shortfall of supervised learning for medical imaging classification is the insatiable need for human annotation, which is very expensive. Further, for microscopic parasite images, the salient structures are generally fuzzy, and the insignificant textures are noising. This paper proposes a semi‐supervised classification method of three parasites and Erythrocytes microscopic images using a large amount of unlabeled data and a small amount of labeled data for training. It contains a feature extractor trained by contrastive learning and a classifier optimized by Laplacian Support Vector Machine (LapSVM). First, for the deep Convolutional Neural Network feature extractor, we introduce real‐world images with similar and clear semantic information to enhance the structure at the representation level. In addition, we introduce variant appearance transformations to eliminate the texture at the representation level. Second, the gated linear network is adopted as the classifier to realize a piecewise linear separation boundary. The parameters are optimized implicitly by LapSVM using a kernel function composed of the representation and the gate control signals, which are generated from the learned feature extractor. The proposed method shows excellent performance when only 1% of the microscopic images are labeled. As a result, we achieve affordable and accurate diagnostic testing in parasite classification. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In the detection of protein complexes, the completeness of a protein–protein interaction (PPI) network is crucial. Complete PPI networks, however, are not available for most species because experimentally identified PPIs are usually very limited. This paper proposes a deep learning based PPI predictor to construct a complete PPI network, from which protein complexes are detected using a spectral clustering method. For this purpose, the unknown PPIs are estimated by using a deep PPI predictor consisting of a semi‐supervised SVM classifier and a deep feature extractor of the convolutional neural network (CNN). Meanwhile, the similarities of gene ontology (GO) annotations contribute to protein interactions, and the differences of subcellular localizations contribute to negative interactions. Considering that, we pretrain the deep CNN feature extractor in a class of deep GO annotation and subcellular localization predictors using datasets from the type species, then transfer it to the PPI prediction model for fine‐tuning. In this way, we have a deep PPI detector enhanced with transfer learning of GO annotation and subcellular localization prediction. Experimental results on benchmark datasets show that the proposed method outperforms the state‐of‐the‐art methods. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Many recent user behavior based click‐through rate models adopt a similar item‐level paradigm: learn the user representation from a list of item representations via a sequence model and/or a pooling mechanism. However, sequence models are usually sensitive to the exact order of the behavior sequence, while item‐level pooling mechanisms simply neglect the chronological information. In this paper, we balance the two approaches by decomposing the long item sequence into a group of extremely short sequences (item pairs) and conducting relational reasoning on them. More specifically, the relational reasoning mechanism consists of two parts, which are designed for capturing various transitional patterns in the behavior sequences. An attentive pooling layer is employed to emphasize those relation‐level signals that are highly related to the target item. Therefore, our approach is essentially a middle ground between the previous two approaches. To verify the effectiveness of our method, we conduct extensive experiments on three public datasets. Experimental results show that our methods achieve better performance than others. Besides, we explore the properties of our model and verify the effectiveness of each component by controlled experiments. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive backstepping controller is designed for the mecanum‐wheeled omnidirectional vehicle (MWOV) with frictions, external disturbances, and unknown slipping parameters. First, kinematic and dynamic models of the MWOV with wheels' slipping are derived. Especially, the virtual neural networks are introduced to on‐line approximate the nonlinear uncertainties of the dynamic system. Then, the adaptation laws with σ‐modification are employed to estimate the unknown parameters. Furthermore, based on the backstepping technology, an adaptive backstepping controller is synthesized with the updated values, and stability and robustness of the proposed control scheme are analyzed via the Lyapunov theory. Finally, comparative simulation results demonstrate the effectiveness of the proposed method. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

As an important part in the power systems, the status of the distribution network affects the safety, reliability, and economy of the whole power supply. When a fault occurs in the distribution network, it is of great significance to accurately and quickly locate the fault. At present, a cost‐effective synchronous phase measurement unit (PMU) device has been developed for the monitoring of the distribution network, which has opened up a new path for fault location in the distribution network. In this paper, the fuzzy clustering algorithm is used to judge the fault section, and the multiple fault information is extracted for fusion, so that the fault characteristic index can highlight the fault information. Then a new method based on multi‐terminal PMU data to realize the fault location of the distribution network is proposed. This method realizes fault location through the relationship between multiple fault indexes, and the simulation verification of PSCAD/EMTDC shows the accuracy and effectiveness of the method. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Power transformer rooms have been gradually installed in residential buildings due to an increasing demand for power supply and space requirement. However, the noise generated by transformers during operation has become a hot topic of complaints. In order to solve the problem of transformer noise pollution and explore the rules of noise for power transformer rooms, a portable noise monitoring system consisting sensor array and a vibration and noise tester is developed in this paper. The noise characteristics of a power transformer room in Guangzhou city are obtained through field tests, which include the time‐domain characteristics, spectrum characteristics, and A‐weighted sound level characteristics. Results show that the frequency component of noises is stable, but the amplitude varies. The sound pressure of the power transformer room has obvious periodicity and the amplitude is 0.1–0.2 Pa. The dominant noise frequency is fixed at 300 Hz. According to different positions, the A‐weighted sound level is distributed between 55 and 65 dB. The research is not only of great help to formulate transformer noise assessment methods, but also of great significance to improve people's living environment and ensure power system's reliable operation. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The oil chromatography online monitoring system can monitor the insulation status of power transformers continuously and real‐time. The accuracy of its detection data directly affects the stable operation of the transformers. Aiming at the problem of abnormal data in the current transformer online monitoring data set, this paper proposes an online oil chromatographic data processing method based on association rules and support vector regression (SVR) analysis. First, using piecewise linearization to convert numerical variables into Boolean variables, and then exploring gas indicators with strong correlations in oil chromatogram. Then, using the improved box plot method to detect the abnormal value points in it, and distinguish the data of different abnormal patterns based on the association rules. Finally, the advanced particle swarm optimization support vector regression (APSO‐SVR) algorithm is used to repair the data to improve the credibility of the data set. Using actual transformer oil chromatographic monitoring data for testing, the results show that the proposed data processing method can effectively improve the accuracy of oil chromatographic online monitoring data. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The induction machine (IM) has advantages of simple structure, low cost, reliable operation, and convenient maintenance, and the application of ultra‐high efficiency IM could effectively improve the energy utilization rate and realize the emission reduction. Therefore, in this paper, the radial skewed rotor and the stator energy‐saving winding are first designed to improve the efficiency of IM. Then the Taguchi method, differential evolution algorithm, sequential subspace multi‐objective optimization, and 6σ evaluation criterion are integrated to realize the multi‐objective robust optimization design (MOROD). In the proposed MOROD scheme, the combined surrogate model is also researched to reduce the calculation burden during the optimization process. Furthermore, the MOROD scheme is applied to the design of a 22 kW, four poles ultra‐high efficiency IM to validate its effectiveness. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

A spherical image has a full field of view. Using spherical images can estimate camera pose more accurately than conventional perspective images. It is known that a sphere can be quasi‐uniform sampled by dividing a geodesic dome repeatedly; it results in a representation with rotational invariance approximately. Based on this fact, in this paper we proposed a method of estimating a spherical camera pose based on the geodesic‐dome‐division‐based discrete spherical image representation by modifying the conventional perspective‐image‐oriented convolutional neural network, called PoseNet. First, a spherical image is represented as a geodesic‐dome‐division‐based discrete spherical image. Then, to cope with the six‐connectivity of the pixels of a geodesic‐dome‐division‐based discrete spherical image using the conventional convolutional neural network framework, the discrete spherical image is flattened as a connected five parallelograms and resampled as an eight‐connectivity image. Consequently, via the comparative experiments, it is found that the geodesic‐dome‐division‐based discrete spherical image representation approach can achieve a better result of camera pose estimation than equirectangular image and CubeMap representations. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The rapid growth of distributed energy resources integrated in distribution systems leads to an increasing need of continuously and automatically changing the system topology to realize the economic operation of distribution networks. This paper proposes an optimization model of dynamic reconfiguration for distribution networks based on a new method of time series analysis. Equivalent daily curve considering time‐varying nature of distributed generator and load demands is divided by an improved fuzzy C‐means clustering algorithm, where the indicator of section function is set to find the optimal reconfiguration time intervals. The uncertainty of distributed generator outputs and load demands is described by the interval algorithm. Then the affine Taylor expansion is adopted to solve the interval power flow equations. The reconfiguration optimization model is solved with decimal particle swarm optimization algorithm based on loop search. The optimal dynamic reconfiguration of a modified 70‐bus test system with distributed generators is carried out and the simulation results demonstrate the effectiveness and superiority of the proposed method. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper is concerned with the path following control for an underactuated unmanned surface vehicle (USV) subject to modeling error and input saturation under time‐varying external disturbances. In this note, a novel trajectory linearization control (TLC) method is first introduced in the design of path following controller for an unmanned surface vessel. Adaptive line‐of‐sight (LOS) algorithm is used in the navigation strategy, which not only solves the sideslip angle problem caused by external disturbances but also optimizes the convergence speed. The neural network minimum learning parameter (MLP) method is used to compensate for modeling errors and external disturbances. Compared with multi‐layer neural networks, MLP solves the problem of 'dimension disaster'. Meanwhile, in order to increase the robustness of the system, adaptive technology is employed to compensate for the compensation error of MLP. In addition, an auxiliary dynamic system is introduced into the controller design to address potential input saturation issue. Considering the above practical conditions, it is more convenient for the engineering implementation of the proposed control path following the control system. Using Lyapunov stability analysis theory, it is proven that all error signals in the system are uniformly ultimately bounded. Finally, two simulation experiments are presented to demonstrate the feasibility of the proposed control strategy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes a simple and efficient method to weaken the cogging torque of the direct‐drive permanent magnet motor with inner enhance force (IEF‐DDPMM). It is characterized by adjusting the relative position of the inner and outer permanent magnets so that the cogging torque generated by the inner and outer air‐gaps is opposite in phase, thus eliminating or weakening a certain order of cogging torque. For IEF‐DDPMM, the expression of cogging torque and the variation law of cogging torque with the staggered‐pole angle are derived by the analytical method. The relationship between optimal staggered‐pole angle and the pole‐slot combination is analyzed. The influence of staggered‐pole on average torque and torque ripple is analyzed. Finally, the commercial finite element software ANASYS‐Maxwell is used for simulation, and the simulation results are consistent with the analytical results. The results show that the cogging torque of IEF‐DDPMM is the linear superposition of cogging torque from inner and outer parts; choosing a suitable staggered‐pole angle can effectively weaken the cogging torque and reduce the torque ripple. Besides, the average torque reduction caused by the staggered‐pole method can be compensated by adopting the internal power factor angle compensation strategy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes a multiparameter estimation method for surface‐mounted permanent magnet synchronous machine (SPMSM) under constant load torque, of which the variations of dq‐axis inductances and rotor flux linkage have been taken into consideration. Second, the voltage equations will be transformed to eliminate the distorted voltage caused by the voltage‐source inverter nonlinearity. On this basis, an improved variable‐step Adaline neural network algorithm based on hyperbolic tangent function is proposed to estimate the parameters of SPMSM online, which can increase the convergence speed and reduce the steady‐state errors compared to the traditional algorithm. Finally, in view of the high sensitivity of inductance, another new method that can reduce the fluctuation rate is proposed. In addition, the effectiveness of these methods is verified through experiments on a small‐power SPMSM. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we address the task of segmenting small organs (i.e., the pancreas) from abdominal CT scans. As the target often occupies a relatively small region in the input image, deep neural networks can be easily confused by complex and variable backgrounds. We propose a method that uses a parallel multi‐scale network with an attention mechanism for pancreas segmentation, which can better grasp the balance between the semantic segmentation, classification, and localization tasks. We use a parallel network to connect the feature maps between different bottleneck layers, which contain rich semantic information and complete spatial information. We apply an attention module to enhance the key features of semantic information. Then, we fuse the two modules and apply the fused module as attention information on the feature map to ensure the full fusion between contextual semantic information and spatial information, thereby improving segmentation accuracy. We conduct extensive experiments on the NIH pancreas segmentation data set. In particular, our model achieves a mean coefficient Dice of 86.6. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper reports the AC dielectric‐breakdown characteristics of a rice‐oil‐based electrical insulating oil as a function of oil temperature as well as the influence of thermal degradation on its performance (kinematic viscosity, AC dielectric breakdown, moisture amount, total acid number, and pour point). We manufactured rice ester oil using the ester‐exchange reaction. The results demonstrated the following. (i) The kinematic viscosity of the rice ester oil was lower than that of the rice and mineral oils. (ii) The AC breakdown strength of the rice ester oil was higher than that of the mineral oil. The AC breakdown strength of both insulating oils increased with the increase in the oil temperature. (iii) The moisture content of the rice ester oil was larger than that of the mineral oil. (iv) The total acid numbers of the rice ester and mineral oils were almost the same. (v) The pour point of the rice ester oil was higher than that of the mineral oil. In addition, the rice ester oil exhibited high resistance to heat stress compared with the mineral oil, but the former was unsuitable for use in cold climates. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

To solve the problem of battery capacity degradation caused by high current magnitudes and frequent current variations in electric vehicles (EVs), a hybrid energy storage system (HESS) incorporating high energy density storage (battery) and high power density storage (ultracapacitor) is proposed. The HESS contains a multi‐port DC‐DC converter, which controls the energy flow among the battery pack, the ultracapacitor (UC) pack, and the port of output. Considering the state of charge (SOC) of UC, the speed, and demand power of EV, an energy management strategy (EMS) based on fuzzy logic control (FLC) for the HESS is proposed in this paper. According to the strategy, the battery pack serves as a base power source while the UC pack serves as a transient power source so as to smooth the battery pack current and prolong the battery life. Simulation and experiment results illustrate the effectiveness of the proposed strategy for UC/battery HESS in EVs. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive generalized dynamic inversion (AGDI) control methodology to the problem of angular position tracking of the rotary flexible joint system while suppressing joint vibrations. The AGDI control is composed of an equivalent control, which is responsible to enforce the prescribed constraint dynamics that encompasses the control objectives and control expression is obtained by inverting the constraint dynamics using Moore–Penrose generalized inversion. Furthermore, robustness is achieved by integrating a switching (discontinuous) term based on the sliding mode control method. The sliding mode gain of the switching control law is made adaptive for chattering reduction and improved tracking capability. The performance of AGDI control is evaluated through both numerical simulation and experimental investigations executed on Quanser's rotary flexible joint system. Simulation and experimental results reveal that the AGDI control is quiet capable to achieve the desired response curves against set‐point tracking and disturbance rejection scenarios. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Dusty weather is a most important disturbance for photovoltaic (PV) systems, that may result in PV panels exposure to partial shading conditions where the PV panel characteristics show several maximum power points. Moreover, dusty weather conditions may lead to rapid changes in solar radiations. Thus, conventional power system tracking algorithms are not being capable to track the global maximum power point (GMPP). This paper provides an advanced maximum power point tracker for partial shading and dusty weather conditions. In the presented technique, scanning and power lock conditions are added to the conventional perturbations and observation technique in photovoltaic system under partial shading or dusty weather conditions. This tracking method scans the PV characteristic in steps and stores all the maximum power points in order to get the GMPP. The proposed tracker is capable to identify the uniform weather conditions to save it from having unnecessary scanning. In addition, this tracker permits dynamic tracking of the GMPP under dusty weather conditions with less fluctuations and stable operation compared to the conventional methods. Accurate and fast conversion to the GMPP during various weather conditions is accomplished using the proposed technique. The proposed modified perturb and observe technique is validated using simulation and practical results. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes an analytical no‐load magnetic field model taking account of the curvature coefficient to compute the no‐load magnetic field of parallel direct‐driven conjoined permanent magnet synchronous motor (PDC‐PMSM). The shortcomings of the 3‐D finite element method are avoided, such as the time‐consuming and sensitive to finite element meshes. As well as, putting forward the design method of the motor. A 2‐D subdomain model of PDC‐PMSM can be obtained by segment 3‐D model at the average radius, which is quasi to linear permanent magnet synchronous motor. Based on Maxwell's equations, the Poisson's equations in the permanent magnet (PM) subdomain and the Laplace's equations in the subdomain between air gap and PM are calculated under no‐load condition. The radial and tangential flux density of each subdomain are obtained by the Fourier's series, hyperbolic functions, separation of variables, and the boundary condition. Better yet, the curvature coefficient is introduced to reduce the error between the analytical magnetic field in the planar model and the tubular model. The analytical no‐load magnetic field model is established more accurately. The expression of curvature coefficient and back‐electromotive force are derived. One prototype is manufactured for simulation and experimental study. The accuracy and feasibility of the proposed model are verified by the prototype test. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Intrinsic localized mode (ILM) can be generated in multiple mass‐spring systems using nonlinear springs, and ILM has attracted a lot of attention due to its special vibration modes that are not found in linear systems. However, the difficulty of creating nonlinearity remains a barrier to ILM research. In this paper, we propose a rotating magnetic spring based on magnetic nonlinearity. The nonlinear restoring properties of the proposed magnetic spring are confirmed by finite element method (FEA). Finally, using the restoring properties obtained from FEA, it is shown that ILM can be excited by MATLAB numerical analysis. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

To analyze crystal defects in polycrystalline silicon substrates, it is necessary to measure the crystal orientation at high speed. In this paper, we propose a method for simultaneous and fast estimation of the crystal orientation of an entire substrate by measuring the reflected light from a single rotation of a light source. The effectiveness of the proposed method is verified by the orientation estimation experiments. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Various control methods which utilize online optimization have been developed. A quadratic programming (QP) problem is typically solved online in such methods. In this paper, we derive a regional sector condition for a QP problem. Then, based on the regional sector condition, we derive a condition to analyze regional l2‐performance of a feedback system with QP. The analysis condition is expressed as a set of linear matrix inequalities. Then, we show methods for applying the analysis condition to a model predictive control system and a feedback system with a control allocator. A numerical example is provided to show effectiveness of the result. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents a reservoir computing technique using Asynchronous Block‐Based Neural Networks (ABBNN). Echo State Networks and Liquid State Machines introduced a new paradigm in artificial neural networks (ANN), known as Reservoir Computing (RC). A recurrent neural network (RNN) in Reservoir Computing is generated randomly, and only a readout is trained. The reservoir computing greatly facilitated the practical RNN application and outperformed classical RNN in many tasks. ABBNN is an extended version of the classical block‐based neural network model. ABBNN, an evolvable neural network model, provides a model‐free estimation of nonlinear dynamical systems. To propose a hardware‐aware model of reservoir computing and high‐speed training, we introduce Block‐Based Reservoir Computing (BBRC). BBRC provides a flexible architecture. The architecture based on the basic blocks provides a regularity that supports scalable hardware. In contrast, BBRC also supports randomness based on the internal configuration. Both are significant features in achieving an optimal hardware reservoir computer. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents a parameter estimation based method to diagnose winding deformation and turn‐to‐turn fault of power transformers. First, an estimation model of transformer parameters is built, in which five equations are taken in account including voltage loop equation, active loss equation, input impedance equation, no‐load current equation and no‐load loss equation. Then, particle swarm optimization (PSO) is used to solve the model, and the characteristics of estimation data under winding faults are analyzed. At last, based on the estimation data, random forest (RF) algorithm is employed to classify transformer states and realize fault diagnostic. The simulation results show that the proposed parameter estimation method has high precision and are not affected by the factors including load power factors and the type and degree of winding deformation, and the impact of load rates can be avoided; the fault diagnostic scheme based on RF is quite sensitive and effective. The proposed method eliminates the need of transformer outage, and compared with other methods based on parameter estimation, it can distinguish winding deformation and turn‐to‐turn fault. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]