IEEJ Transactions on Electrical and Electronic Engineering最新文献

Crosswinds and transverse slopes of the road surface affect the motion of a ground vehicle as disturbances. The objective of this paper is to develop a method for estimating crosswind disturbances and lateral force disturbances caused by transverse slopes of the road surface under the variation of the vehicle speed. Firstly, a dynamical model of a vehicle is described as a Linear Parameter-Varying (LPV) system in which the value of the coefficient matrices vary with the vehicle velocity. Then, an algorithm to estimate the disturbance is derived based on Moving Horizon Estimation (MHE) and applied to the derived LPV system. Furthermore, a simple control law which counteracts the effects of the disturbances on the lateral velocity and the yaw rate in steady-state based on the estimates of the disturbances is presented. The effectiveness of the proposed method is demonstrated by a numerical example. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

In this paper, we consider an estimation problem of sideslip angle and cornering stiffness of a vehicle from measurements of yaw rate, lateral acceleration and steering angle. Firstly, a vehicle dynamical model is expressed as a linear parameter-varying system with cornering stiffness as uncertain parameters. Then, we show a method to estimate the parameters and the state based on moving horizon estimation. We provide a simple algorithm to solve the estimation problem. The effectiveness of the estimation method is evaluated through numerical simulations. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Since ripples in hippocampal CA1 diversify with episodic experience to increase information entropy, we hypothesized that ripples contain local waveforms (shapelets) that episodic memories are encoded. Finding shapelets from ripples of rats that experienced an episode contributes to verify our hypothesis. In this letter, to find key shapelets from ripples, we proposed a method consisting of k-shape for clustering time-series waveforms, shapelet transform to classify time-series waveforms, and L₁ regularized logistic regression to select key factors for classification in shapelet transform. Among these, k-shape and shapelet transform should be improved because k-shape has a restriction that lengths of time-series waveforms must be the same, and similarity criteria of time-series waveforms in the both methods are inconsistent. To solve the problems, we improved functions defined as similarity between time-series waveforms. Our experimental results showed that the proposed method was able to find key shapelets from ripples. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Tactile paving is a ground-texture display device installed on sidewalks to guide visually impaired people. In recent years, many studies have been conducted on tactile paving detection using cameras to help visually impaired people walk independently. In addition, several computer vision-based tactile paving detection methods have been proposed. However, it is difficult to compare the detection accuracy of different proposed algorithms because there are no publicly available tactile paving datasets, and the ground truth and evaluation criteria used for evaluation are often inconsistent or not clearly presented. To this end, in this paper, we collect a tactile paving dataset and name it ‘Tenji10K’. The dataset is constructed with 20 sequences consisting of 10 K first-person tactile paving images taken in Japan, and ‘Tenji block’ refers to Japanese-style tactile paving. For detailed evaluation analysis, up to six sequence attributes are assigned, taking into account various real-world situations. On the other hand, we also proposed a tactile paving tracking algorithm based on an evolutionary algorithm. The effectiveness of the dataset is evaluated by conducting a comparative experiment based on Tenji10K with respect to four different methods, including our proposed method. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

This paper introduces EmoBone, a comprehensive audio-only emotional bone-conducted speech dataset featuring speakers from various countries. The dataset comprises speeches from 28 individuals representing 10 different nations, with each participant delivering 10 sentences designed to evoke distinct emotions. In addition to an air-conducted microphone, the recordings utilized bone conduction technology, transmitting sound directly to the speakers' inner ears, ensuring high-quality emotional speech recordings. To assess the validity of the dataset, 80 university students from Bangladesh listened to the recordings and successfully identified the expressed emotions with an accuracy exceeding 76%. Statistical methods were also employed to evaluate the reliability of the dataset, revealing a high level of agreement among raters. EmoBone, with a cumulative duration surpassing 19 h and 15 680 unique utterances, stands as the most extensive emotional speech dataset available. This makes it a valuable tool for studying how emotional speech varies across cultures. Furthermore, due to its utilization of bone conduction technology, EmoBone facilitates the study of acoustic features in emotional speech from diverse dimensions. The data that supports the findings of this study is available upon reasonable request. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Aiming at the problem of electrical life prediction of AC contactor individual, considering that characteristic information and degradation trend of different life stages are different, a comprehensive electrical life analysis method is proposed. First, based on uncertainty reasoning, initial electrical life is qualitatively evaluated to realize an early warning for contactor with poor performance. Secondly, real-time monitoring of performance degradation inflection point is used to realize the determination of degradation stage. With degradation stage matching mechanism, the quantitative prediction of remaining useful electrical life is realized based on performance inflection point and Elman neural network, thus forming an effective monitoring of the operation state in full life cycle. It is verified by experiment that the proposed method can accurately evaluate initial life grade and predict remaining useful life after performance inflection point. Compared with other methods, the information of electrical life for contactor individual can be accurately and comprehensively obtained. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

This study presents the development of a Pulse Height Analyzer (PHA) using an FPGA-based hardware platform, specifically the National Instruments MyRIO embedded device, for radiation detectors. Electronic pulses generated by the detector when exposed to radiation are triggered, digitized, and transferred to a data buffer. A pulse height analysis tool categorizes these pulses and stores pulse-height information in registers or channels, enabling the construction of a pulse-height distribution. The data of pulse-height distribution is then recorded on a computer via a user-friendly interface. The Pulse Height Analyzer was implemented using a 3-inch by 3-inch NaI(Tl) scintillation detector for gamma energy measurements, employing standard radioisotopes Na-22 and Co-60. Gamma energy spectra were acquired and analyzed. Our results demonstrate that the achieved energy resolution is comparable to that of the commercial Pulse Height Analyzers, such as EASY-MCA 2K, a product of AMETEK Inc. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

In the two-stage inverter system, due to the space vector modulation (SVM), the midpoint potential of active neutral point clamped three-level inverter system (ANPC-TLIS) will have triple frequency fluctuation, under the influence of the closed-loop control strategy, the fluctuation amplitude of the lithium battery energy storage system (LBESS) output current will increase. To reduce the low-frequency output current fluctuation, a voltage loop strategy based on active disturbance rejection control (ADRC) with notch filter (NF)is proposed in this paper. In this scheme, the voltage outer-loop control strategy not only maintains voltage stability, but also reduces the fluctuation amplitude of reference current. In addition, during the electromagnetic transient process, the LBESS output current fluctuation frequency is constantly changing because the power supply frequency required by linear motor is constantly changing. To solve this problem, the inverter output current frequency is feedforward to the LBESS controller, forming a variable frequency notch filter (VFNF). Finally, the effectiveness of the proposed strategy is verified by fixed-frequency and variable frequency conditions experiments on RT-LAB experimental platform. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

In this paper, we propose a cost-effective driver allocation scheme based on the Genetic Algorithm (GA) aimed at improving fuel efficiency for bus companies. With our evaluations using real bus sensing data, our scheme has demonstrated a significant reduction in running resistance, achieving a 20%–26% decrease compared to current real-world allocations. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The oil-immersed transformer is a crucial power equipment in power system, which is prone to abnormality or failure under long running. In order to improve the level of operation and maintenance and ensure the safe and reliable operation of the power grid, it is necessary to diagnose the fault of the oil-immersed transformer in time. Most of the traditional fault vibration methods are off-line detection, and are easily disturbed by mechanical deterioration. In order to solve the above problems, this paper established a 3D electromagnetic and stress coupling simulation model of oil-immersed transformer by finite element simulation software. The vibration characteristics of oil-immersed transformer core winding are obtained, and at the same time, this paper obtained the vibration signals at different positions on transformer core winding and oil tank. According to the vibration signal of the transformer, the best measuring point position of the tank wall is proposed to accurately reflect the vibration characteristics of the transformer. The signal data is preprocessed by CEEMDAN decomposition method, and the signal data is classified by GWO-BP composite classification algorithm. This paper proposed an online transformer fault diagnosis method based on vibration signal, which achieves the purpose of accurately diagnosing oil-immersed transformer faults. The test results show that in the case of oil-immersed transformers the accuracy of the proposed transformer fault diagnosis method is more than 93%, which provides important guiding significance for the safe and stable operation of the transformer. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.