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Stochastic PWM methods to inhibit junction temperature rise in IGBT module
Zihui Liu,Jiaqing Ma,Zhiqin He,Qinmu Wu 전력전자학회 2024 JOURNAL OF POWER ELECTRONICS Vol.24 No.4
The insulated gate bipolar transistor (IGBT) module is a core component of high-power electronic device systems. Since the junction temperature of an IGBT module increases with operation, the junction temperature of the IGBT module is the main cause of failure, which seriously affects the safe and stable operation of systems. To restrain the junction temperature and to improve the reliability of IGBT modules during operation, a new stochastic pulse width modulation (PWM) strategy is proposed. It is deduced that this method can do a good job of restraining the junction temperature of IGBT modules. The effectiveness of this method is verified on an experimental platform of a permanent magnet synchronous motor system. Experimental results show that the stochastic PWM has a good inhibitory effect on the junction temperature of IGBT modules in the same cycle, and that the difference of the most significant inhibition effect is about 3.27 K. The proposed stochastic PWM has practical engineering significance in terms of restraining the junction temperature of IGBT modules.
TENG ZIHUI,신선민,김기애,이연정,심아윤,김경진,Amgalan Natsagdorj,Zhijun Wu,Atsushi Matsuki,송미정,김창혁,장경순,이지이 한국대기환경학회 2021 한국대기환경학회 학술대회논문집 Vol.2021 No.10
In this study, to understand the characteristic of the composition of organic compounds in PM2.5 and to evaluate major factors for determining organic aerosols in Northeast Asia, the PM2.5 filters were collected simultaneously at three major urban sites (Ulaanbaatar, Beijing, Seoul) in Northeast Asia from Dec. 15, 2020, to Jan. 15, 2021. The samples were extracted using the organic solvent and then analyzed by GC-MS to obtain n-alkanes and PAHs concentrations. Total n-alkanes concentration in Ulaanbaatar (209±156 ng/m³) presented about five times as high as Beijing (46.8±23.5 ng/m³) and about six times as high as Seoul (35.6±6.63 ng/m³). For PAHs, Ulaanbaatar showed extremely high values as 609±378 ng/m³, which is 24 times as high as Beijing (25.8±14.5 ng/m³) and 46 times as high as Seoul (13.2±3.47 ng/m³). It indicated that the emission from fossil fuel combustion was the most significant in Ulaanbaatar during the winter period. From the contribution of plant wax (WNA%) and carbon preference index calculated from n-alkanes, it can be suggested that aerosol in Ulaanbaatar had the most significant contribution from anthropogenic emission than biogenic emission. From this study, the contribution of anthropogenic emissions for three sites will be compared.
New results on the pseudoredundancy
Marcus Greferath,Zihui Liu,Xin-Wen Wu,Jens Zumbragel 대한수학회 2019 대한수학회보 Vol.56 No.1
The concepts of pseudocodeword and pseudoweight play a fundamental role in the finite-length analysis of LDPC codes. The pseudoredundancy of a binary linear code is defined as the minimum number of rows in a parity-check matrix such that the corresponding minimum pseudoweight equals its minimum Hamming distance. By using the value assignment of Chen and Kl\o ve we present new results on the pseudocodeword redundancy of binary linear codes. In particular, we give several upper bounds on the pseudoredundancies of certain codes with repeated and added coordinates and of certain shortened subcodes. We also investigate several kinds of $k$-dimensional binary codes and compute their exact pseudocodeword redundancy.
NEW RESULTS ON THE PSEUDOREDUNDANCY
Greferath, Marcus,Liu, Zihui,Wu, Xin-Wen,Zumbragel, Jens Korean Mathematical Society 2019 대한수학회보 Vol.56 No.1
The concepts of pseudocodeword and pseudoweight play a fundamental role in the finite-length analysis of LDPC codes. The pseudoredundancy of a binary linear code is defined as the minimum number of rows in a parity-check matrix such that the corresponding minimum pseudoweight equals its minimum Hamming distance. By using the value assignment of Chen and Kløve we present new results on the pseudocodeword redundancy of binary linear codes. In particular, we give several upper bounds on the pseudoredundancies of certain codes with repeated and added coordinates and of certain shortened subcodes. We also investigate several kinds of k-dimensional binary codes and compute their exact pseudocodeword redundancy.
Fuzzy Approximation-Based Backstepping Control of Permanent Magnet Synchronous Motor
Zhang Yufeng,Yan Qi,Huang Nan,Wu Zihui,Gong Hao,Du Guanghui 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3
A permanent magnet synchronous motor(PMSM) control system based on backstepping control can effectively improve the dynamic performance, and the design process is simple and easy to be implemented in engineering. However, factors such as changes in motor parameters due to environmental changes, wear and aging, and external load disturbances can adversely affect the control system, resulting in degraded control performance. To address this problem, this paper proposes a fuzzy approximation-based backstepping control method for PMSM. The method constructs a mathematical model containing the perturbation term of the PMSM body parameters and the load disturbance term. And the universal approximation property of the fuzzy logic system is used to approximate the disturbance terms in the model, based on which a backstepping controller satisfying the stability requirements is designed. Finally, the simulation and experiment are given, which compare with the traditional backstepping method. The results show that the proposed method can effectively suppress the adverse effects of motor parameter changes and load disturbances on the motor control system.
Few-shot transfer learning with attention for intelligent fault diagnosis of bearing
Yao Hu,Qingyu Xiong,Qiwu Zhu,Zhengyi Yang,Zhiyuan Zhang,Dan Wu,Zihui Wu 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.12
The bearing is one of the key components in modern industrial equipment. In the past few years, many studies have been carried out on bearing diagnosis through datadriven methods. However, there are two practical problems. First, under actual working conditions, the lack of fault samples is a major factor that hinders the application of these methods in industrial environments. Second, there is a lack of full utilization of a priori knowledge in the current stage of methods using relational networks for fault diagnosis. It is manifested by the incompleteness of the relational network structure. To address these problems, we present a new diagnosis method based on few-shot learning, which is suitable for the environment where the data is scarce. In this method, we train the model with the data generated by the artificial damaged bearings instead of the data from the real bearing. We experimentally validate the performance improvement of the complete relational network structure. It is able to perform the few-shot learning task better. In addition, we also reduce the global feature discrepancy by introducing an attention mechanism to improve the performance of the model. And the impact of the number of layers of the attention mechanism on the model is also discussed in detail. In this paper, our model performs better under the same experimental conditions compared with other transfer learning models.