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| 1 | Suppression of growth and migration by blocking the hedgehog signaling pathway in gastric cancer cells显示文摘 | Runwei Yan Xiang Peng Xiaogang Yuan Dengliang Huang Jiang Chen Quqin Lu Nonghua Lv Shiwen Luo | 2013 | Cellular Oncology2013，，5： | 1 |
| 2 | Suppression of growth and migration by blocking the hedgehog signaling pathway in gastric cancer cells显示文摘 | Runwei Yan Xiang Peng Xiaogang Yuan Dengliang Huang Jiang Chen Quqin Lu Nonghua Lv Shiwen Luo | 2013 | Cellular Oncology2013，，5： | 1 |
| 3 | Suppression of growth and migration by blocking the hedgehog signaling pathway in gastric cancer cells显示文摘 | Runwei Yan Xiang Peng Xiaogang Yuan Dengliang Huang Jiang Chen Quqin Lu Nonghua Lv Shiwen Luo | 2013 | Cellular Oncology2013，，5： | 1 |
| 4 | Physics Informed Neural Network-based High-frequency Modeling of Induction Motors显示文摘The high-frequency(HF)modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system.In this study,a physics informed neural network-based HF modeling method,which has the merits of high accuracy,good versatility,and simple parameterization,is proposed.The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy.The per phase circuit structure is symmetric concerning its phase-start and phase-end points.This symmetry enables the proposed model to be applicable for both star-and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa.Motor physics knowledge,namely per-phase impedances,are used in the artificial neural network to obtain the values of the circuit elements.The parameterization can be easily implemented within a few minutes using a common personal computer(PC).Case studies verify the effectiveness of the proposed HF modeling method. | Zhenyu Zhao Fei Fan Quqin Sun Huamin Jie Zhou Shu Wensong Wang Kye Yak See | 2022 | Chinese Journal of Electrical Engineering2022，8，4： | 0 |
| 5 | Impact of Motor Stator Winding Faults on Motor Differential-mode Impedance and Mode Transformation显示文摘Motor impedance and mode transformation have significant effects on the electromagnetic interference(EMI)generated in motor drive systems.Stator winding faults commonly cause motor failure;however,in their early stages,they may not affect the short-term operation of the motor.To date,EMI noise under the influence of premature stator winding faults has not been adequately studied,particularly the differential-mode(DM)noise due to the common-mode(CM)-to-DM transformation.This study investigates and quantifies the influence of stator winding faults on the motor DM impedance and mode transformation.First,the transmission line model of an induction motor is described based on the scattering(S)parameter measurements of each phase of the motor.It offers the flexibility to emulate different types of stator winding faults at specific locations and various severities,such that the impacts of the faults on the motor DM impedance can be easily estimated.Second,a test setup is proposed to quantify the CM-to-DM transformation due to the stator winding faults.The findings of this study reveal that even the early stages of stator winding faults can result in significant changes in the DM noise. | Fei Fan Zhenyu Zhao Huamin Jie Quqin Sun Pengfei Tu Zhou Shu Wensong Wang Kye Yak See | 2022 | Chinese Journal of Electrical Engineering2022，8，3： | 0 |
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