TY - GEN
T1 - Fault Diagnosis of Inter-turn Short Circuit in Rotor Winding of Doubly-fed Generator Based on Data Fusion of Multi-flux Sensors
AU - Liang, Feng
AU - Chen, Yu
AU - Zhao, Shouwang
AU - Rehman, Attiq Ur
AU - Wang, Shuang
AU - Zhao, Yong
AU - Deng, Wei
AU - Ma, Yong
AU - Cheng, Yonghong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Inter-turn short circuit fault in doubly-fed generator is a common electrical fault that directly affects the normal operation of the wind turbine and endangers the safety of the grid connection. This paper proposes an inter-turn short circuit fault identification technology based on multi-flux sensor data fusion. A simulation experiment platform for the inter-turn short circuit fault of a doubly-fed generator with a power of 100 kW is used, consisting of a three-phase wound rotor induction machine, monitoring systems, frequency converters, and related control a drive motor. This experimental system can genuinely simulate the actual working conditions of the machine when the machine is short-circuited, and the experimental simulation can be closer to the operation process of the double-fed induction generator. The signal detection system is used to collect the external magnetic flux leakage signal of the motor. Flux sensors are placed in the axial and radial positions, then extracting the RMS value of each flux sensor as the characteristic value. Use D-S evidence theory to fuse data from magnetic flux sensors to determine the operating status of the generator. This method can effectively detect the short circuit fault of rotor windings.
AB - Inter-turn short circuit fault in doubly-fed generator is a common electrical fault that directly affects the normal operation of the wind turbine and endangers the safety of the grid connection. This paper proposes an inter-turn short circuit fault identification technology based on multi-flux sensor data fusion. A simulation experiment platform for the inter-turn short circuit fault of a doubly-fed generator with a power of 100 kW is used, consisting of a three-phase wound rotor induction machine, monitoring systems, frequency converters, and related control a drive motor. This experimental system can genuinely simulate the actual working conditions of the machine when the machine is short-circuited, and the experimental simulation can be closer to the operation process of the double-fed induction generator. The signal detection system is used to collect the external magnetic flux leakage signal of the motor. Flux sensors are placed in the axial and radial positions, then extracting the RMS value of each flux sensor as the characteristic value. Use D-S evidence theory to fuse data from magnetic flux sensors to determine the operating status of the generator. This method can effectively detect the short circuit fault of rotor windings.
KW - data fusion
KW - doubly-fed wind turbine
KW - flux sensor array
KW - inter-turn short circuit fault
UR - https://www.scopus.com/pages/publications/85124953927
U2 - 10.1109/ICSMD53520.2021.9670827
DO - 10.1109/ICSMD53520.2021.9670827
M3 - 会议稿件
AN - SCOPUS:85124953927
T3 - ICSMD 2021 - 2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence
BT - ICSMD 2021 - 2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2021
Y2 - 21 October 2021 through 23 October 2021
ER -