Research on Open Circuit Fault Diagnosis of Inverter Circuit Switching tube Based on Machine Learning Algorithm

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Xu, Huaqing^1 ; Peng, Yanqing^1 ; Su, Lumei^1

School of Electrical Engineering and Automation, Xiamen University of Technology, Xiamen Fujian

361024, China^1

关键词: Inverter circuit;    K-nearest neighbors;    Open circuit failure;    Random forests;    Simulation;    Single-phase full-bridge inverters;    Time domain feature extraction;    Time domain features;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/4/042015/pdf
DOI  :  10.1088/1757-899X/452/4/042015

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

The inverter circuit is widely used, and the switching tube has the highest incidence of open circuit failure. In order to improve the recognition rate of the open circuit fault of the inverter circuit, this paper proposes a method to extract the output voltage, output current and input current time domain features and then use the Random Forest and K-Nearest Neighbor to identify the fault. In this paper, through the simulation of single-phase full-bridge inverter circuit, the open-circuit fault test of the switch tube is simulated, and the output voltage, output current and DC-side input current of each switch tube open-circuit fault are obtained, and then the time domain feature extraction is performed. The Random Forest and K-Nearest Neighbor are used for diagnostic comparison. The results show that the single-tube fault recognition rate can reach more than 96% and the highest fault recognition rate can reach 99.77%.