首页|A HYBRID MODEL/DATA-DRIVEN METHOD FOR OPEN-CIRCUIT FAULT DIAGNOSIS IN NPC THREE-LEVEL INVERTERS
A HYBRID MODEL/DATA-DRIVEN METHOD FOR OPEN-CIRCUIT FAULT DIAGNOSIS IN NPC THREE-LEVEL INVERTERS
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In this paper, the diagnosis and location issue of open-circuit faults in neutral-point-clamped three-level inverters is analyzed. A hybrid method based on model-based and data-driven fault diagnosis is proposed for the insulated gate bipolar transistors open-circuit faults. First, the three-phase current residual is attained by subtracting the true value of the three-phase current generated by the inverter with the estimated three-phase current generated by the state estimator. Second, the Park's vector modulus and wavelet transformation algorithms are utilized for normalization of three-phase current residuals and feature analysis. Then, the 11 fault features of current residuals are extracted and the datasets of fault feature are established. Finally, the fault feature samples are utilized to train the random forest model to achieve state classification. The proposed method can improve the diagnostic accuracy compared with traditional fault diagnosis methods. The effectiveness and the robustness of this method under various conditions are validated by experimental results.
School of Internet of Things Engineering Jiangnan University No. 1800, Lihu Avenue, Wuxi 214122, P. R. China
School of Electrical Engineering||Engineering Research Center of Electrical Transport Technology, Ministry of Education Southeast University No. 2, Sipailou, Xuanwu District, Nanjing 210096, P. R. China
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