Abstract：The traditional fault diagnosis methods for converter need to establish an accurate mathematical model to realize fault identification and location, but the modeling process is complex and it is impossible to establish a nonlinear system model. According to above problems, this paper adopts a data-driven method to realize the research of converter faults. The paper mainly divides the data-driven fault diagnosis types into three categories: converter fault diagnosis method based on statistical analysis, converter fault diagnosis method based on signal processing, and inverter fault diagnosis method based on artificial intelligence. After that, the basic research principles, applications and limitations are explained for three different methods. Finally, this paper proposes that the fault diagnosis of the converter should be prospected from the aspects of fault diagnosis methods, detection of new types of faults, online learning of fault modes and setting of data monitoring systems.
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2019, Vol. 20 
