## 1 Introduction  
In recent years, due to the increase in nonlinear connected to the utility grid, the problems of low quality and harmonic distortion in power systems have increasingly attracted widespread attention [1]. A large amount of harmonic current will cause power grid voltage distortion and affect the normal operation of electrical equipment. It may also cause parallel or series resonance of the power grid [2]. Three-phase PWM converter, as the interface for energy conversion, has become an important device to improve this problem due to its excellent performance and potential advantages, such as sinusoidal input current and adjustable high input power factor. It is widely used in photovoltaic power generation, wind power generation, traction drive system and other occasions that require strict equipment reliability. However, the reliability of converters used in high-reliability applications is not high, and semiconductor power devices are the weakest components in converters. According to the semiconductor device survey report of more than 200 products from 80 companies, the converter failure caused by semiconductor devices accounts for about 60% of all failure data [3]. In order to obtain high-performance power quality, the system needs to work at a very high switching frequency, generally above 10 kHz. Working at high frequency and high temperature for a long time further increases the damage probability of the IGBT. Since the fault of IGBT has always been the main reason for the fault of the three-phase PWM converter, the fault diagnosis and location of IGBT becomes particularly important [4]. The fault types of IGBT are divided into short-circuit fault and open-circuit fault. Extremely high inrush currents from short-circuit conditions can cause permanent damage to the system, and this type of fault is catastrophic and easy to measure. Therefore, the protection circuit is usually integrated in the inverter system [5]. On the other hand, the open-circuit fault is recessive, and when the fault occurs, it is not enough to trigger the hardware protection circuit. Excessive electrical stress and thermal stress will lead to secondary failures of other equipment. If failure detection methods are not taken, serious safety and property accidents will occur. Therefore, the open-circuit fault diagnosis of IGBT has attracted a lot of research attention [6]. Generally, fault diagnosis methods can be divided into model-based, signal-based and data-driven [7; 8; 9]. Model-based and signal-based inverter fault diagnosis for drive systems have been extensively studied in recent years. Reference [10] proposes a fast diagnosis method for a senseless inverter open-circuit fault by analyzing the switching function model of the inverter in healthy state and fault state. Subsequently, they proposed a fault diagnosis method based on the existing residual vector to remove the influence of the load [11]. Reference [12] proposed an open-circuit fault diagnosis method for voltage source inverters in PMSM drive systems using model reference adaptive system technology. References [13; 14] proposed a simple single-switch and double-switch OC fault diagnosis method based on the three-phase current distortion of a vector-controlled induction motor driven by voltage source inverter. Reference [15] proposed a fault detection technology for an IGBT open-circuit fault in an induction motor driven by voltage source inverter. This technology detects the IGBT open-circuit fault by analyzing the PWM switching signal and the line-to-line voltage level during the switching time. In recent years, benefiting from the rapid development of machine learning theory, the machine learning data-driven fault diagnosis method, which can directly realize fault diagnosis without logical or mathematical description of the inspection object, has received special attention due to its significant advantages [16].