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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Vu, Hoang-Giang
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Intermittent open-circuit fault diagnosis of inverters based on DC-link electromagnetic field signal Vu, Hoang-Giang; Yahoui, Hamed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp3885-3893

Abstract

For the objective of improving the reliability of converters in electric drives, research on a method for early detection of intermittent open-circuit faults of power valves is reported in this article. Intermittent open circuit condition is the incipient form of power valve open-circuit fault in power converters. Prompt detection of this fault allows for timely remediation of permanent open circuit defects that is a commonly subsequent process. This study introduces an investigation of this fault, which occurs in the voltage source inverter of induction motor drives. Intermittent faults are created through interference with the control pulse of the power valve. Wavelet transform with the Mexican hat mother function is utilized for signal processing. Appropriate ranges of the scale are selected to obtain a high magnitude of the wavelet coefficient at faulty instants. The analysis for the direct current recorded at the DC-link in simulation and the electromagnetic signal measured at the DC-bus of the inverter can be effectively used for the fault diagnosis.
Fault diagnosis for inverter open circuit faults using DC-link signal and random forest-based technique Vu, Hoang-Giang; Nguyen, Dang Toan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2178-2185

Abstract

Three-phase voltage source inverters based on insulated-gate bipolar transistors (IGBTs) are widely used in various industrial applications. Faults in IGBTs significantly affect the performance of the inverter and entire system. Robust and accurate fault detection are the key requirements of fault diagnosis methods. This paper explores a method for diagnosing power switch open circuit faults of a voltage source inverter based on machine learning algorithms. The diagnosis is performed in two steps, firstly the fault is detected by applying the Random Forest classifier algorithm with the DC-link signal. Next, the fault switch location is performed by additionally using the inverter output AC current signals. The diagnostic results based on simulation data show that the fault can be detected with maximum accuracy. Meanwhile, the accuracy in locating the fault switch is also significantly improved with the additional use of current signals measured at the DC-link. Potential application of electromagnetic field signal is also highlighted for the practical implementation of fault diagnosis.
Co-Authors Nguyen, Dang Toan Yahoui, Hamed