Open-Circuit, Current Sensor Fault Diagnosis of Three-Phase Four-Wire Inverters Based on Fourier Fitting

Existing fault diagnosis methods of inverter’s open-circuit faults and sensor faults are mainly for linear loads. With the increasing use of nonlinear loads, a large number of harmonics are also generated in the nonfault phase when a fault occurs, which makes fault diagnosis more difficult. In this study, a Fourier fitting multiplicative averaging secondary sampling method is proposed to simultaneously diagnose open-circuit faults and sensor faults under nonlinear loads. First, the ideal bridge arm midpoint voltage and the actual bridge arm midpoint voltage are derived, and empirical wavelets are used for adaptive banding of the bridge arm voltage difference before and after the fault. Next, the frequency band range of secondary sampling is determined using the weights of the bridge arm midpoint voltage differences before and after the fault and the bridge arm voltage weights after the fault. Then, the actual midpoint voltage of the bridge arm is sampled secondarily and Fourier fit, replacing the actual value with the fit value, eliminating the high harmonics and not generating a delay. To minimize the effect of sampling spikes, the fit values are multiplicatively averaged. After that, fault diagnosis is achieved using the normalized detection variables of the ideal bridge arm voltage and the fit bridge arm voltage. Meanwhile, the open-circuit faults and current sensor faults can be identified through the difference between the neutral line current constructed by dc-link voltages and the sum of three-phase currents. Finally, an experimental setup is built to verify the proposed method. The results show that the online fault diagnosis method is effective, fast, and robust.