Fault Detection and Reconfiguration Technique for Cascaded H-bridge 11-level Inverter Drives Operating under Faulty Condition

摘要

A fault detection and reconfiguration technique for a cascaded H-bridge 11-level inverter drives during faulty condition is proposed in this paper. The ability of cascaded H-bridge multilevel inverter drives (MLID) to operate under faulty condition is also discussed. Output phase voltages of a MLID can be used as a diagnostic signal to detect faults and their locations. AI-based techniques are used to perform the fault classification. A neural network (NN) classification is applied to the fault diagnosis of a MLID system. Multilayer perceptron (MLP) networks are used to identify the type and location of occurring faults. The principal component analysis (PCA) is utilized in the feature extraction process to reduce the NN input size. The genetic algorithm (GA) is also applied to select the valuable principal components to train the NN. A reconfiguration technique is also developed. The developed system is validated with simulation and experimental results. The developed fault diagnostic system requires about 6 cycles (～100 ms at 60 Hz) to clear an open circuit and about 9 cycles (～150 ms at 60 Hz) to clear a short circuit fault. The experiment and simulation results are in good agreement with each other, and the results show that the developed system performs satisfactorily to detect the fault type, fault location, and reconfiguration.