Open-circuit Fault Diagnosis for Grid-connected NPC Inverter Based on Independent Component Analysis and Neural Network
Abstract: An open circuit
(O-C) fault detection method for grid-connected neutral-point-clamped (NPC) inverter
based on independent component analysis (ICA) and neural network (NN) is
proposed in this paper. A NN classifier is applied to the fault diagnosis of
NPC inverter. The ICA is utilized for the three phase current feature
extraction. The ICA reduces the number of NN input neuron. A lower dimensional input
space reduces the noise and the training time of NN, the ICA algorithm improves
the mapping performance. The proposed algorithm is evaluated with simulation
test set. The overall classification performance of the proposed network is
more than 97%. The simulation results show that the proposed algorithm performs
satisfactorily to fault location.
Author: Xiaofeng Wan
Journal Code: jptkomputergg170110
