A method of inverter circuit fault diagnosis based on BP neural network and D-S evidence theory

With the study and analysis on intelligent fault diagnosis for inverting circuit, an improved diagnosis method combined BP neuron network and D-S evidence theory was proposed. Each measuring point was extracted by BP neural network to obtain the local diagnosis, which is adopted to design the belief function of D-S evidence theory. Multiple monitoring points' information is fused to receive the comprehensive global diagnosis result. The experimental results show that this method has the better feasibility and effectiveness on fault diagnosis in inverter's key components-inverting circuit.