Fault Diagnosis of Three Level Inverter Based on Improved Neural Networks

Inverter and related system were widely used in power electrical system and motor drive system to enhance the reliability and efficiency, the faults with various types and difficult to isolate with traditional techniques, so a new method based on neural network was presented. The neural-point clamped three level invert systems were analyzed and fault features were created by harmonica spectral analysis. The neural network was designed with algorithm programmed, with the fault diagnosis as inputs of neural network, by neural networks adaptive self-learning and take the outputs as judgment of fault types and then the faults occurred in inverter system was isolated . The new technique proposed in this paper was a theoretical foundation for invert system fault diagnosis and practical application for motor driver system, the simulation shows this method is effective and can be widely into inverted fault diagnosis system and relevant fault diagnosis system.