Fault diagnosis based on Danger Model Immune wavelet neural network

Abstract

Danger Model Immune Algorithm (DMIA) is an algorithm based on the danger theory of biological immune system, and it has a good performance in optimization. DMIA is proposed to initialize the weights and biases of wavelet neural network (WNN), the ergodic weights and biases are used for further net-training. The fault diagnosis for marine diesel engine is conducted by using the well-trained wavelet network. The results indicate that this algorithm is efficient in fault diagnosis.