Fault diagnosis based on robust FCM algorithm

A method for improving the ability of noise tolerance of FGM algorithm during fault diagnosis process was proposed. A new metric distance function was introduced to replace the Euclidean norm in fuzzy c-means clustering procedures, and was proved by Gaussian kernel function. Performances of the two norms were compared under noise background. A robust FCM algorithm based on the new metric distance function was presented and then the approach of the algorithm was given. Numerical results show that the proposed algorithm has higher robustness than the FGM algorithm. Finally, a fault diagnosis example of certain airborne weapon system demonstrates the effectiveness of the algorithm. Experiment results show that the proposed algorithm is effective in dealing with the above problem and has higher precision.