Improved WNN to Rotating Machinery Fault Diagnosis

The improved algorithm of WNN based on BP was proposed in this paper. Theoretical analysis and simulation result show it avoids both the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations, such as local optimization. So it can simplify the training of neural networks. It has better abilities in function learning and generalization. This algorithm was successfully applied to rotating machinery fault diagnosis. Therefore it has wide application prospect.