Novel “On-Line” Identification Procedure using Artificial Neural Network

Abstract A novel neural network learning procedure which has faster training features suitable to real-time implementation is proposed. Then, improved structure backpropagation and radial basis function networks by using the proposed learning scheme are developed. Simulations are performed to confirm the feasibility of these neural networks for real time applications. Lastly, these are experimentally applied to machine tool breakage detection problems resulting in excellent fault diagnosis methods.