Research on fault diagnosis for turbines based on BP neural network of preserving nonlinear and quasi-Newton algorithm

A new method of fault diagnosis for turbines using preserving nonlinear and quasi-Newton algorithm for the learning process of BP neural network was introduced in the paper, Which take advantages of preserving nonlinear and quasi-Newton algorithm with fast speed, significant superiority for high-dimensional problems and more accurate mathematical models comparing with traditional BP neural network. Though simulation studies on typical fault diagnosis examples of turbines in power plant, the results have shown that the performances of BP neural network based on preserving nonlinear and quasi-Newton algorithm is superior to the traditional BP algorithm, improving the ability of online diagnosis for turbines and having broad application prospects and value.