Flue Gas Turbine Condition Trend Prediction Based on Improved Echo State Network

Fault prediction is the key technology for ensuring safe operation and scientific maintenance of large equipment. As the running of flue gas turbine has nonlinear characteristics, echo state network (ESN) was introduced to predict the condition trend of the turbine. Singular value decomposition was used to improve the linear regression algorithm of ESN, and the prediction workflow was given. Condition trend prediction results showed the effectiveness of the proposed method.