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Methods for Gas Turbine’s Compressor General Characteristic Curve Prediction

Due to the high experiment cost and limited experiment conditions, it is hard to get the gas turbine compressor characteristic curve, which is crucial for the gas turbine performance evaluation. Based on the limited data, this paper tries to use different method to predict the characteristic curve. The result indicate that the K-Nearest Neighbors(KNN) is better in prediction than the back propagation neural network(BPNN) and the least square method. Furthermore, this paper analyzes the predicted performance by using a certain corrected rotational speed data or not. It shows that KNN has better predicted results than other methods whether the relevant data is used or not.