In this paper, a gas turbine fuzzy analytic hierarchy process based on health degree is proposed to determine the current health state and remaining useful life of the gas turbine. The concept of health degree is introduced to quantitatively represent the health state of gas turbine and its components and parameters. The probability density function is used to calculate the health degree of the evaluation parameters to avoid the complexity of evaluation caused by different orders of magnitude. This paper proposes the weights hiding method that reflects the inhomogeneity of the evaluation parameters and proposes a remaining useful life prediction algorithm based on the health degree. Finally, the training data set from the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) simulator is used to validate the proposed health evaluation method and the remaining useful life prediction algorithm. The results show that the gas turbine health degree obtained by the method in this paper can be used to accurately predict the degradation trend of gas turbine, and the predicted remaining useful life coincides with the result of the test data set, thereby demonstrating the validity and practicability of the proposed method of using health degree to describe the gas turbine health state.

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