The multi-parameter comprehensive evaluation method of gas turbine can accurately grasp the state of engine health. Eight evaluation indicators were chosen from the condition of engine gas path degradation, the combustion system and the whole machine vibration. Aimed at the uncertainty of data information, the objective attribute weights were gotten based on the method of the combination of fuzzy clustering and information entropy by calculating the mutual information. In view of the equilibrium of data, another objective weights were gotten using the entropy weight method. Then the linear weighted sum method of the two was used to get the final objective weights of indicators. Subjective weights were obtained by analytic hierarchy process. Integrating the subjective and objective weights, multiplication combination method was used to determine the final weights. The multi-attribute comprehensive evaluation of gas turbine health status was carried out combined with a 2,000 hours test. Results show that the method can integrate the advantages of objective and subjective weighting methods, evaluation results are in line with the practical experience, which means it is a feasible way to the gas turbine condition assessment and maintenance decision.
