Turbofan Engine Overhaul Quality Evaluation Based on Cloud Theory

Abstract

The paper was aimed to construct the engine overhaul quality cloud model on the basis of the randomness and fuzziness of overhaul test data. The engine overhaul quality evaluation system was established by nine parameters of engine performances at the condition of the engine taking-off test under engine stable thrust and engine pressure ratio (EPR). In the meantime, the test quantitative data recording five times of engine overhaul parameters were transformed to the qualitative data in the cloud model. The weight values of the calculated parameters were given by method of the information entropy theory. The cloud gravity center weighted deviation degree was accordingly given as an evaluation criterion of the engine overhaul quality. The overhaul test data concerning turbofan engine TRENT 700 were chosen in order to validate the model. The results of the paper show that the calculated performance deviation degree was separately 0.5188, 0.4851, and 0.5288. The first and third values were nearly equivalent, while the second one was lower in comparisons with the other two values. As for the two former, the two engines were equipped on the same airplane. Therefore, the cloud model proposed in the paper can be applied to accurately make assessments of the engine performances. The accuracy of the aero-engine quality evaluation is further improved. The results can provide the references for the engine fleet management.