Study on Component Characteristic Correction Algorithm of Turbofan Engine

The optimization of component characteristics is an important part of the research on model modification of turbofan engine. This paper studied three kinds of modification and optimization algorithms: genetic algorithm (GA), differential evolution algorithm (DE) and particle swarm optimization algorithm (PSO), and made a comparative analysis on the principles of the algorithms. In addition, the DGEN380 turbofan engine component model was taken as the research object to test and compare the modification performance of each algorithm. The results show that：compared with GA, DE algorithm and PSO algorithm have higher adaptability to multi-objective and multi-parameter correction, the success rate can reach 100%, the error is kept within 1%, and the convergence ability is strong. Compared with the other two algorithms, the solving speed of PSO algorithm is more influenced by the initial parameters. This conclusion can provide an important reference for selecting and improving the algorithm.