Multi-objective optimization of three-stage running-in process for main bearing of marine diesel engine

Abstract

Abstract Running-in quality can be improved by optimizing the running-in parameters (load, speed and running-in time). The relationship between running-in quality and the fractal dimensions of friction signal and wear surface is analyzed. It shows that the larger the fractal dimension, the better the running-in quality. A multi-objective optimization design of the running-in parameters of the main bearing is carried out, using a non-dominated sorting genetic algorithm with elite strategy. The optimization targets are the large fractal dimension of friction coefficient, the large fractal dimension of wear surface, and small running-in time. It shows that the selection principles of running-in parameters are different for different stages and priorities. The optimal running-in parameters listed in this paper provides a specific reference to the optimal design of the three-stage running in of main bearing.