Matching technology of reducer bearing based on genetic algorithm

Abstract

This paper presents a method of bearing selection for heavy reducer based on genetic algorithm. A mathematical model for the selection of key parts of bearing cap and adjusting ring is established, the coding mode of bearing cap and adjusting ring components is determined, the initial population is constructed, the fitness function is established, and the genetic calculations of selection, crossover and variation are carried out. Finally, through repeated experiments and 500 iterations, the value of the optimal objective function tends to be stable, and a good convergence effect is obtained. The assembly rate of the gearing cap-adjustment ring assembly is increased from the original 50% to over 70%, which greatly improves the assembly efficiency of heavy-duty reducer bearing, and thus the assembly cost is reduced, which is significant to the actual assembly of heavy-duty reducer.