학술논문

NUMERICAL CONTROL MILLING PARAMETER OPTIMIZATION ON THE BASIS OF IMPROVED GENETIC ALGORITHM
Document Type
article
Source
Jixie qiangdu, Vol 44, Pp 620-626 (2022)
Subject
Multi-objective
NDX crossover
CA sorting
ENDE-NSGA-II
Numerical control machining
Mechanical engineering and machinery
TJ1-1570
Materials of engineering and construction. Mechanics of materials
TA401-492
Language
Chinese
ISSN
1001-9669
Abstract
Numerical control machining is widely used in traditional manufacturing industry and national defense strategic industry, and optimization of milling parameters is closely related to processing efficiency, quality and cost. Firstly, a constrained multi-objective optimization function is constructed as a parameter optimization model. Then, the ENDE-NSGA-II method is adopted to complete the parameter optimization. By adoption of the NDX crossover algorithm, CA sorting method and DE strategy can increase the search interval, ensure the population diversification distribution, and improve the convergence rate. The DMU125 P five-axis CNC machine tool combined with Matlab 2020 was used to complete the comparison experiment of processing parameters, quality and system steady-state. Experimental results show that in comparison with the traditional empirical processing method, the processing parameters optimized by the ENDE-NSGA-II method can improve the surface roughness and the processing quality of the workpiece, under the premise of ensuring the processing efficiency. And increase the wear resistance of cutting tools, improve economic benefits. In addition, it allows the system to reach steady state more quickly.