Research on Hybrid Particle Swarm Optimization Algorithm Calculating Numerical Control Machining Step Error
The step error is the machining error between adjacent tool positions in the feed direction,its ef-ficient and accurate calculation is a prerequisite for generating high-quality NC machining tool paths.In or-der to improve the computational efficiency of the step error,a hybrid particle swarm optimization method combining genetic algorithm was proposed.The mapping relationship between the cutter contact interval in step error calculation and the particle search interval and the fitness calculation model were established.The maximum fitness value was taken as the step error.The particle population was initialized using the Tent mapping.Two nonlinear control methods based on the sigmoid function for the inertia weight coefficient and based on the number of iterations for the learning factor were proposed.The crossover and mutation strategies of genetic algorithm were introduced to improve the global search ability of particles.Then a hy-brid particle swarm optimization method was constructed.The functionality of the aforementioned parallel hybrid particle swarm optimization method was implemented,some typical free-form surfaces were taken as examples to calculate the step errors and equal error tool path is generated.The calculation results show that the tool path generation time of the proposed algorithm is lower than that of the geometric iterative algo-rithm and the standard particle swarm optimization algorithm,which verifies the feasibility and effectiveness of the proposed scheme.
NETL
NSTL
万方数据
维普
