关键词: 高速铣销, 切削力, 建模, 粒子群优化, 人工神经网络, 反向传播

Abstract: Theory of Particle Swarm Optimization (PSO) trained artificial neural network was applied in the research of high speed milling force modeling. Combined PSO algorithm with Back Propagation (BP) algorithm, the BP neural network model was optimized. The network parameters were trained by PSO algorithm until the error reached to a stable value. Then BP algorithm was adopted to accomplish cutting force forecast based on optimized initial weights，which takes full use of the global optimization of PSO and local accurate searching of BP. Results of simulation showed that with comparison to other BP algorithms, the neural network trained by PSOBP not only greatly shortened the training time, but also greatly improved the accuracy of prediction. It was an effective and robust tool to model high speed milling force.

Key words: high speed milling, cutting force, modeling, particle swarm optimization, artificial neural network, back propagation