恒力铣削智能控制算法研究与仿真

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针对数控加工，建立了2种以切削力恒定为控制目标的在线智能控制系统。首先，利用BP神经网络对铣削过程进行了建模；然后，基于BP神经网络和模糊控制理论，提出了2种以切削力恒定为控制目标的在线铣削控制算法；最后，在变轴向切削深度条件下开展了仿真实验。相对于传统恒速切削，基于BP神经网络和模糊控制的在线智能控制系统分别节省了13．9％和13．7％的切削时间。 This paper investigates the application of intelligent control strategies in milling process to get constant cutting force. Since the cutting process is under a good condition, the surface quality is improved and the higher accuracy is obtained. The milling process was modeled by a developed BP neural network. Intelligent control strategies based on neural network and fuzzy logic were proposed to guarantee the constant cutting force and improve the cutting efficiency. Simulations were conducted to verify the effectiveness of the proposed strategies and the results showed that the time saving of two strategies are 13.9% and 13.7%, respectively.