基于BP神经网络的车削加工刀具变形误差补偿技术

摘要

In allusion to the common machine tool processing problems, put forward a kind of precision compensation method, the general machine tools can obtain high machining accuracy. First of all, based on analysis of machining errors, introduces the neural network model, are discussed in detail from the structure and the method, and using MATLAB to build; the input samples to train the network, obtain the predictive value, verify the correctness and feasibility of this scheme.%针对目前普通机床加工存在精度不足的问题，提出了一种精度误差补偿方法，使普通机床也能获得较高的加工精度。首先，在分析车床加工误差的基础上，引入了神经网络模型，从结构和方法上进行了详细阐述，并利用MATLAB构建；输入样本对网络进行训练，获取预测值，验证了本方案的正确性和可行性。