CAJ | 학술논문

以6UPU教学型并联机床为实验平台,以壳体铝合金零件加工为研究对象,提取加工尺寸误差样本数据,采用BP神经网络建立加工尺寸误差预测模型,通过分析6UPU教学型并联机床误差,提出实验数据与样本数据的处理原则,全面考虑到加工过程中各种情况.提出的基于BP网络来预测加工误差具有较强的实用性和一定的先进性,能有效提高加工精度,为提高开环数控系统精度提供了新的途径.
이6UPU교학형병련궤상위실험평태,이각체려합금령건가공위연구대상,제취가공척촌오차양본수거,채용BP신경망락건립가공척촌오차예측모형,통과분석6UPU교학형병련궤상오차,제출실험수거여양본수거적처리원칙,전면고필도가공과정중각충정황.제출적기우BP망락래예측가공오차구유교강적실용성화일정적선진성,능유효제고가공정도,위제고개배수공계통정도제공료신적도경.
A study on the processing of an aluminum shell component with a 6UPU parallel machine tool was made. The sample data of the finish size error were extracted and a model for the finish size error prediction was set up by using BP neural network. Through analyzing the error of 6UPU teaching parallel machine tool,the processing principle of the experimental data and sample data was put forward,with overall consideration about the processing situations. The proposed prediction of processing error based on BP neural network has strong practicability and advanced nature,and it can effectively improve the machining precision,and it also provides a new way to improve the accuracy of the open loop numerical control system.