矿井天轮在线切削精度测量设备的柔性误差预测

矿井天轮绳槽要求切削精度在±0.5 mm,用于切削加工的在线测量设备为自驱动关节臂坐标测量机,由于其柔性产生的变形使测量机的测量精度无法保证,建立了测量机的理论模型与三维仿真分析模型,通过刚柔耦合仿真分析确定测量机的测量误差值。将仿真结果用RBF神经网络进行预测,确定测量机的模型参数与误差值的关系。通过对比,建立的RBF神经网络能够实现柔性动态变形误差最大值为5.16×10^-4 mm的高精度预测。

Flexible Error Prediction of Online Cutting Accuracy Measuring Equipment for Mine Sheave

The cutting accuracy of the rope groove of the sheave in mine is required to be±0.5 mm.Because of the deformation of the self-driven articulated arm coordinate measuring machine,the measuring accuracy of the measuring machine cannot be guaranteed.The theoretical model and three-dimensional simulation analysis model of the measuring machine were established,and the measurement error value of the measuring machine was determined through the rigid flexible coupling simulation analysis.The simulation results were predicted by RBF neural network to determine the relationship between the model parameters and the error value of the measuring machine.Through comparison,the established RBF neural network can achieve the high precision prediction of the maximum vale of flexible dynamic deformation error of 5.16×10^-4 mm.