Prediction of shape and position errors in CNC machining of mechanical dies based on geometric feature parameters
In the process of CNC machining,the lack of necessary geometric feature parameters makes the modeling process complex and the model accuracy low,resulting in a significant deviation in the prediction results of the shape and position error indicators.Therefore,a geometric feature parameter based method for predicting the shape and position errors of mechanical mold CNC machining is designed.Using the least squares method,calculate the fitted sampling signal and obtain the best fitted sampling signal by analyzing the error between it and the actual sampling signal.Combined with the path information of the machining tool,the form and position errors in the machining process are detected,and the geometric feature parameters of the mechanical mold are measured to obtain the coordinates of the discrete points of the tool.The trigonometric functions principle is used to build the pose model of the machining tool.Taking roundness error as an example,the minimum region method is used to predict roundness error,and the least squares method is combined to fit actual error data to achieve shape and position error prediction in mechanical mold CNC machining.The experimental results show that under the same testing environment,the various shape and position error indicators obtained by the proposed method are close to the actual situation,verifying the effectiveness of the design method.