Statistical Method Of Usage Based On CNC System Data And Its Application In Turning Tool Wear

In industrial production,CNC system often counts the working times,time and even mileage of machine parts in the service process,and takes them as the judgment basis of health status or service life monitoring and management of parts.At present,although the methods of timing and counting times are simple,they are not accurate enough under complex working conditions,resulting in large errors in the judgment of health status and life.In view of the disadvantages of the above methods,this paper summarizes and refines the usage statistics method on the basis of the life management work of timepieces.Through the statistical calculation of the service history information of parts,the cumulative loss is measured,and the feasibility and accuracy of the usage statistics method is verified for the specific case of tool wear.Aiming at the problem that the existing statistical function of CNC system is simple and rough,combined with the characteristics of CNC system electronic control data,through the general analysis of the use process of machine parts,the usage statistics method is summarized to achieve accurate life management.Based on this,the design framework of internal usage statistics method of CNC system is summarized,and the three control data,usage and loss amount are established In addition,a method for evaluating the accuracy of usage is proposed to screen the most accurate usage.According to the above statistical method and design framework,this paper analyzes the use characteristics of spindle bearing,feed shaft lead screw and turning tool as well as the relevant electronic control data,puts forward and designs the corresponding statistical value of usage and its calculation method,and initially constructs the statistical design method system of CNC system.Among them,the tool as a vulnerable part,its wear prediction problem is selected as a specific case to verify the effectiveness of the statistical method.The PCA-SVR model is established to predict the tool wear based on the input of 7 kinds of tool usage.In order to verify the generalization ability of the model in industrial production,through a practical turning workpiece processing,the relative prediction accuracy of the tool wear predicted by the usage is less than 5%,which achieves a good effect.In addition,the accuracy evaluation of tool usage shows that the new statistical value of tool wear is better than the traditional life statistics.The usage statistics method proposed in this paper achieves good results in the specific application of tool wear prediction,and the method is not limited to a certain part.Therefore,it has a strong application value to improve the overall accuracy of life management of existing CNC system parts.