Research on Digital Twin Monitoring System during Milling of Large Parts

Abstract

In the milling process of large-scale critical parts of energy equipment, the rigidity of the tool can be lower than that of workpieces, which makes it easy to trigger tool chatter. When the vibration is large, the tool cannot act on the workpiece and cannot effectively remove the material. In severe cases, the tool will be embedded inside the workpiece, resulting in the tool and the workpiece being scrapped at the same time. At the same time, in the event of programming errors, the tool or shank could interfere or collide with workpieces or worktable, which may damage the machine parts and reduce the machining accuracy of machine tool, leading to economic losses and even casualties. In response to the problems of tool chatter and tool collision in the milling process, this paper has done four steps as follows to improve the monitoring, modeling, and control of the machining dynamics integrity. First of all, the study constructs a digital twin monitoring system framework for the milling process of large parts, utilizes Unity 3D to build the digital twin virtual system, designs and develops the relevant functions of the virtual machine tool. Secondly, this study establishes a dynamic cutting thickness model for high-feed milling cutter and a milling dynamics model for rigid parts, and builds the stability lobe diagram (SLD) based on the modal parameters and milling force coefficients. In turn, the study obtains the chatter adaptive threshold of the digital twin monitoring system with the guidance of the stabilizing leaf petal diagram. Thirdly, this study also utilizes OPC UA protocol and LabVIEW to acquire the signals of spindle position, speed, acceleration, etc., and process them. Based on the digital twin front-end technology, it will realize user interaction, machine tool collision prevention, and cutting parameters calculation; then based on the digital twin back-end technology, it will obtain the theoretical guidance for chatter monitoring, suppression, and prediction. Finally, it proposes a driver update database based on the MySQL, and utilizes it to update the back-end model of the digital twin monitoring system. According to the experimental test of the digital twin monitoring system under realistic machining process conditions, the results show that the system has a certain improvement in processing safety and processing quality, which has carries practical value and guiding significance.