A rapid generation method of models in machining processes for real-time human-machine interaction with virtual-real fusion

The intelligent service of the digital twin machine tool provides convenience for the human operation interaction in the machine tool, and the real-time operation interaction between the human and the machine tool has high requirements for the real-time machining model simulation algorithm. Firstly, this paper proposes a simulation method based on the combination of augmented reality (AR) and digital twin of machine tool machining virtual-real fusion. Secondly, to improve the real-time interoperability between human and machine tools in the AR virtual-real fusion machining process, this paper proposes a fast Dexel model generation method based on binary tree space segmentation. The method is based on the 3D model of the workpiece preprocessing to generate a one-way Dexel model of the binary tree storage structure, using the tool and the workpiece overlap envelope in the binary tree structure to determine the interference region, and ultimately calculating the intersection line between the one-way generation line and the tool geometry to get the model of the workpiece after cutting. By analyzing the real-time performance of the algorithm, the algorithm satisfies the simulation calculation of Dexel models of different scales. Finally, through the example of real-time interactive operation between human and machine tool AR, the results show that the average display frame rate of this algorithm in the machining process reaches 55-60 frames, and the parameter error between the model after virtual machining and the actual machining model is within 1.3%. At the same time, 100 people were randomly selected to carry out AR interaction training, and the real-time performance experience of AR virtual-real fusion machining was comprehensively evaluated, and the results showed that the system can meet the real-time demand of interaction operation of most participants.