Research On Collision Detection Of Heavy-duty Machine Tool Machining Process Driven By Perceptual Data

As an important equipment and industrial machine tool of intelligent manufacturing,heavy-duty machine tools are widely used in processing,manufacturing,assembly and other fields.Its safety is always the basic requirement of production and processing.Collision detection is an important function to ensure machining safety,which has an important impact on machining safety and efficiency.The traditional collision detection function lacks consideration of the complex and changeable actual processing environment such as the actual clamping mode,which may lead to unpredictable collision and reduce the processing safety.Therefore,it is very necessary to consider the actual processing environment for collision detection.Through the actual perceptual data to drive the virtual model of heavy machine tool for collision detection,map the real processing environment and evolve,so as to guide the real processing,which provides an effective idea to solve the above problems.In this paper,the actual perceptual data is used to drive the collision detection of heavy machine tools to predict the potential collision and interference phenomena in the machining process of heavy machine tools.The main research contents are as follows:(1)Research on key technologies of 3D modeling and perception of heavy machine tools.The basic framework of perceptual data-driven collision detection of heavy machine tools is proposed,and the three-dimensional motion model of heavy machine tools is constructed.At the same time,the lightweight of the three-dimensional model is studied to optimize the visualization effect.This paper studies the fixture identification and positioning method of heavy machine tool based on target detection and edge detection,identifies the type of fixture through target detection,obtains the relative position of workpiece and fixture through edge detection,and maps the actual clamping mode in the virtual space,so as to meet the requirements of the evolution of heavy machine tool driven by the actual environment.(2)Research on hierarchical collision detection method driven by perceptual data.According to the requirements of accuracy and efficiency in collision detection of heavy machine tools,the preprocessing method of machining element model based on hierarchical bounding box algorithm is constructed,and the hierarchical collision detection method is studied to detect the collision of the above model,so as to meet the requirements of accuracy and efficiency.Aiming at the problem that the traditional collision detection function does not consider the actual clamping mode and may ignore the unpredictable collision,a collision detection method based on the actual clamping mode is proposed.The virtual model of heavy machine tool will carry out collision detection driven by the mapped actual clamping mode,which is verified by an example.(3)Design and implementation of heavy machine tool collision detection prototype system driven by perceptual data.According to the system requirements,a prototype system for heavy-duty machine tool collision detection is designed.Using B/S architecture,based on SSH integrated development framework,combined with Web GL visualization technology,the user login and authority management module,the heavy-duty machine tool monitoring management module,heavy-duty machine tool fixture library management module and heavy-duty machine tool simulation module are developed,and the collision detection function is realized.Finally,the module function test of the system is carried out to verify the effectiveness of the proposed method.