Real-Time and Efficient Point Cloud Data Web Visualization Method of Intelligent Manufacturing Parts Based on Rendering Optimization

In the application scenario of point cloud visualization of intelligent manufacturing parts, it is one of the important requirements to realize the fast loading and dynamic rendering of point cloud data. Traditional point cloud Web visualization methods lack lightweight data structure management and dynamic data update processing capabilities. Aiming at the data characteristics of intelligent manufacturing parts scene, this paper proposes a real-time and efficient point cloud data Web visualization method of intelligent manufacturing parts based on rendering optimization. The method uses flat data structure to process point cloud data index and data communication through json data format. Based on WebGL, the underlying mechanism of rendering is optimized, data is loaded at high speed through instantiation, and shader optimization is adopted to improve rendering efficiency. A data response mechanism is constructed to realize dynamic data loading on demand. The experiment proves that this method can effectively improve the point cloud data loading problem and frame rate problem of intelligent manufacturing parts.