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压缩体素模型在五坐标数控加工仿真中的应用 被引量:1

Application of Compressed Voxelmodel in Five-axes NC Milling Simulation
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摘要 针对五坐标数控加工仿真中刀具扫描体和零件毛坯之间布尔运算量大,传统基于空间分解的体素建模方法需要大量计算机内存空间,仿真时间很长,仿真精度低等问题,结合Dexel模型提出了一种压缩体索模型,极大地简化了仿真过程中的布尔运算。同时有效地压缩了仿真模型的数据量,仿真的精度也有所提高。并且根据压缩模型的特点,设计了基于Maehing Cubes的优化表面三角网格提取算法,加快了仿真结果的图形显示。整个加工过程的仿真速度比传统体素模型提高了8~9倍,在实际应用中取得了良好的效果。 In five- axes NC milling simulation, the Boolean calculation between tools and rough part is very large, traditional voxelmodel of space decomposing needs huge computer ram, which result in long simulation time and low simulation quality. A new compressed voxelmodel using Dexel was put forward, which predigests the Boolean calculation largely and compresses the part data effectively. In addition, the quality of simulation result is more better. According to the characteristic of the compressed voxelmodel, a optimized Marching Cubes algorithm to construct the surface model was designed which can quichen displaying the result of the NC simulation. Generally speaking, the whole simulation process is quickened about 8 ~ 9 times. This compressed voxelmodel has gotten a better effect in practical usage.
出处 《机床与液压》 北大核心 2006年第3期26-28,共3页 Machine Tool & Hydraulics
基金 国家自然科学基金资助(项目编号:50375126)
关键词 数控仿真 Dexel 体素 MARCHING CUBES NC simulation Dexel Voxel Marching cubes
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