基于粒子群优化算法的砂轮三维形貌匹配

测量金刚石砂轮表面形貌时，为了获得砂轮大范围表面形貌，需要对砂轮三维形貌进行匹配并拼接。将粒子群优化算法引入砂轮的三维形貌匹配，并对砂轮匹配算法进行了实验分析。结果显示匹配前后获得的重合区域的相关系数均大于0.8，且能够在400 s内完成匹配。实验结果表明，运用了粒子群算法后，该算法能够在满足测量精度的条件下，克服一般砂轮匹配运算量大、耗时长的缺点，满足实际运用中匹配精度和速度的要求。

3D topography matching of diamond grinding wheel based on particle swarm optimization

The 3D topography matching is required to gain the surface topography of grinding wheel in a wide range, which is a key process to measure the surface topography of diamond grinding wheel. In this work, the Particle Swarm Optimization（PSO） algorithm is utilized in the 3D matching process of grinding wheel topography, and the matching accuracy of PSO algorithm is analyzed. The experiments indicate that the correlation coefficient of overlap area before and after adjustment and matching is more than 0.8, in which the matching process can be finished within 400 s. The common shortcomings of excessive operations and time consuming can be overcome by the PSO algorithm. The method can meet the demands of high precision and efficiency in the surface topography matching process.