【摘要】 针对航空发动机叶片服役过程产生的局部损伤修复问题，提出了一种适用于叶片不同损伤情况下的局部待修复区域识别染色和连续平滑自适应加工路径规划方法。建立了以立体光刻（STL）染色面片为核心的底层数据结构模型，基于区域识别算法自适应提取分割损伤叶片的待修复区域面片群并染色；拟合估算染色面片群的局部曲率特征来计算最小加工行距，对染色面片进行切分计算路径轮廓，通过非均匀有理B样条（NURBS）曲线插值提高光顺性后基于二分容差法进行步长计算；完成了进退刀路的螺旋走刀设计。结果表明：区域识别算法可以正确识别出不同修复位置的面片集群，并能够针对提取出的局部染色面片群生成高效修复刀路。将算法集成到自主开发的叶片修复软件中并进行仿真测试，仿真结果精度为0.048 mm（设计值为0.05 mm），与整体全局刀路相比，路径长度缩短80.2%，实现了待修复叶片的局部高效加工路径规划。更多还原

【Abstract】 To address the repair of local damage in aeroengine blades during service,a method for identifying,coloring,and continuously smoothing adaptive toolpath planning of local regions to be repaired under varying damage situations was proposed.A low-level data structure model with stereolithography(STL) colored patches as the core was established.Based on the region recognition algorithm,a group of patches to be repaired of the damaged blade was adaptively extracted,segmented,and colored.The local curvature characteristics of the colored patch groups were fitted and estimated to calculate the minimum machining line spacing.The colored patches were segmented to calculate the path contours,interpolated with the non-uniform rational B-splines(NURBS) curves for improved smoothness,the step size was calculated based on the bisection method,and the spiral toolpath design for approach and retract motions was finally completed.The results show that the region recognition algorithm can correctly identify patch groups at different repair positions,and efficiently generate repair toolpaths for the extracted local colored patch groups.The algorithm has been integrated into the self-developed blade repair software and tested via simulation; the simulation accuracy is 0.048 mm(design value is 0.05 mm).Compared to global toolpaths,the path length is reduced by 80.2%,achieving efficient local toolpath planning for the blades to be repaired.更多还原