叶身型线轮廓度评定方法研究

Profile Evaluation Method for Blade Pattern

针对传统方法配准时求解基准变换速度缓慢和精度差等问题,提出了一种叶身型线基准误差求解方法。首先采用非均匀有理B样条曲线的矩阵形式对叶身型线进行拟合,利用区间搜索的方法寻找实测点所对应理论轮廓上的最近点及偏差;其次运用二维最近点迭代的解析形式,计算基准变换的旋转量和初始平移量,然后对初始平移量加微小扰动,以最短距离均值为优化目标,采用自适应权重粒子群算法重新计算平移量;最终计算叶身型线实测点变换基准后的偏差,得到实测轮廓的轮廓度。实验结果表明,该方法基准变换向量误差在0.006左右,相对于采用进化算法直接计算变换参数速度提高了40%左右。所提算法适用于三坐标测量叶身型线数据后对叶身型线进行评价,能够有效减小由于基准不重合对偏差计算的影响,避免叶身型线加工质量误判。

Aiming at the slow solving rate of reference transformation and low accuracy in the traditional method, a method for solving the blade pattern reference error is proposed. The blade pattern is fitted by the matrix form of the non-uniform rational B-spline curve, and the interval search method is used to find the nearest point and deviation on the theoretical blade pattern corresponding to the measured point. The analytic form of two-dimensional iterative closest points is used to calculate the rotation amount of the reference transformation, and then the small disturbance is added to the translation amount calculated by the iterative closest points. The adaptive weight particle swarm optimization algorithm is chosen to recalculate the translation amount with the shortest distance mean as the optimization target. The deviation calculation is performed on the measured points of blade pattern, and the profile of the measured blade pattern is obtained. Experimental results show that the reference transformation vector error in the proposed method is about 0.006, and this method heightens the calculating rate by 40% for direct calculation of transformation parameters compared with the evolutionary algorithm. The proposed method is suitable for the evaluation of the blade pattern after three-coordinate measurement of the blade pattern coordinate data, effectively reduces the influence of the reference misalignment on the deviation calculation, and avoids the misjudgment of the blade pattern processing quality.