摘要
针对航空发动机叶片形状复杂,传统的线轮廓统计控制方法(SPC)难以保证其整体精度的问题,本文基于面轮廓控制图,建立了叶片磨削过程误差监控模型。针对叶片型面特征,采用波纹度参数进行精度监控。建立了测量点到理论型面曲面的最短距离模型,并基于粒子群算法给出了距离求解算法;基于最短距离,构建了基于指数加权移动平均的面轮廓控制图(Exponentially Weighted Moving-Average,EWMA),并通过蒙特卡罗仿真方法给出了控制图上下控制限计算方法。最后通过基于仿真数据的模型验证,表明了该模型的有效性。
As the shape of aero-engine blades is complex, the traditional line profile statistical process control（SPC） method is difficult to meet the requirements of the overall accuracy. Based on the surface contour control chart, the monitoring model of the error for the aero-engine blades in the grinding process is established. As for the characteristics of the blade surface, the parameters of surface waviness are adopted to monitor the overall accuracy of the blades. The model of the shortest distance from the measuring point to the theoretical surface profile is presented and an algorithm is given based on the particle swarm algorithm. The EWMA（exponentially weighted moving-average） surface contour control chart is constructed based on the shortest distance and the calculation method of the upper and lower control limits for the control chart is given by Monte Carlo simulation method. The simulation experiments verify the effectiveness of the model.
出处
《航空精密制造技术》
2016年第3期25-29,共5页
Aviation Precision Manufacturing Technology
基金
中央高校科研基金资助项目(3102015JCS05012)
关键词
叶片
磨削
面轮廓
误差监控
控制图
blades
grinding
surface contour
error monitoring
control chart
