|
|
|
| The Dynamic Error Modeling Study of CMM Touch Trigger Probe Based on RBF Neural Network |
| QU Ying,LUO Zai,LU Yi,GUO Bin |
| College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou,Zhejiang 310018, China |
|
|
|
|
Abstract To solve the problem of low precision when touch trigger probe of CMM is in the process of dynamic measurement, the sources of the dynamic error for the probe were analyzed. Through the measurement experiment to the standard ball, the main factors which influence the dynamic error of probe were verified. Among them there are three most important crucial factors: approach speed, stylus length and stylus tip diameter. To reduce the dynamic measurement error caused by the probe, the compensation model of RBF neural network was introduced. It can avoid the derivation of complicated mathematical relationships in the traditional error compensation model. On the Global Class 9158 CMM, the standard ball was measured and the network training data was obtained. The standard ring gauge was measured as the test sample and it was compensated by the error model. The experiment results show that after the compensation by the model the mean measurement error decreases from 3.5 μm to 1.3 μm, and the model is stable and reliable.
|
|
|
|
|
|
|
|
［1］Tyler Estler W, Phillips S D, Borchardt B, et al. Practical aspects of touch-trigger probe error compensation［J］. Precision Engineering, 2003, 3(10):1-17.
［2］Johnson R P,Yang Q,Butler C.Dynamic error characteristics of touch trigger probe fitted to coordinate measuring machines［C］//IEEE Instrumentation and Measurement Technology Conference, St Paul, Minnesota, USA, 2004, 1104-1109.
［3］Van Vilet W P, Schellekens P H J. Development of a fast mechanical probe for coordinate measuring machine［J］. Precision engineering, 1998, 21(7): 141-152.
［4］杨庆东, Van Den Bergh C, Vanherck P, Kruth J P.三坐标测量机的热变形和神经网络误差补偿［J］. 计量学报, 2000, 21(2):113-118.
［5］郑大腾,费业泰.基于Monte Carlo理论的柔性坐标测量机测量空间的分析［J］.计量学报,2010,31(4):294-298.
［6］张宏韬,杨建国.RBF网络在线建模方法在热误差实时补偿技术中的应用［J］.上海交通大学学报,2009,43(5):807-810.
［7］裴丽梅,位恒政,王为农.基于步距规的三坐标测量机的几何误差分析［J］ .计量学报,2009,30(5A):50-52.
［8］张丹,赵军,李东.基于RBF神经网络的柴油机排气温度智能检测方法的研究［J］.仪器仪表学报,2008,29(2):401-404. |
|
|
|
2011, Vol. 32 
