Paper Title:
Emulating and Modeling for Position Errors of Ultra-Precision Aspherical Grinding
  Abstract

In the process of the ultra-precision grinding, the machining path of the aspherical is the result of motor coordination by several axes for the numerical control system. Since the motion of each axis have errors, there are big errors between the real positions and the theoretical positions, and the position error of the wheel infects the accuracy of the workpiece greatly. This paper analyses the position error property of the wheel and finds the machining approach path has nothing to do with the position error, just do with to the present machining point. In order to solve the problem, the method using the Neural Network optimized by the Genetic Algorithm to establish the position error model is introduced. A three-layer error back propagation (simplified as BP) Neural Network is used to establish the position error model, the position coordinates (x, z) of the program instruction is input layer, and the corroding measured error value ( Δx , Δz ) is output layer. Before training data sample, using the Genetic Algorithm to optimize the Neural Network to improve the predicting accuracy of the Neural Network, and reduce the training time. The emulation results indicate that using the Neural Network model optimized by the Genetic Algorithm can predict the position error in a high degree of accuracy, and at the same time, according to the predicting results, compensating the position error of the wheel is possible.

  Info
Periodical
Edited by
Kai Cheng, Yingxue Yao and Liang Zhou
Pages
291-296
DOI
10.4028/www.scientific.net/AMM.10-12.291
Citation
D. J. Chen, Y. Zhang, F. H. Zhang, H.M. Wang, "Emulating and Modeling for Position Errors of Ultra-Precision Aspherical Grinding", Applied Mechanics and Materials, Vols. 10-12, pp. 291-296, 2008
Online since
December 2007
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Jae Seob Kwak, In Kwan Kim
Abstract:To minimize the geometric error made in ground surface, the optimization of grinding parameters is essential. This paper focused on the...
709
Authors: Zhen Zhong Sun, Zeng Hong, Sheng Gui Chen
Abstract:By using homogenous coordinate transformation principle and Denavit-Hartenberg analysis method, a measurement kinematics model and a error...
263
Authors: Lei Wang, Jiang Ning Gai
Chapter 3: Micro/Nano Materials
Abstract:In electrochemical machining (ECM) machining accuracy of workpieces is greatly influenced by many machining parameters. In this paper the BP...
375
Authors: Jian Han, Li Ping Wang, Lian Qing Yu, Hai Tong Wang
Chapter 1: Mechatronics
Abstract:Error modeling and compensation is the most effective way to reduce thermal errors. In this paper, a novel approach to predict the thermal...
1516
Authors: Wei Qing Wang, Huan Qin Wu
II. Advanced Manufacturing Technology and Processes
Abstract:Abstract: In order to determine that the effect of geometric error to the machining accuracy is an important premise for the error...
493