Paper Title:
The FNN Quilting Process Deformation Prediction Model
  Abstract

It is easy to have deformation that non-rigid materials is on high-speed processing, so this paper introduces the fuzzy neural networks combine with computer vision measurement technology to control this process. Based on the traditional PID control, increasing a fuzzy neural network predictor for pre-processing of trajectory compensation. Established a fuzzy neural network deformation prediction model of the single needle quilting, and simulated. Experimental and simulation results show that: error compensation which based on fuzzy neural network, have a good real-time, allow fast and accurate automated processing of quilting.

  Info
Periodical
Edited by
Shengyi Li, Yingchun Liu, Rongbo Zhu, Hongguang Li, Wensi Ding
Pages
306-310
DOI
10.4028/www.scientific.net/AMM.34-35.306
Citation
L. X. Tang, B. Bin, K. Han, "The FNN Quilting Process Deformation Prediction Model", Applied Mechanics and Materials, Vols. 34-35, pp. 306-310, 2010
Online since
October 2010
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: Ying Jun Sang, Xue Liang Huang
Sensor Technology
Abstract:In this paper, the piezoelectric ceramic electronic voltage transducer principles is researched, a new internal structure of the measurement...
992
Authors: Xu Dong Zhou, Xiang Ru Liu
Chapter 3: Materials Forming, Machining and Joining
Abstract:The researches of non-oriented silicon steel are mainly focused on the effect of main processing parameters on the microstructure and...
1468
Authors: Jie Chen
Chapter 1: Advanced Material Technology
Abstract:When machining multi-frame complex components, more than 90% of the materials would be removed, resulting in severe distortion of the parts...
143
Authors: Sha Ma, Zhi Quan Huang
Chapter 8: Biomedical Manufacturing
Abstract:The question of rock mass deformation Long-term forecast is researched base on DRNN. The construction of neural network is optimized via...
770
Authors: Wei Shin Lin, Bean Yin Lee, Yuan Chuan Hsu, Jui Chang Lin
Chapter 3: Materials Forming, Machining and Joining
Abstract:In multi-wire flat rolling process, the error of the rolled wires in thickness was due to the roller deflection and the spring back of the...
1251