Paper Title:
Analysis of Electromagnetic Inverse Model of Resistance Spot Welding
  Abstract

Resistance spot welding (RSW) is an important welding process in modern industrial production, and the quality of welding nugget determines the strength of products to a large extent. Limited by the level of RSW quality monitor, however, RSW has rarely been applied to the fields with high welding quality requirements. Associated with the inversion theory, in this paper, an electromagnetic inverse model of RSW was established, and the analysis of influence factors, such as the layout of the probes, the discrete program and the regularization method, was implemented as well. The result shows that the layout of the probe and the regularization method has great influence on the model. When the probe is located at the y direction of x-axis or the x direction of y-axis and Conjugate Gradient method is selected, a much better outcome can be achieved.

  Info
Periodical
Advanced Materials Research (Volumes 160-162)
Edited by
Guojun Zhang and Jessica Xu
Pages
974-979
DOI
10.4028/www.scientific.net/AMR.160-162.974
Citation
N. F. Fan, Z. Luo, Y. Li, W. B. Xuan, "Analysis of Electromagnetic Inverse Model of Resistance Spot Welding", Advanced Materials Research, Vols. 160-162, pp. 974-979, 2011
Online since
November 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: Jia Xi Du, Hong Shen, Su Fang Fu, Xin Ning
Chapter 11: Modeling, Analysis and Simulation of Manufacturing Processes
Abstract:According to the law of rigid body around fixed axis rotation, established the mathematical model of motor drive current and instantaneous...
2184
Authors: Yao Yan, Hong Hua Wang
Chapter 4: Mechatronics and Automation Manufacturing Systems, Control Technologies
Abstract:This paper analysis the control principle of the asynchronous motor soft-start with discrete variable frequency technology.A simulation model...
686
Authors: Xiang Jun Wang
Chapter 6: Data Acquisition and Data Processing, Computational Techniques
Abstract:It is difficult to evaluate water quality, because there are lots of influence factors. It presents discrete Hopfield neural network to...
1338