On-line quality estimation in resistance spot welding

被引：38

作者：

Li, W ^{[1
]}

Hu, SJ ^{[1
]}

Ni, J ^{[1
]}

机构：

[1] Univ Michigan, Dept Mech Engn & Appl Mech, Ann Arbor, MI 48109 USA

来源：

JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME | 2000年 / 122卷 / 03期

关键词：

D O I：

10.1115/1.1286814

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A neural network model is developed for on-line nugget size estimation in resistance spot welding. The variables used consist of features extracted from both controllable process input variables and on-line signals. A systematic signal and feature selection procedure is developed. The three commonly observed on-line signals, dynamic resistance, force, and electrode displacement have been proven to carry similar information. Thus, only dynamic resistance is used in the model. The obtained model has been demonstrated to be robust over various welding conditions including electrode wear. [S1087-1357(00)01204-1].

引用

页码：511 / 512

页数：2