Study on BPNN based welding joint properties soft sensing method

doi:10.1109/ICNC.2010.5584606

	Study on BPNN based welding joint properties soft sensing method
	Yufen, Gu1 ; Cheng, Xue 1; Yu, Shi 2; Ding, Fan 2
	2010
会议录名称	Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
卷号	4
页码	1865-1868
出版者	IEEE Computer Society
摘要	It is found that the mechanical properties of welded joints is mainly related to the welding heating input and complicated mutual effects in multi composition welding material. According to this principle, a soft sensor model based on the BP neural network (BPNN) is designed. The soft sensing BPNN has been constructed by use of the BP network toolkit of the Matlab software. The dates of five kinds of Low-Ally steels mechanical properties under different welding thermal cycle which used to train and test the BPNN have been obtained by welding thermal simulator. In this way, the soft sensing model for welding joint mechanical properties testing has been established. The BPNN has been tested by use of testing samples from the obtained data. By comparing the predicting date and the actual date, it shows that the soft sensing model has acceptable precision. The soft sensing method provides a new way for predication of mechanical properties of welding joints. © 2010 IEEE.
关键词	MATLAB Mechanical properties Neural networks BP neural networks Mechanical properties testing Soft sensing Soft sensing method Soft sensor models Soft-sensing model Welding joints Welding thermal cycles
DOI	10.1109/ICNC.2010.5584606
收录类别	EI
语种	英语
EI入藏号	20104613375252
EI主题词	Welding
来源库	Compendex
分类代码	538.2 Welding - 921 Mathematics - 951 Materials Science
引用统计	无
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/116475
专题	材料科学与工程学院省部共建有色金属先进加工与再利用国家重点实验室
作者单位	1.Key Laboratory of Non-ferrous Metal Alloys and Processing, Lanzhou University of Technology, Ministry of Education, 730050, Lanzhou, China; 2.State Key Laboratory of Gansu Advanced Non-ferrous Metal Materials, Lanzhou University of Technology, 730050, Lanzhou, China
第一作者单位	兰州理工大学
推荐引用方式 GB/T 7714	Yufen, Gu,Cheng, Xue,Yu, Shi,et al. Study on BPNN based welding joint properties soft sensing method[C]:IEEE Computer Society,2010:1865-1868.