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, Gu 1; Cheng, Xue 1; Yu, Shi 2; Ding, Fan 2
	2010
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
卷号	4
DOI	10.1109/ICNC.2010.5584606
页码	1865-1868
英文摘要	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.
会议录	Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://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
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]. 见:.