Prediction for emission of environmental burden in GTAW based on combined neural network

JIANG Weiqi; HUANG Haihong; LIU Yun; LI Lei; LIU Zhifeng

doi:10.12073/j.hjxb.20211104002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2022 > 43(10): 77-85. > DOI: 10.12073/j.hjxb.20211104002

JIANG Weiqi, HUANG Haihong, LIU Yun, LI Lei, LIU Zhifeng. Prediction for emission of environmental burden in GTAW based on combined neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2022, 43(10): 77-85. DOI: 10.12073/j.hjxb.20211104002

Citation:

PDF (1540 KB)

Prediction for emission of environmental burden in GTAW based on combined neural network

JIANG Weiqi^{1, 2,},
HUANG Haihong^{1, 2, ,},
LIU Yun^{1, 2},
LI Lei^{1, 2},
LIU Zhifeng^{1, 2}

1.
Hefei University of Technology, Key Laboratoryof Green Design and Manufacturing of Mechanical Industry, Hefei, 230009
2.
Hefei University of Technology, Hefei 230009

More Information

Received Date: November 03, 2021
Available Online: July 14, 2022

Graphical Abstract

Abstract

Abstract

The model is established for quantitative predicting the generation of environmental burdens in welding. The key factors for influencing the emissions in GTAW are determined using Taguchi method, including welding current, nozzle height, and welding time. Moreover, the emission model based on RBF-BP neural network was established. It can be predicting the emissions of environmental burden in GTAW when different welding parameters are adapted. The results show that the average error is 6.63% for predicting emissions of environmental burden using RBF-BP combination neural network model. The welding current, nozzle height and welding time are positively correlated with the generation of environmental burdens. That can provide support for reducing the emission of welding environmental burden and formulating reasonable welding process route.
- GTAW,
- welding emissions,
- orthogonal test,
- neural network,
- prediction model

FullText(HTML)

References (25)

References

中国产业信息网数据中心. 2020-2026年中国焊接材料行业市场营销战略及未来发展潜力报告 [EB/OL]. https://www.chyxx.com/research/202006/877599.html. 2020.

Data Center of China Industrial Information Network. Report on marketing strategy and future development potential of China welding materials industry (2020-2026) [EB/OL]. https://www.chyxx.com/research/202006/877599.html.2020.

Aravind S, Das A D. An examination on GTAW samples of 7-series aluminium alloy using response surface methodology[J]. Materials Today: Proceedings, 2021, 37: 614 − 620. doi: 10.1016/j.matpr.2020.05.623

Vinothkumar H, Balakrishnan M, Gulanthaivel K, et al. Investigation on effects of flux assisted GTAW welding process on mechanical, metallurgical characteristics of dissimilar metals SS 304 and SS 316 L[J]. Materials Today:Proceedings, 2020, 33: 3191 − 3196. doi: 10.1016/j.matpr.2020.04.143

郭枭, 徐锴, 吕晓春, 等. 钨极氩弧焊热输入与面积稀释率关系的探讨[J]. 压力容器, 2021, 38(6): 10 − 14.

GUO Xiao, XU Kai, Lü Xiaochun, et al. Investigation on relations between heat input and dilution ratio for GTAW[J]. Pressure Vessel Technology, 2021, 38(6): 10 − 14.

D’oliveira A, Paredes R S C, Santos R L C. Pulsed current plasma transferred arc hardfacing[J]. Journal of Materials Processing Technology, 2006, 171(2): 167 − 174. doi: 10.1016/j.jmatprotec.2005.02.269

吴仲伟, 夏金兵, 时惜今. 等离子体焊接除尘装置设计与数值模拟[J]. 中国机械工程, 2020, 30(23): 2862 − 2869.

Wu Zhongwei, Xia Jinbing, Shi Xijin. Design and numerical simulation of plasma welding fume removal devices[J]. China Mechanical Engineering, 2020, 30(23): 2862 − 2869.

黎雪花, 吴春霞, 胡毅, 等. 三种焊接作业职业危害因素对比分析[J]. 中华劳动卫生职业病杂志, 2022, 40(4): 288 − 291.

Li Xuehua, Wu Chunxia, Hu Yi, et al. Comparative analysis on occupational hazards of three welding operations[J]. Chinese Journal of Industrial Hygiene and Occupational Diseases, 2022, 40(4): 288 − 291.

闪顺章, 王从陆. 焊接烟尘扩散数学模型研究[J]. 中国安全生产科学技术, 2018, 14(6): 177 − 181. doi: 10.11731/j.issn.1673-193x.2018.06.028

Shan Shunzhang, Wang Conglu. Study on numerical model for diffusion of welding fume[J]. Journal of Safety Science and Technology, 2018, 14(6): 177 − 181. doi: 10.11731/j.issn.1673-193x.2018.06.028

张恒铭, 石玗, 李春凯, 等. 工艺参数对自保护药芯焊丝焊接烟尘的影响[J]. 焊接学报, 2020, 41(11): 31 − 37.

ZHANG Hengming, SHI Yu, LI Chunkai, et al. Effect of process parameters on welding fume of selfshielded flux cored wire[J]. Transactions of the China Welding Institution, 2020, 41(11): 31 − 37.

鲍升凯, 卜智翔, 王若玺, 等. 焊接材料对形成焊接烟尘影响的研究进展[J]. 焊接, 2018(10): 20 − 25.

Bao Shengkai, Bu Zhixiang, Wang Ruoxi, et al. Research progress on influence of welding consumables on formation of welding fume[J]. Welding & Joining, 2018(10): 20 − 25.

张艳君. 焊接烟尘的治理措施分析[J]. 环境科学与管理, 2007(4): 105 − 107. doi: 10.3969/j.issn.1673-1212.2007.04.032

Zhang Yanjun. Manage measures analysis of welding dust[J]. Environment Science and Management, 2007(4): 105 − 107. doi: 10.3969/j.issn.1673-1212.2007.04.032

Amza G, Cicic D T, Rontescu C, et al. Theoretical and experimental research on the environmental impact of certain welding processes[C]// Proceedings of the 4th IASME/WSEAS International Conference on Energy & environment, 2009.

Pires I, Quintino L, Amaral V, et al. Reduction of fume and gas emissions using innovative gas metal arc welding variants[J]. The International Journal of Advanced Manufacturing Technology, 2010, 50(5): 557 − 567.

Guha N, Loomis D, Guyton K Z, et al. Carcinogenicity of welding, molybdenum trioxide, and indium tin oxide[J]. The Lancet Oncology, 2017, 18(5): 581 − 582. doi: 10.1016/S1470-2045(17)30255-3

卜智翔, 鲍升凯, 王立世, 等. 熔化极气体保护焊发尘率研究进展[J]. 焊接, 2016(7): 17 − 21. doi: 10.3969/j.issn.1001-1382.2016.07.004

Bu Zhixiang, Bao Shengkai, Wang Lishi, et al. A review of fume formation rate in gas metal arc welding[J]. Welding & Joining, 2016(7): 17 − 21. doi: 10.3969/j.issn.1001-1382.2016.07.004

Ioffe I, Maclean D, Perelman N, et al. Fume formation rate at globular to spray mode transition during welding[J]. Journal of Physics D:Applied Physics, 1995, 28(12): 2473 − 2477. doi: 10.1088/0022-3727/28/12/013

Dennis J H, Hewitt P J, Redding C, et al. A model for prediction of fume formation rate in gas metal arc welding (GMAW), globular and spray modes, DC electrode positive[J]. The Annals of Occupational Hygiene, 2001, 45(2): 105 − 113. doi: 10.1093/annhyg/45.2.105

Deam R T, Simpson S W, Haidar J. A semi-empirical model of the fume formation from gas metal arc welding[J]. Journal of Physics D:Applied Physics, 2000, 33(11): 1393 − 1402. doi: 10.1088/0022-3727/33/11/320

卜智翔, 鲍升凯, 王立世, 等. 基于熔滴过渡模型的 GMAW焊接发尘率计算[J]. 焊接学报, 2018, 39(2): 97 − 100.

Bu Zhixiang, Bao Shengkai, Wang Lishi, et al. Calculation of fume formation rate in GMAW process based on metal transfer model[J]. Transactions of the China Welding Institution, 2018, 39(2): 97 − 100.

Vimal K E K, Vinodh S, Raja A. Optimization of process parameters of SMAW process using NN-FGRA from the sustainability view point[J]. Journal of Intelligent Manufacturing, 2017, 28(6): 1459 − 1480. doi: 10.1007/s10845-015-1061-5

Wang B, Lin R, Liu D, et al. Investigation of the effect of humidity at both electrode on the performance of PEMFC using orthogonal test method[J]. International Journal of Hydrogen Energy, 2019, 44(26): 13737 − 13743. doi: 10.1016/j.ijhydene.2019.03.139

王万良, 张兆娟, 高楠, 等. 基于人工智能技术的大数据分析方法研究进展[J]. 计算机集成制造系统, 2019, 25(3): 5 − 23.

Wang Wanliang, Zhang Zhaojuan, Gao Nan, et al. Progress of big data analytics methods based on artificial intelligence techonlogy[J]. Computer Integrated Manufacturing Systems, 2019, 25(3): 5 − 23.

唐正魁, 董俊慧, 张永志, 等. 混合聚类RBF神经网络焊接接头力学性能预测[J]. 焊接学报, 2014, 35(12): 105 − 108.

Tang Zhengkui, Dong Junhui, Zhang Yongzhi, et al. Prediction of mechanical properties of welding joints by hybrid cluster fuzzy rbf neural network[J]. Transactions of the China Welding Institution, 2014, 35(12): 105 − 108.

Tomaz I V, Colaço F H G, Sarfraz S, et al. Investigations on quality characteristics in gas tungsten arc welding process using artificial neural network integrated with genetic algorithm[J]. The International Journal of Advanced Manufacturing Technology, 2021, 113(11): 3569 − 3583.

朱师琦. GMAW焊接烟尘形成速率的工艺因素影响及预测研究[D]. 武汉: 湖北工业大学, 2020.

Zhu Shiqi. Studies on technological factors impact and prediction of fume emission rate in gas metal arc welding[D]. Wuhan: Hubei University of Technology, 2020.

[1]	SUN Jiahao, ZHANG Chaoyong, WU Jianzhao, ZHANG Shuaikun, ZHU Lei. Prediction of weld profile of 316L stainless steel based on generalized regression neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2021, 42(12): 40-47. DOI: 10.12073/j.hjxb.20210526003
[2]	LI Xiangwei, FANG Ji, ZHAO Shangchao. Master S-N curve fitting method of welded structure and software development[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(1): 80-85. DOI: 10.12073/j.hjxb.20191018001
[3]	ZOU Yuanyuan, ZUO Kezhu, FANG Lingshen, LI Pengfei. Recognition of weld seam for tailored blank laser welding based on least square support vector machine[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(2): 77-81. DOI: 10.12073/j.hjxb.2019400046
[4]	XUE Jiaxiang, JIANG Chengfeng, ZHANG Xiaoli, ZHU Xiaojun, ZHU Qiang. Research on unified adjustment of pulsed MIG welding parameters based on least squares method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2014, 35(8): 75-78.
[5]	LIN Naichang, YANG Xiaoxiang, LIN Wen-jian, ZHU Zhibin. Defect detection of TOFD D scanning image based on parabola Htting[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2014, 35(6): 105-108.
[6]	ZHU Xiaopeng, ZHANG Ke, TU Zhiqiang, HUANG Jie. Calibration of relative position and orientation between robot and positioner based on spheres fitting method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2013, (1): 41-44.
[7]	QIN Tao, ZHANG Ke, DENG Jingyu, JIN Xin. Algorithm of extracting feature lines in welding seam image based on improved least-square method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2012, (2): 33-36.
[8]	ZHANG Ke, WU Yixiong, LV Xueqin, JIN Xin. Real-time identification of heading angle based on least squares estimator for welding mobile robot[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (6): 13-16.
[9]	LI Ruihua, MENG Guoxiang, GONG Liang, ZHANG Ke. Partial least square approach for multi-parameter assessment of resistance spot welding quality[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (3): 49-52.
[10]	CAI Yan, YANG Hai-lan, XU Xin, WU Yi-xiong. Spatter model of CO₂ arc welding based on partial least-square regression method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2004, (5): 125-128.

Cited By

Get Citation

PDF

XML

Article views (303) PDF downloads (33)

Turn off MathJax

Article Contents

Abstract

References

Prediction for emission of environmental burden in GTAW based on combined neural network

Abstract

References

Related Articles

Catalog

Prediction for emission of environmental burden in GTAW based on combined neural network

Abstract

References

Related Articles

Catalog

Export File

Citation

Format

Content