Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data

doi:10.1049/cim2.12043

	Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data
	Zhang, Zhongke 1; Li, Zhao 3; Zhao, Changzhong 2
刊名	IET Collaborative Intelligent Manufacturing
	2022-03-01
卷号	4 期号:1 页码:45-57
关键词	Big data Display devices Failure analysis Fault detection Light emission Metadata Program debugging Trees (mathematics) Virtual private networks Cloud platforms Condition monitoring and faults diagnosis Electronics materials Fault prediction Faults diagnosis Manufacturing industries On condition monitoring Production line Window control center configuration Windows control centers
DOI	10.1049/cim2.12043
英文摘要	With the continuous upgrading and transformation of the intelligentisation of China's manufacturing industry, and in response to the requirements for further intelligentisation of the phosphor copper ball production line proposed by a new electronic material company, this study proposes a fault prediction and diagnosis method based on big data. A high-efficiency distributed big data platform is constructed, and a workshop-level monitoring centre with the Windows control centre (WinCC) as the core is formed. The WinCC configuration software is used to monitor the key parameters of the equipment during the operation phase, and the login interface is configured according to the requirements of workshop information integration, for example, display interface, alarm interface, debugging interface, trend graph and other common functions. Cloud platforms and virtual private network (VPN) communication are used to realise remote maintenance. Aiming at the common fault problems in the production process, an expert diagnosis system based on fault tree analysis is constructed by fusing the fault tree theory and expert systems. The fault tree model of the unqualified phosphor copper ball production quality and the failure of the hydraulic system is highlighted. Therefore, ensuring the safety of the phosphor copper ball production line is of great significance to the entire production system. © 2021 The Authors. IET Collaborative Intelligent Manufacturing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
语种	英语
出版者	John Wiley and Sons Inc
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/157958]
专题	材料科学与工程学院
作者单位	1.School of Materials Science and Engineering, Lanzhou University of Technology, Lanzhou, China; 2.Nickel-Metropolis Industrial Company, Jinchang Gansu, China 3.School of Materials Science and Engineering, Northeastern University, Shenyang, China;
推荐引用方式 GB/T 7714	Zhang, Zhongke,Li, Zhao,Zhao, Changzhong. Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data[J]. IET Collaborative Intelligent Manufacturing,2022,4(1):45-57.
APA	Zhang, Zhongke,Li, Zhao,&Zhao, Changzhong.(2022).Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data.IET Collaborative Intelligent Manufacturing,4(1),45-57.
MLA	Zhang, Zhongke,et al."Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data".IET Collaborative Intelligent Manufacturing 4.1(2022):45-57.