Application of artificial neural networks throughout the entire life cycle of coatings: A comprehensive review

doi:10.1016/j.porgcoat.2024.108279

	Application of artificial neural networks throughout the entire life cycle of coatings: A comprehensive review
	Ning, Zenglei 1,2,3; Zhao, Xia2,3,6 ; Fan, Liang 2,3; Peng, Zhongbo 1; Ma, Fubin2,3 ; Jin, Zuquan 4; Deng, Junying 5; Duan, Jizhou2,3 ; Hou, Baorong 2,3
	2024-04-01
发表期刊	PROGRESS IN ORGANIC COATINGS
ISSN	0300-9440
卷号	189 页码:22
通讯作者	Zhao, Xia([email protected])
摘要	Artificial neural networks (ANNs) have been widely employed in performance testing and life prediction throughout the entire life cycle of coatings due to their self-learning and arbitrary function approximation capabilities. This paper reviews the application research combined with the technologies including optimization algorithms, coating preparation, electrochemistry, machine vision, image processing, non-destructive testing, and simulation so as to optimize formulation design, optimize preparation process parameters, identify micro defects, and predict the service life of coating. In addition, the potential problems encountered in the practical application of neural networks are presented and some corresponding solutions are also proposed. This paper reviews the applied research of ANN in optimizing formulation design, optimizing preparation process parameters, identifying micro-defects and predicting coating service life by combining optimization algorithms, coating preparation processes, electrochemistry, machine vision, image processing, non-destructive testing and simulation.
关键词	Artificial neural networks Formulation design Preparation process micro defects Service life
DOI	10.1016/j.porgcoat.2024.108279
收录类别	SCI
语种	英语
资助项目	Chinese National Natural Science Foundation[52278286]; Chinese National Natural Science Foundation[52225905]; Chinese National Natural Science Foundation[U2106221]; Key R & D Plan Projects in Shandong Province[2023CXPT008]; Wenhai Program of the S & T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Tech- nology (Qingdao)[2021WHZZB2305]; Shandong Key Labora- tory of Corrosion Science
WOS研究方向	Chemistry ; Materials Science
WOS类目	Chemistry, Applied ; Materials Science, Coatings & Films
WOS记录号	WOS:001181439600001
出版者	ELSEVIER SCIENCE SA
WOS关键词	PARTICLE SWARM OPTIMIZATION ; THERMAL BARRIER COATINGS ; INFRARED THERMOGRAPHY ; CORROSION BEHAVIOR ; FAILURE BEHAVIOR ; DAMAGE DETECTION ; PREDICTION ; STEEL ; IDENTIFICATION ; TEMPERATURE
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/184802
专题	海洋环境腐蚀与生物污损重点实验室
通讯作者	Zhao, Xia
作者单位	1.Chongqing Jiaotong Univ, Sch Shipping & Naval Architecture, Chongqing 400074, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Marine Environm Corros & Biofouling, Qingdao 266071, Peoples R China 3.Pilot Natl Lab Marine Sci & Technol, Open Studio Marine Corros & Protect, Qingdao 266237, Peoples R China 4.Qingdao Univ Technol, Cooperat Innovat Ctr Engn Construct & Safety Shand, Qingdao 266032, Peoples R China 5.Wanhua Chem Grp Co Ltd, Yantai 264000, Peoples R China 6.Inst Oceanol, CAS Key Lab Marine Environm Corros & Biofouling, Qingdao, Peoples R China
第一作者单位	中国科学院海洋研究所
通讯作者单位	中国科学院海洋研究所
推荐引用方式 GB/T 7714	Ning, Zenglei,Zhao, Xia,Fan, Liang,et al. Application of artificial neural networks throughout the entire life cycle of coatings: A comprehensive review[J]. PROGRESS IN ORGANIC COATINGS,2024,189:22.
APA	Ning, Zenglei.,Zhao, Xia.,Fan, Liang.,Peng, Zhongbo.,Ma, Fubin.,...&Hou, Baorong.(2024).Application of artificial neural networks throughout the entire life cycle of coatings: A comprehensive review.PROGRESS IN ORGANIC COATINGS,189,22.
MLA	Ning, Zenglei,et al."Application of artificial neural networks throughout the entire life cycle of coatings: A comprehensive review".PROGRESS IN ORGANIC COATINGS 189(2024):22.