Research on the membrane fouling diagnosis of MBR membrane module based on ECA-CNN

doi:10.1016/j.jece.2022.107649

	Research on the membrane fouling diagnosis of MBR membrane module based on ECA-CNN
	Shi, Yaoke 2; Wang, Zhiwen 1,2,3; Du, Xianjun 1,2,3; Ling, Guobi 2; Jia, Wenchao 2; Lu, Yanrong 1,2,3
刊名	JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
	2022-06-01
卷号	10 期号:3
关键词	Membrane fouling Convolutional neural network Attention mechanism Feature extraction Fault diagnosis
ISSN号	2213-2929
DOI	10.1016/j.jece.2022.107649
英文摘要	In order to make it easier to extract fault features, reduce model complexity and improve the accuracy of membrane fouling diagnosis on membrane modules, a membrane module fault diagnosis method based on attention mechanism and convolutional neural network (ECA-CNN) is proposed in this study. First, the convolution kernel is used to extract the image features of the input layer. At the same time, a rectified linear unit (ReLU) is connected after each convolution layer, and a batch normalization layer (BN) is added to solve the problem of internal co variate shift, so as improving the expression ability of nonlinear models. Secondly, in batches after the first layer, add the attention mechanism module (ECA), extract the important features and connect to the pooling layer, reduce the network calculation complexity, and improve the accuracy and efficiency of the network. Finally, the membrane module operating data is used as the research object to conduct fault diagnosis experiments as verification. This method can improve the diagnosis accuracy to a large extent, in which the highly difficult fault classification and localization can be accomplished. Besides, the effluent quality from the membrane water treatment system may be improved with this method with less energy consumption, paving the theoretical foundation for actual production.
WOS研究方向	Engineering
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000794220100002
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/158637]
专题	电气工程与信息工程学院
作者单位	1.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Peoples R China; 2.Lanzhou Univ Technol, Coll Elect & Informat Engn, 36 Pengjiaping Rd, Lanzhou 730050, Peoples R China; 3.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Shi, Yaoke,Wang, Zhiwen,Du, Xianjun,et al. Research on the membrane fouling diagnosis of MBR membrane module based on ECA-CNN[J]. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING,2022,10(3).
APA	Shi, Yaoke,Wang, Zhiwen,Du, Xianjun,Ling, Guobi,Jia, Wenchao,&Lu, Yanrong.(2022).Research on the membrane fouling diagnosis of MBR membrane module based on ECA-CNN.JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING,10(3).
MLA	Shi, Yaoke,et al."Research on the membrane fouling diagnosis of MBR membrane module based on ECA-CNN".JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 10.3(2022).