Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN

doi:10.1155/2020/6347625

	Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN
	Osman, Yousuf Babiker M.1,2; Li, Wei1,2
	2020-05-29
发表期刊	Journal of Control Science and Engineering
ISSN	16875249
卷号	2020
摘要	Real-time measurements of key effluent parameters play a highly crucial role in wastewater treatment. In this research work, we propose a soft sensor model based on deep learning which combines stacked autoencoders with neural network (SAE-NN). Firstly, based on experimental data, the secondary variables (easy-to-measure) which have a strong correlation with the biochemical oxygen demand (BOD5) are chosen as model inputs. Moreover, stochastic gradient descent (SGD) is used to train each layer of SAE to optimize weight parameters, while a strategy of genetic algorithms to identify the number of neurons in each hidden layer is developed. A soft sensor model is studied to predict the BOD5 in a wastewater treatment plant to evaluate the proposed approach. Interestingly, the experimental results show that the proposed SAE-NN-based soft sensor has a better performance in prediction than the current common methods. © 2020 Yousuf Babiker M. Osman and Wei Li.
关键词	Biochemical oxygen demand Deep learning Effluent treatment Effluents Genetic algorithms Gradient methods Learning systems Parameter estimation Reclamation Sewage treatment plants Stochastic systems Real time measurements Secondary variables Soft sensor models Stochastic gradient descent Strong correlation Wastewater treatment plants Wastewater treatment process Weight parameters
DOI	10.1155/2020/6347625
收录类别	EI ; ESCI
语种	英语
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000540596400001
出版者	Hindawi Limited, 410 Park Avenue, 15th Floor, 287 pmb, New York, NY 10022, United States
EI入藏号	20202608870253
EI主题词	Wastewater treatment
EI分类号	452 Municipal and Industrial Wastes ; Waste Treatment and Disposal - 921.6 Numerical Methods - 961 Systems Science
来源库	Compendex
分类代码	452 Municipal and Industrial Wastes; Waste Treatment and Disposal - 921.6 Numerical Methods - 961 Systems Science
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/115495
专题	电气工程与信息工程学院
通讯作者	Li, Wei
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China; 2.Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Peoples R China
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院
第一作者的第一单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Osman, Yousuf Babiker M.,Li, Wei. Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN[J]. Journal of Control Science and Engineering,2020,2020.
APA	Osman, Yousuf Babiker M.,&Li, Wei.(2020).Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN.Journal of Control Science and Engineering,2020.
MLA	Osman, Yousuf Babiker M.,et al."Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN".Journal of Control Science and Engineering 2020(2020).

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