Application of in-situ micro laser transmission on real-time monitoring of flocculation process

Qin, Y; Jia, H; Liu, W; Lu, N; Ngo, HH; Wang, J

Application of in-situ micro laser transmission on real-time monitoring of flocculation process

Qin, Y Jia, H Liu, W Lu, N Ngo, HH Wang, J

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Journal of Water Process Engineering, 2023, 51, pp. 103364
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Qin, Y
dc.contributor.author	Jia, H
dc.contributor.author	Liu, W
dc.contributor.author	Lu, N
dc.contributor.author	Ngo, HH
dc.contributor.author	Wang, J
dc.date.accessioned	2024-02-01T03:38:11Z
dc.date.available	2024-02-01T03:38:11Z
dc.date.issued	2023-02-01
dc.identifier.citation	Journal of Water Process Engineering, 2023, 51, pp. 103364
dc.identifier.issn	2214-7144
dc.identifier.uri	http://hdl.handle.net/10453/175209
dc.description.abstract	A low-cost in-situ micro laser transmission (IMLT) analysis system for particle size monitoring based on the principle of laser transmission extinction was developed to monitor the flocculation process. In this study, the IMLT system was used to obtain the voltage generated with the changes of flocculant dosage and floc sizes in different flocculation stages. A typical machine learning model, convolution neural network (CNN) method was built to manage the flocculant dosage, detection voltage and floc size to improve the accuracy of the correlation between the them. Results of IMLT revealed that the particle size of flocs was inversely proportional to the voltage, and a larger final voltage R value indicated better effects of flocculation and sedimentation. The correlation between the particle size obtained by CNN training and measured particle size was 42.4 % and 30.5 % higher than that without training at low and high concentrations, respectively. IMLT is effective in reflecting the floc sedimentation, stability and dynamic influence of the coagulant aid on flocculation system.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Journal of Water Process Engineering
dc.relation.isbasedon	10.1016/j.jwpe.2022.103364
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering, 0907 Environmental Engineering
dc.subject.classification	4004 Chemical engineering
dc.subject.classification	4005 Civil engineering
dc.subject.classification	4011 Environmental engineering
dc.title	Application of in-situ micro laser transmission on real-time monitoring of flocculation process
dc.type	Journal Article
utslib.citation.volume	51
utslib.for	0905 Civil Engineering
utslib.for	0907 Environmental Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	closed_access	*
dc.date.updated	2024-02-01T03:38:09Z
pubs.publication-status	Published
pubs.volume	51

Abstract:

A low-cost in-situ micro laser transmission (IMLT) analysis system for particle size monitoring based on the principle of laser transmission extinction was developed to monitor the flocculation process. In this study, the IMLT system was used to obtain the voltage generated with the changes of flocculant dosage and floc sizes in different flocculation stages. A typical machine learning model, convolution neural network (CNN) method was built to manage the flocculant dosage, detection voltage and floc size to improve the accuracy of the correlation between the them. Results of IMLT revealed that the particle size of flocs was inversely proportional to the voltage, and a larger final voltage R value indicated better effects of flocculation and sedimentation. The correlation between the particle size obtained by CNN training and measured particle size was 42.4 % and 30.5 % higher than that without training at low and high concentrations, respectively. IMLT is effective in reflecting the floc sedimentation, stability and dynamic influence of the coagulant aid on flocculation system.

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http://hdl.handle.net/10453/175209