Floc sensor prototype tested in the municipal wastewater treatment plant
A novel floc sensor prototype was tested in a Norwegian municipal wastewater treatment plant. The resulting images of flocs, captured using a specially designed software, were analysed by texture image analysis technique—grey level co-occurrence matrix (GLCM). The results of image analysis were merg...
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2018-01-01
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Online Access: | http://dx.doi.org/10.1080/23311916.2018.1436929 |
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doaj-47ccaec13f084d7b8ad409ce31a213df2021-03-02T14:46:46ZengTaylor & Francis GroupCogent Engineering2331-19162018-01-015110.1080/23311916.2018.14369291436929Floc sensor prototype tested in the municipal wastewater treatment plantN. Sivchenko0K. Kvaal1H. Ratnaweera2Norwegian University of Life SciencesNorwegian University of Life SciencesNorwegian University of Life SciencesA novel floc sensor prototype was tested in a Norwegian municipal wastewater treatment plant. The resulting images of flocs, captured using a specially designed software, were analysed by texture image analysis technique—grey level co-occurrence matrix (GLCM). The results of image analysis were merged with the coagulation process measurement data—inlet and outlet wastewater parameters. The data based only on GLCM textural features resulted in 96.6% explained total variance by two principal components and distinguished two classes in the data—low and high outlet turbidity values. The predicted by partial least squares regression (PLSR) coagulant dosages precisely followed the reference dosages, explained Y total variance by 3 factors equals 91.8% for calibration and 77.9% for validation. Results of the studies indicate that the GLCM method and sensor prototype can be used for an improvement of coagulant dosage control. Tested sensor prototype gives a solid basis for development of the low-cost floc sensor.http://dx.doi.org/10.1080/23311916.2018.1436929coagulationwastewater treatment plantimage analysistexture analysisfloc sensordosage predictionraspberry pi |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
N. Sivchenko K. Kvaal H. Ratnaweera |
spellingShingle |
N. Sivchenko K. Kvaal H. Ratnaweera Floc sensor prototype tested in the municipal wastewater treatment plant Cogent Engineering coagulation wastewater treatment plant image analysis texture analysis floc sensor dosage prediction raspberry pi |
author_facet |
N. Sivchenko K. Kvaal H. Ratnaweera |
author_sort |
N. Sivchenko |
title |
Floc sensor prototype tested in the municipal wastewater treatment plant |
title_short |
Floc sensor prototype tested in the municipal wastewater treatment plant |
title_full |
Floc sensor prototype tested in the municipal wastewater treatment plant |
title_fullStr |
Floc sensor prototype tested in the municipal wastewater treatment plant |
title_full_unstemmed |
Floc sensor prototype tested in the municipal wastewater treatment plant |
title_sort |
floc sensor prototype tested in the municipal wastewater treatment plant |
publisher |
Taylor & Francis Group |
series |
Cogent Engineering |
issn |
2331-1916 |
publishDate |
2018-01-01 |
description |
A novel floc sensor prototype was tested in a Norwegian municipal wastewater treatment plant. The resulting images of flocs, captured using a specially designed software, were analysed by texture image analysis technique—grey level co-occurrence matrix (GLCM). The results of image analysis were merged with the coagulation process measurement data—inlet and outlet wastewater parameters. The data based only on GLCM textural features resulted in 96.6% explained total variance by two principal components and distinguished two classes in the data—low and high outlet turbidity values. The predicted by partial least squares regression (PLSR) coagulant dosages precisely followed the reference dosages, explained Y total variance by 3 factors equals 91.8% for calibration and 77.9% for validation. Results of the studies indicate that the GLCM method and sensor prototype can be used for an improvement of coagulant dosage control. Tested sensor prototype gives a solid basis for development of the low-cost floc sensor. |
topic |
coagulation wastewater treatment plant image analysis texture analysis floc sensor dosage prediction raspberry pi |
url |
http://dx.doi.org/10.1080/23311916.2018.1436929 |
work_keys_str_mv |
AT nsivchenko flocsensorprototypetestedinthemunicipalwastewatertreatmentplant AT kkvaal flocsensorprototypetestedinthemunicipalwastewatertreatmentplant AT hratnaweera flocsensorprototypetestedinthemunicipalwastewatertreatmentplant |
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