Journal
COGENT ENGINEERING
Volume 5, Issue 1, Pages -Publisher
TAYLOR & FRANCIS AS
DOI: 10.1080/23311916.2018.1436929
Keywords
coagulation; wastewater treatment plant; image analysis; texture analysis; floc sensor; dosage prediction; Raspberry Pi
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Funding
- IMPREC project - Polish-Norwegian Research Fund
- Water Harmony project - SIU
- Ministry of foreign affairs of Norway
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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 techniquegrey level co-occurrence matrix (GLCM). The results of image analysis were merged with the coagulation process measurement datainlet 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 datalow 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.
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