Estimation of oxygen demand levels using UV-Vis spectroscopy and artificial neural networks as an effective tool for real-time, wastewater treatment control
作者： Shoshana Fogelman , Michael Myer Blumenstein , Huijun Zhao , Shanqing Zhang
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摘要: In order to effectively manage and treat wastewater, it is important constantly monitor the oxygen demand levels, so that remediation process can be implemented immediately if problems are found. To enable constant monitoring of a simple effective method based on mathematical treatment spectral absorbance patterns, using artificial neural networks (ANNs) demonstrated fro rapidly estimating biochemical (BOD) chemical (COD) values wastewater samples. The involves recording spectrum patterns from 190 350 nm processing obtained an ANN indirectly estimate BOD COD values. results indicated in most cases proposed technique (UV-ANN) worked well, as UV-ANN derived were very close those estimated standard methods. also followed trends methods closely, which make them ideal for real-time, on-line control effluents, such exceeding critical limits could identified easily.
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