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Research on raw water quality assessment oriented to drinking water treatment based on the SVM model

Dongsheng Wang

Open publisher page 11 citations

Abstract

Raw water quality variation has a great effect on drinking water treatment. To improve the adaptivity of drinking water treatment and stabilize the quality of treated water, a raw water quality assessment method, which is based upon the support vector machine (SVM), is developed in this study. Compared to existing raw water quality assessment methods, the assessment method studied herein is oriented to drinking water treatment and can directly be used for the control of the chemical (alum and ozone) dosing process. To this end, based upon the productive experiences and the analysis of the operating data of water supply, a raw water quality assessment standard oriented to drinking water treatment is proposed. A raw water quality model is set up to assess the raw water quality based upon the SVM technique. Based upon the raw water quality assessment results, a feedforward–feedback control scheme has been designed for the chemical dosing process control of drinking water treatment. Thus, the chemical dosage can be adjusted in time to cope with raw water quality variations and hence, the quality of the treated water is stabilized. Experimental results demonstrate the improved effectiveness of the proposed method of raw water quality assessment and the feedforward–feedback control scheme.

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What this paper is about

Raw water quality variation has a great effect on drinking water treatment. To improve the adaptivity of drinking water treatment and stabilize the quality of treated water, a raw water quality assessment method, which is based upon the support vector machine (SVM), is developed in this study. Compared to existing raw water quality assessment methods, the assessment method studied herein is oriented to drinking water treatment and can directly be used for the control of the chemical (alum and ozone) dosing process. To this end, based upon the productive experiences and the analysis of the operating data of water supply, a raw water quality assessment standard oriented to drinking water treatment is proposed. A raw water quality model is set up to assess the raw water quality based upon the SVM technique. Based upon the raw water quality assessment results, a feedforward–feedback control scheme has been designed for the chemical dosing process control of drinking water treatment. Thus, the chemical dosage can be adjusted in time to cope with raw water quality variations and hence, the quality of the treated water is stabilized. Experimental results demonstrate the improved effectiveness of the proposed method of raw water quality assessment and the feedforward–feedback control scheme.

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Available abstract

Raw water quality variation has a great effect on drinking water treatment. To improve the adaptivity of drinking water treatment and stabilize the quality of treated water, a raw water quality assessment method, which is based upon the support vector machine (SVM), is developed in this study. Compared to existing raw water quality assessment methods, the assessment method studied herein is oriented to drinking water treatment and can directly be used for the control of the chemical (alum and ozone) dosing process. To this end, based upon the productive experiences and the analysis of the operating data of water supply, a raw water quality assessment standard oriented to drinking water treatment is proposed. A raw water quality model is set up to assess the raw water quality based upon the SVM technique. Based upon the raw water quality assessment results, a feedforward–feedback control scheme has been designed for the chemical dosing process control of drinking water treatment. Thus, the chemical dosage can be adjusted in time to cope with raw water quality variations and hence, the quality of the treated water is stabilized. Experimental results demonstrate the improved effectiveness of the proposed method of raw water quality assessment and the feedforward–feedback control scheme.

Key concepts: Raw water, Water quality, Water treatment, Alum, Raw data, Raw material, Environmental science, Quality (philosophy)

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