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Implementation of Fuzzy Logic Model on Textile Wastewater Treatment by Electrocoagulation Proсess
Journal of Water Chemistry and Technology ( IF 0.5 ) Pub Date : 2021-08-02 , DOI: 10.3103/s1063455x21030127
Kubra Ulucan-Altuntas 1 , Fatih Ilhan 1 , Caner Kasar 1 , Mustafa Talha Gonullu 1
Affiliation  

Abstract

A high concentration of colour, chemical oxidation demand (COD) and low biodegradability make textile wastewater a major source of pollution. While physicochemical processes, adsorption and chemical coagulation were the most commonly applied treatment methods for textile wastewater, the electrocoagulation process as compared to these conventional methods, produces less sludge with high colour removal efficiency. In this study, textile wastewater obtained from industry was treated by electrocoagulation process and the results were evaluated with fuzzy logic, an artificial intelligence-based modelling, which is used for advanced control and is employed in many environmental engineering applications, from wastewater treatment to air pollution estimation. Current density, initial pH and electrolysis time were selected as variables and utilized to predict COD, total organic carbon (TOC) and colour removal efficiencies. The experimental studies were applied to the developed fuzzy logic model to demonstrate the model accuracy. Using fuzzy logic model, surface maps were prepared for COD, TOC and colour removal. According to the obtained results, while Colour can be removed by 90%, COD and TOC can be removed by approximately 55 and 80%, respectively. While low pH was more efficient in COD and TOC removal, high pH values were shown to be efficient in colour removal. Time was the most efficient parameter for the electrocoagulation treatment and 15 minutes of reaction time was obtained as optimum value. Moreover, the results were evaluated with the multiple regression model. The obtained equations were maximized to determine the optimum conditions. These optimum conditions are 60 mA/cm2 of current density, pH 5 and 20 min of reaction time. When these parameters were examined, colour, TOC and COD removal efficiencies were attained as 89, 86 and 61%, respectively.



中文翻译:

电凝法处理纺织废水的模糊逻辑模型的实现

摘要

高浓度的颜色、化学氧化需求 (COD) 和低生物降解性使纺织废水成为主要的污染源。虽然物理化学工艺、吸附和化学混凝是纺织废水最常用的处理方法,但与这些传统方法相比,电混凝工艺产生的污泥更少,脱色效率高。在这项研究中,从工业中获得的纺织废水通过电凝过程进行处理,并用模糊逻辑评估结果,模糊逻辑是一种基于人工智能的建模,用于高级控制并用于许多环境工程应用,从废水处理到空气污染估计。当前密度,选择初始 pH 值和电解时间作为变量并用于预测 COD、总有机碳 (TOC) 和颜色去除效率。实验研究被应用于开发的模糊逻辑模型,以证明模型的准确性。使用模糊逻辑模型,为 COD、TOC 和颜色去除准备表面图。根据获得的结果,虽然颜色可以去除 90%,但 COD 和 TOC 可以分别去除约 55% 和 80%。虽然低 pH 值在 COD 和 TOC 去除方面更有效,但高 pH 值显示出在颜色去除方面有效。时间是电凝处理最有效的参数,15分钟的反应时间为最佳值。此外,用多元回归模型评估结果。将获得的方程最大化以确定最佳条件。这些最佳条件是 60 mA/cm2电流密度,pH 5 和 20 分钟的反应时间。当检查这些参数时,颜色、TOC 和 COD 去除效率分别达到 89%、86% 和 61%。

更新日期:2021-08-03
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