Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China; College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China; Weihai Institute for Bionics, Jilin University, Weihai 264401, China.
China Northeast Municipal Engineering Design and Research Institute Co., Ltd., Changchun 130021, China.
Water Res. 2023 May 15;235:119878. doi: 10.1016/j.watres.2023.119878. Epub 2023 Mar 15.
For public health consideration, it is important to ensure the wastewater discharged from wastewater treatment plant is within the regulatory limits. This problem can be effectively solved by improving the accuracy and rapid characterization of water quality parameters and odor concentration of wastewater. In this paper, we proposed a novel solution to realize the precisive analysis of water quality parameters and odor concentration of wastewater by the electronic nose device. The main work of this paper was divided into three steps: 1) recognizing wastewater samples qualitatively from different sampling points, 2) analyzing the correlation between electronic nose response signals and water quality parameters and odor concentration, and 3) predicting the odor concentration and water quality parameters quantitatively. Combined with different feature extraction methods, support vector machine and linear discriminant analysis were applied as classifiers to recognize samples at different sampling points, which reported the best recognition rate of 98.83%. Partial least squares regression was applied to complete the second step, and R was reaching 0.992. As for the third step, ridge regression was used to predict water quality parameters and odor concentration with the RMSE less than 0.9476. Thus, electronic noses can be applied to determine water quality parameters and odor concentrations in the effluent discharged from wastewater plants.
出于公共卫生方面的考虑，确保污水处理厂排放的废水在规定的限制范围内是很重要的。通过提高水质参数和废水气味浓度的准确性和快速特征化，可以有效地解决这个问题。在本文中，我们提出了一种新的解决方案，通过电子鼻装置实现对废水水质参数和气味浓度的精确分析。本文的主要工作分为三个步骤：1）从不同采样点定性识别废水样品，2）分析电子鼻响应信号与水质参数和气味浓度之间的相关性，3）定量预测气味浓度和水质参数。结合不同的特征提取方法，支持向量机和线性判别分析被应用为分类器来识别不同采样点的样本，报告的最佳识别率为 98.83%。偏最小二乘回归被应用于完成第二步，R 达到 0.992。对于第三步，岭回归用于预测水质参数和气味浓度，其 RMSE 小于 0.9476。因此，电子鼻可用于确定污水处理厂排放废水中的水质参数和气味浓度。
