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基于双光源在线监测化学需氧量的传感器设计

Design of Sensor for Online Detecting Chemical Oxygen Demand Based on Dual-Light Source

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摘要

化学需氧量(COD)是水源地水质有机物污染的一项重要指标,是水质监测的必检参数之一。基于紫外分光光度法(UV法)的COD在线监测是全面实施污染源在线实时监测的重要手段。针对传统试剂法COD在线检测存在的问题,设计了基于双光源检测方法的COD在线检测传感器。从理论方面分析了浊度、光源温度和水样温度变化对测量值的影响并提出了温度补偿和浊度补偿的方法。实验结果表明,传感器的重复性误差为3.12%,实际水样对比实验最大相对误差为6.18%,浊度补偿和温度补偿可靠性较高。所制COD传感器能够对水样COD浓度进行准确测量,满足水质在线监测设备的技术要求。

Abstract

Chemical oxygen demand (COD) is an important indicator of organic matter pollution in water source and one of the necessary parameters for monitoring water quality. Detecting the COD based on ultraviolet spectrophotometry is an important method for online real-time monitoring of pollution sources. This study designs a COD online detection sensor based on a dual-light source to solve the problems of COD online detection using the traditional reagent method. The influences of turbidity, light-source temperature, and water-sample temperature on measurement are analyzed theoretically. Methods of temperature and turbidity compensations are then proposed. Experimental results show that the repeatability error of the sensor is 3.12%, whereas the maximum relative error of the actual water-sample comparison experiment is 6.18%. The turbidity and temperature compensations are accurate. The designed COD sensor can accurately measure the COD concentration of the water samples to meet the technical requirements of water quality online monitoring equipment.

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DOI:10.3788/LOP56.131201

所属栏目:仪器,测量与计量

基金项目:国家自然科学基金、北京市科技创新服务能力建设项目;

收稿日期:2019-01-08

修改稿日期:2019-01-24

网络出版日期:2019-07-01

作者单位    点击查看

李文:北方工业大学机械与材料工程学院, 北京 100144
金旭:北方工业大学机械与材料工程学院, 北京 100144
张志永:北方工业大学机械与材料工程学院, 北京 100144
李新民:北方工业大学机械与材料工程学院, 北京 100144
罗学科:北方工业大学机械与材料工程学院, 北京 100144

联系人作者:金旭(18713480350@163.com)

备注:国家自然科学基金、北京市科技创新服务能力建设项目;

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引用该论文

Wen Li, Xu Jin, Zhiyong Zhang, Xinmin Li, Xueke Luo. Design of Sensor for Online Detecting Chemical Oxygen Demand Based on Dual-Light Source[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131201

李文, 金旭, 张志永, 李新民, 罗学科. 基于双光源在线监测化学需氧量的传感器设计[J]. 激光与光电子学进展, 2019, 56(13): 131201

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