A Fluorescence Based Dissolved Oxygen Sensor

doi:10.12133/j.smartag.2020.2.2.202005-SA004

Abstract

Abstract:

The measurement of dissolved oxygen content in water is of great significance to aquaculture. However, the dissolved oxygen sensors on the market in China are expensive, and are difficult to maintain continuous online measurement and update parts, so they cannot be widely applied in real production and play expected role in the aquaculture Internet of things(IoT). Based on the principle of fluorescence quenching, a low cost and easy maintenance of dissolved oxygen sensor was developed in this work based on the relationship between the concentration of dissolved oxygen in water and the phase difference of fluorescence signal. The self-made oxygen-sensitive membrane was used to generate red fluorescence which being excited by blue light, and the fluorescence life was regulated by the concentration of dissolved oxygen. Photoelectric conversion circuit with optical signal sensing device was designed to sense optical signal. The STM32F103 microprocessor was used as the main control chip, and the lower computer program was programmed to generate the excitation light pulse. The phase-sensitive detection principle and fast Fourier transform (FFT) were used to calculate the phase difference between the excitation light and the reference light, which was converted into the concentration of dissolved oxygen and realized the measurement of dissolved oxygen. The fluorescence detection part and the main control part of the system were designed as detachable independent modules, and shield lines were used to plug and pull directly, so as to facilitate replacement and maintenance and realize online remote measurement. The testing results showed that, the measurement range of the sensor was 0-20 mg/L, system time delay was less than 2 s, and the life time of the oxygen sensitive membrane would be about 1 year. The dissolved oxygen sensor has the characteristics of convenient measurement, stable result output, low cost and small volume, which will lay a good foundation for the development and marketization of low-cost dissolved oxygen sensors in aquaculture industry of China.

Key words: dissolved oxygen sensor, fluorescence quenching, aquaculture, STM32 microprocessor, oxygen sensitive membrane

CLC Number:

TP212.6

GU Hao, WANG Zhiqiang, WU Hao, JIANG Yongnian, GUO Ya. A Fluorescence Based Dissolved Oxygen Sensor[J]. Smart Agriculture, 2020, 2(2): 48-58.

References

1	李新成, 林德峰, 王胜涛, 等.基于物联网的水产养殖池塘智能管控系统设计[J].水产学杂志, 2020, 33(1): 81-86.
1	LI X,LIN D,WANG S,et al.A control system of an aquaculture pond based on Internet of Things[J].Chinese Journal of Fisheries, 2020, 33(1): 81-86.
2	房景辉, 邹健, 刘毅, 等. 基于物联网技术的水质监测系统中不同溶解氧传感器应用效果初探[J]. 山东农业科学, 2016, 48(4): 134-138.
2	FANG J, ZOU J, LIU Y, et al. Preliminary study on application effect of different dissolved oxygen sensors in online water environment monitoring system based on the Internet of Things[J]. Shandong Agricultural Sciences, 2016, 48(4): 134-138.
3	高亚. 基于荧光猝灭法的溶解氧传感器研制[D].杭州: 浙江大学, 2018.
3	GAO Y. Development of dissolved oxygen sensor based on fluorescence quenching principle[D]. Hangzhou: Zhejiang University, 2018.
4	吴丙伟, 张颖颖, 张云燕, 等. 基于氧敏感膜的海水溶解氧测定技术研究[J]. 山东科学, 2019, 32(5): 31-37.
4	WU B, ZHANG Y, ZHANG Y, et al. A dissolved oxygen detection technique based on an oxygen sensitive membrane in seawater[J]. Shandong Science, 2019, 32(5): 31-37.
5	杨亦睿. 基于荧光猝灭原理的溶解氧浓度传感器的研究设计[D]. 青岛：青岛理工大学, 2017.
5	YANG Y. The study and design of dissolved oxygen potency sensor based on fluorescence quenching principle[D]. Qingdao：Qingdao University of Technology, 2017.
6	陈朋, 赵智, 赵冬冬, 等. 基于单光源频域荧光寿命的水体溶解氧浓度检测方法[J]. 光子学报, 2020, 49(3): 134-143.
6	CHEN P, ZHAO Z, ZHAO D, et al. Detection method of dissolved oxygen concentration in water based on single source frequency domain fluorescence lifetime[J]. Acta Photonica Sinica, 2020, 49(3): 134-143.
7	SUN L, DAI W, BAO J, et al. Design and research on the optical sensor of dissolved oxygen in water based on fluorescence quenching[C]// International Symposium on Advanced Optical Manufacturing & Testing Technologies: Optical Test & Measurement Technology & Equipment. International Society for Optics and Photonics. Burlingame, California, USA: SPIE, 2007.
8	LIAO H, QIU Z, FENG G, et al. The research of dissolved oxygen detection system based on fluorescence quenching principle[C]// International Conference on Electronic & Mechanical Engineering & Information Technology. Piscataway, New York, USA: IEEE, 2011.
9	周冬秋. 光纤溶解氧传感器特性研究[D]. 南京: 南京信息工程大学, 2012.
9	ZHOU D. The property study of fiber optic dissolved oxygen sensor[D]. Nanjing: Nanjing University of Information Science & Technology, 2012.
10	沈方华. 基于STM32微处理器的可编程序控制器设计[J]. 教育现代化, 2017, 4(34): 159-160, 168.
10	SHEN F. Design of programmable logic controller based on STM32[J]. Course Education Research, 2017, 4(34): 159-160, 168.
11	王清珍, 邵杰. 基于单片机的可编程序控制器设计[J]. 现代电子技术, 2016, 39(6): 161-165, 170.
11	WANG Q, SHAO J. Design of programmable controller based on microcomputer[J]. Modern Electronics Technique, 2016, 39(6): 161-165, 170.
12	陈连清, 谢林波, 钟柔潮, 等. 新型1,2,4-三唑重金属离子荧光淬灭剂的合成、表征与性能[J]. 中南民族大学学报(自然科学版), 2015, 34(3): 15-21.
12	CHEN L, XIE L, ZHONG R, et al. Synthesis, characterization and properties of novel 1, 2, 4-triazole heavy metal ion fluorescence quencher[J]. Journal of South-Central University for Nationalities (Natural Science Edition), 2015, 34(3): 15-21.
13	陈连清, 李群丽, 施超, 等. 4-氨基-3,5-二(2-羟基苯基)-1,2,4-三唑的合成、表征及其光物理性能[J]. 中南民族大学学报(自然科学版), 2009, 28(3): 19-24.
13	CHEN L, LI Q, SHI C, et al. Synthesis, characterization and photophysical properties of 4-Amino-3, 5-bis(o-Hydroxyphenyl)-1, 2, 4-Triazole[J]. Journal of South-central University for Nationalities(Natural Science Edition), 2009, 28(3): 19-24.
14	袁晨, 亓夫军, 郭金家, 等. 基于STM32微控制器的光谱仪控制系统设计[J]. 中国海洋大学学报(自然科学版), 2019, 49(S2): 170-175.
14	YUAN C, QI F, GUO J, et al. Simulation on miniature control system of FSV-305spectrometer based on STM32[J]. Periodical of Ocean University of China, 2019, 49(S2): 170-175.
15	邵兴, 詹金晶. 基于STM32控制器的检测系统设计[J].水雷战与舰船防护, 2018, 26(1): 18-22.
15	SHAO X,ZHAN J.Design of detection system based on STM32 controller[J].Mine Warfare&Ship Self-Defence, 2018, 26(1): 18-22.
16	刘敏层, 张峰. 基于STM32的智能照明监控系统的设计与实现[J]. 自动化仪表, 2018, 39(7): 43-46, 50.
16	LIU M, ZHANG F. Design and realization of intelligent lighting monitoring system based on STM32[J].Process Automation Instrumentation, 2018, 39(7): 43-46, 50.
17	许晶鑫. 开关电源对电子设备的电磁干扰分析[J]. 通信电源技术, 2019, 36(12): 146-147.
17	XU J. Analysis of electromagnetic interference of switching power supply to electronic equipment[J].Telecom Power Technology, 2019, 36(12): 146-147.
18	郭玉秀, 黄跃祖.基于单片机的开关电源设计[J]. 通信电源技术, 2018, 35(8): 134-138.
18	GUO Y, HUANG Y. Design of switching power supply based on single chip microcomputer[J].Telecom Power Technologies, 2018, 35(8): 134-138.
19	张文强, 冯搏, 俞竹青. LED负载恒流驱动电源电路的研究[J]. 化工自动化及仪表, 2016, 43(1): 84-88.
19	ZHANG W, FENG B, YU Z. Study on constant current-driven LED power circuit[J]. Control and Instruments in Chemical Industry, 2016, 43(1): 84-88.
20	唐夕晴, 李建闽, 佘晓烁. RS485 总线接口性能测试仪设计与开发[J]. 电测与仪表, 2019, 56(7): 142-147.
20	TANG X, LI J, SHE X. Design and development of RS485 bus interface performance tester[J]. Electrical Measurement & Instrumentation, 2019, 56(7): 142-147.
21	张哲丰, 贺明智, 刘雪山, 等. 负载源极连接谐振式Buck-Boost LED驱动电源[J/OL]. 电源学报: 1-9. [2020-06-27]. .
21	ZHANG Z, HE M, LIU X, et al. Resonant Buck-Boost LED driver based on output common-source connection[J/OL]. Journal of Power Supply: 1-9. [2020-06-27]. .
22	关丛荣, 赵伟程, 祝天岳, 等. 基于STM32大功率LED调光控制器设计[J]. 照明工程学报, 2019, 30(6): 94-99, 104.
22	GUAN C, ZHAO W, ZHU T, et al. High-power LED dimming controller based on STM[J]. China Illuminating Engineering Journal, 2019, 30(6): 94-99, 104.
23	PIETROWSKI W, LUDOWICZ W, WOJCIECHOWSKI R M. The wide range of output frequency regulation method for the inverter using the combination of PWM and DDS[J]. COMPEL - The International Journal for Computation and Mathematics in Electrical and Eelectronic Engineering, 2019, 38(4): 1323-1333.
24	杨子腾, 刘琨, 杨昆. 基于PWM调光的LED驱动器设计[J]. 现代信息科技, 2020, 4(2): 32-36.
24	YANG Z, LIU K,YANG K. LED driver design based on PWM dimming[J]. Modern Information Technology, 2020, 4(2): 32-36.
25	吴永忠, 梅新星. 基于STM32的微弱光电信号检测系统的设计与实现[J].传感器与微系统, 2020, 39(6): 107-109, 112.
25	WU Y, MEI X.Design and implementation of weak photoelectric signal detection system based on STM32[J].Transducer and Microsystem Technologies, 2020, 39(6): 107-109, 112.
26	张仲明, 郭东伟, 吕巍, 等.基于DS18B20温度传感器的温度测量系统设计[J]. 实验技术与管理, 2018, 35(5): 76-79, 88.
26	ZHANG Z, GUO D, LYU W, et al. Design of temperature measurement system based on DS18B20 temperature sensor[J]. Experiment Technology and Management, 2018, 35(5): 76-79, 88.
27	李建兰, 邵建龙. 数字温度传感器DS18B20的关键时序研究[J]. 电子测试, 2018(1): 114-116.
27	LI J, SHAO J. Study on critical timing sequence of digital sensor DS1820[J]. Electronic Test, 2018(1): 114-116.
28	高锋, 叶成彬, 陈贤钰. 基于STM32的OLED音乐频谱显示器的设计[J]. 电子设计工程, 2020, 28(11): 156-160.
28	GAO F, YE C, CHEN X. Design of OLED music spectrum display based on STM32[J]. Electronic Design Engineering, 2020, 28(11): 156-160.
29	吴正明. 基于FFT算法的两相式测量在单片机中的实现[J]. 水利电力机械, 2007(12): 166-169.
29	WU Z. Two phases measurement in monolithic microprocessor based on FFT algorithmic[J]. Water Conservancy & Electric Power Machinery, 2007(12): 166-169.
30	石军, 曹卫锋, 徐方友, 等. 数字相敏检波在DSP中的实现[J]. 郑州轻工业学院学报(自然科学版), 2010, 25(2): 85-87.
30	SHI J, CAO W, XU F, et al. The realization of digital phase sensitivity detection technique in DSP[J]. Journal of Zhengzhou University of Light Industry (Natural Science Edition), 2010, 25(2): 85-87.
31	张学龙, 陈德智. 相敏检波技术测量微弱信号的原理与方法[J]. 测试技术学报, 1997(2): 25-28.
31	ZHANG X, CHEN D. To measure small signal by the technique of the coherent detection[J]. Journal of Test Measurement Technique, 1997(2): 25-28.
32	傅家乐. 荧光淬灭法溶解氧测定仪校准方法的研究[J]. 化学分析计量, 2014, 23(1): 83-85.
32	FU J. Discussion on calibration method of fluorescence quenching method dissolved oxygen meter[J]. Chemical Analysis and Meterage, 2014, 23(1): 83-85.

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[2]	Zhou Chao, Xu Daming, Lin Kai, Chen Lan, Zhang Song, Sun Chuanheng, Yang Xinting. Evaluation of fish feeding intensity in aquaculture based on near-infrared machine vision [J]. Smart Agriculture, 2019, 1(1): 76-84.