鱼类水质监测法是目前水质生物监测法的一个重要方向。针对鱼类活动生物电信号强度弱、易受噪声干扰、以及鱼类水质监测传感器缺乏有效判定依据等难题,通过对观测电极采集到的鱼类活动电信号进行滤波增幅处理,再通过MSP430进行采集、转换,并在基于Labview程序设计的上位机中分别计算鱼类各种活动电位信号(呼吸运动和游泳运动)的功率谱密度,实现鱼类活动电信号的频域分析。然后,结合各类运动功率占比变化超过阈值与否这一全新判据,完成预警判断。最后,通过实验证明所开发系统的有效性。
Abstract
The fish analysis is the main direction of biological monitoring of water quality at present.Aiming at the problems such as weak strength of the fish bioelectric signal, easy to be interfered by noise, and lack of effective determination basis of fish water quality monitoring sensor.Filtered and increased the fish bioelectric signal collected by the observation electrode.Then through MCU MSP430 to collect and convert the signal, while in the upper computer based on Labview program, the power spectral density of various active potential signals (breathing and swimming movement) of the fish were calculated respectively to realize the frequency domain analysis of the bioelectrical signals of the fish.Then, combining with the new criterion of whether the variation of various movement power proportions exceeds the threshold value, the early warning judgment was completed.Finally,the effectiveness of the system had been proved by experiments.
关键词
计量学 /
水质监测 /
生物电信号 /
鱼类活动 /
增幅滤波电路 /
功率谱密度
Key words
metrology /
water quality monitoring /
bioelectrical signal /
fish activity /
amplifying and filter circuit /
power spectrum density
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
［1］姚跃, 虞丽娟, 曹守启, 等.基于北斗通信的河道水质监测系统设计 ［J］. 计量学报, 2020, 41 (10): 1291-1296.
Yao Y, Yu L J, Cao S Q.et al.Design of river water quality monitoring system based on Beidou commnication ［J］. Acta Metrologica Sinica, 2020, 41 (10): 1291-1296.
［2］程淑红, 张仕军, 赵考鹏.基于卷积神经网络的生物式水质监测方法 ［J］. 计量学报, 2019, 40 (4): 721-727.
Cheng S H, Zhang S J, Zhao K P.Biological water quality monitoring method based on convolution neural network ［J］. Acta Metrologica Sinica, 2019, 40 (4): 721-727.
［3］Ding J, Tang Y, Zhang L, et al.A Novel Front End Design for Bioelectrical Signal Wearable Acquisition ［J］. IEEE Sensors, 2019, 19 (18): 8009-8018.
［4］程淑红, 张仕军, 李雷华, 等.基于鱼群运动特征和XGBoost的异常水质监测 ［J］. 计量学报, 2018, 39 (4): 572-577.
Cheng S H, Zhang S J, Li L H, et al.Water quality monitoring based on fish movement characteristics and XGBoost ［J］. Acta Metrologica Sinica, 2018, 39 (4): 572-577.
［5］周冏, 罗海江, 孙聪, 等.中国农村饮用水水源地
水质状况研究 ［J］. 中国环境监测, 2020, 36 (6): 89-94.
Zhou J, Luo H J, Sun C, et al.Study on water quality of rural drinking water sources in China ［J］. Environ.Monitoring in China, 2020, 36 (6): 89-94.
［6］周明娟,逯迈.基于高阶滤波的肌电信号采集电路设计 ［J］. 传感技术学报, 2018, 31 (1): 58-64.
Zhou M J, Lu M.Design of EMG signal acquisition circuit based on high-order filter ［J］. Chinese Journal of sensors and actuators, 2018, 31 (1): 58-64.
［7］Ai Z, Zheng L, Qi H, et al.Low-Power Wireless Wearable ECG Monitoring System Based on BMD101［C］// 第37届中国控制会议(CCC). 武汉, 中国. 2018: 7374-7379.
［8］Fortune B C, Pretty C G, Cameron C J, et al. Electrode-skin impedance imbalance measured in the frequency domain ［J］. Biomedical Signal Processing and Control, 2021, 63: 102202.
［9］Avci R, Miller K J W, Niranchan P, et al.Bioelectrical Signals for the Diagnosis and Therapy of Functional Gastrointestinal Disorders ［J］. Applied Sciences, 2020, 10(22): 8102.
［10］徐敏, 陆瑞珏, 杨凌升.基于鱼类活动电位功率频谱密度的水质监测方法 ［J］. 安徽大学学报 (自然科学版), 2019, 43 (2): 89-95.
Xu M, Lu R Y, Yang L S. Water quality monitoring based on power spectral density of fish activity electrical potential ［J］. Journal of Anhui University (Natural Science Edition) , 2019, 43 (2): 89-95.
［11］Fu Y , Zhao J, Dong Y , et al.Dry Electrodes for Human Bioelectrical Signal Monitoring ［J］. Sensors, 2020, 20 (13): 3651-3681.
［12］Gerhardt A.A new multispecies freshwater biomonitor for ecologically relevant surveillance of surface waters ［M］. New York: Kluwer-Plenum Press, 2001: 301-317.
基金
国家自然科学基金(41401572);江苏省高校优势学科项目(PAPD);昆山&南京信息工程大学智能传感研究中心项目(20200143)
PDF(838 KB)
