基于机器鱼的内陆湖泊水质在线监测系统设计
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(1.合肥职业技术学院 信息中心,合肥 238000;2.安徽斯玛特物联网科技有限公司,合肥 231000)

作者简介:

童晓红(1965-),男,安徽合肥人,工学硕士,副教授,研究方向为物联网技术与应用[FQ)]

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安徽省自然科学研究重点基金项目(KJ2014A219)


Design on Monitoring System for Inland Lake Water Quality Based on Robotic Fish
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(1.Information Center,Hefei Vocational and Technical College,Hefei 238000,China;2.Anhui Smart Internet of things Technology Co., Ltd.,Hefei 231000,China)

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    摘要:

    仅依赖无线传感器网络在线实测是利用多跳式通信实现远程发送与存储数据丢包率高,实验阶段设计的二维结构仿真机器鱼巡游避障性能差,GPRS全天候数据采集与传送所需的流量费用高,针对以上这些问题,设计了一套可进行实测的机器鱼自动巡游避障、水质环境实时监测系统平台;该系统通过移动终端程序设计、利用三维采集路径跟踪算法及WSNs与Wifi热点技术对机器鱼群实现远程精准控制,按照设定深度、路径规划的采集点进行水温水位、PH值、溶解氧、电导率、浊度等常五类水质环境数据实时采集、处理、远程存储、显示、分析及预警,给出了系统的总体设计、机器鱼的结构与控制系统设计、终端节点与协调器的硬件系统及上下位机软件系统设计;利用这套系统对巢湖5个取样点实测,水温、溶解氧、PH值平均误差率分别为0.18%、0.5%及0.01%,远高于其他水质在线监测的精度要求,达到了预期成果;同时对水库及精细水产养殖业等水质在线监测与预警具有很高的推广价值。

    Abstract:

    online measurement of transmission and storage data packet loss rate is high due to the remote multi hop communication rely only onWireless sensor networks. The obstacle avoidance ability of the simulation robot fish in the two-dimensional structural design stage is poor. data acquisition and transmission costs of GPRS traffic is high all weather.in order to solve the above problems, a set of rea-time monitoring system of water quality for automatic obstacle avoidance is designed. the system is designed by using the mobile terminal program, using 3D acquisition path tracking algorithm and WSNs and Wifi hot spot technology to realize the precise control of the robot fish, according the set depth and planning of acquisition point, achieve five water quality environmental datas including of water level and temperature, pH, dissolved oxygen, conductivity, turbidity, etc in real-time acquisition, processing, remote storage, display, analysis and warning. the overall design of the system, the structure and control system design, the hardware system of the terminal node and coordinator, the software design of the upper and lower computer are given.the application of the system to the five sampling points in the Chaohu Lake,the average error rate of water temperature, dissolved oxygen and pH value were 0.18%, 0.5% and 0.01%, respectively,much higher than other water quality on-line monitoring accuracy requirements,to achieve the expected results. It has a very high value for the on-line monitoring and early warning ofreservoir and fine aquaculture.

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引用本文

童晓红,陈玲,华艳,杨磊.基于机器鱼的内陆湖泊水质在线监测系统设计计算机测量与控制[J].,2017,25(5):56-61.

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  • 收稿日期:2017-02-04
  • 最后修改日期:2017-03-13
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  • 在线发布日期: 2017-05-31
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