安徽农学通报 >
2025 , Vol. 31 >Issue 22: 122 - 124
DOI: https://doi.org/10.16377/j.cnki.issn1007-7731.2025.22.026
基于无人船的水产品养殖水质移动监测装置和系统的研发与应用
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唐义军(1972—),男,江苏盐城人,研究员,从事农业农村信息化技术研究与推广工作。 |
Copy editor: 胡立萍
收稿日期: 2025-07-21
网络出版日期: 2025-11-28
基金资助
盐城市重点科技研发计划(农业)项目(YCBN202315)
Development and application of a USV-based mobile water quality monitoring device and system for aquaculture
Received date: 2025-07-21
Online published: 2025-11-28
为提高水产品养殖中水质动态监测的精确度和高效性,本文研发了以无人船为平台的新型水质监测装置和系统,并在实际生产中进行应用。移动式监测装置采用无人船作为移动平台,配备PLC远程控制伸缩杆和各类传感器、摄像头,实现对溶解氧、水温、pH等参数和水产品生长发育图像的实时监测和采集,并进行远程数据传输。智能化管控系统集监测、预警、控制与参数阈值模型于一体,其通过传感器网络实时采集溶解氧、水温等数据,并基于内置的参数阈值模型(以鲫鱼为例,溶氧量在3~5 mg/L,生长水温在20~25 ℃,pH在7.0~8.5,氨氮含量<0.5 mg/L,亚硝酸盐含量<0.1 mg/L)进行智能诊断与风险预警,最终驱动增氧机等调控设备执行自动控制,实现了对养殖水环境的智能化管理。2023—2024年该装置与系统的累计示范应用面积为155 hm2,实践表明,与未应用该技术的基地相比,使用该技术的示范基地,鲫鱼产量增加2 280 kg/hm2,产值增加34 500元/hm2,提升了水质监测与调控的数据覆盖度和稳定性,促进了水产品养殖产量、品质和效益的同步提升。本文为水产品养殖中的水质监测提供参考。
唐义军 , 杨文伟 , 仓晶晶 , 朱芙蓉 , 朱浩 , 施建军 , 袁瑞芳 . 基于无人船的水产品养殖水质移动监测装置和系统的研发与应用[J]. 安徽农学通报, 2025 , 31(22) : 122 -124 . DOI: 10.16377/j.cnki.issn1007-7731.2025.22.026
To enhance the precision and efficiency of dynamic water quality monitoring in aquaculture, this paper presents the development and practical application of a novel monitoring device and system utilizing an unmanned surface vehicle (USV) as its platform. The mobile monitoring device employs the USV equipped with a PLC-remotely controlled telescopic pole, various sensors, and cameras. This setup enables real-time monitoring and collection of key parameters, including dissolved oxygen, water temperature, pH, along with images tracking aquatic product growth.The integrated intelligent management system combines monitoring, early warning, control, and a parameter threshold model. It collects water quality data in real-time via the sensor network. Based on its built-in threshold model (for the cultivation of Carassius auratus, dissolved oxygen 3-5 mg/L, optimal temperature 20-25 ℃, pH 7.0-8.5, ammonia nitrogen <0.5 mg/L, nitrite <0.1 mg/L), the system performs intelligent diagnostics and issues risk warnings. It subsequently drives control equipment, such as aerators, to execute automated adjustments, thereby achieving intelligent management of the aquaculture water environment. From 2023 to 2024, the cumulative demonstration area for this device and system reached 155 hm2. Practical results demonstrated that, compared to bases not using this technology, the demonstration sites achieved a yield increase of 2 280 kg/hm2 and an output value increase of 34 500 yuan/hm2 for crucian carp. The system significantly improved the data coverage and stability of water quality monitoring and regulation, ultimately promoting the simultaneous enhancement of aquaculture production, product quality, and economic benefits. This study provides a valuable reference for water quality monitoring in aquaculture.
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