文章摘要
基于模糊逻辑控制的鱼塘养殖精准投饲系统设计与试验
Design and experiment of precision feeding system of pond culturing based on fuzzy-logic control
投稿时间:2019-01-03  最后修改时间:2019-03-11
DOI:10.13872/j.1000-0275.2019.0023
中文关键词: 鱼塘养殖  精准投饲  模糊逻辑控制  水质监测  饵料系数  溶解氧饱和度  温度
英文关键词: fishpond culture  precision feeding  fuzzy logic control  water quality monitoring  feed conversion ratio  dissolved oxygen saturation  temperature
基金项目:江苏省农机三新工程项目(NJ2013-12);国家自然科学基金青年项目(31401778)
作者单位E-mail
赵思琪 南京农业大学工学院 960014782@qq.com 
丁为民 南京农业大学工学院 wmding@njau.edu.cn 
张建凯 南京农业大学工学院 2016212006@njau.edu.cn 
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中文摘要:
      为解决现有鱼塘养殖投饲模式粗放,养殖效率低的问题,基于模糊逻辑控制理论,设计一种鱼塘养殖精准投饲系统,采用Nash-Sutcliffe效率系数(NS)和均方根误差(RMSE)对传统投饲模式和精准投饲模式的决策性能进行评估,利用池塘试验,以鱼生长率、特定生长率和饵料系数为评价指标,分析了不同投饲模式对鱼生长的影响。设计的鱼塘养殖精准投饲系统主要包括水质监测系统、投喂决策控制系统和执行系统3个部分。首先通过水质监测系统获取投饲区养殖水体水质参数溶解氧饱和度(DO)和温度(T),结合投饲决策模型计算出目标所需投饲量,然后通过模块子程序控制驱动执行机构步进电机,带动齿轮齿条运动以调控供料斗开度,并采用测角法反馈饲料流量信息,调整目标投饲量,实现精准按需投饲作业。试验结果表明,精准投饲模式与传统投饲模式相比,NS值由-0.772提高至0.903,RMSE降低了19.671,鱼生长参数和产量不存在显著差异性(P>0.05),但饵料系数同比降低9.23%,存在显著性差异性(P<0.05)。研究表明,精准投饲模式系统决策控制性能良好,在不影响鱼类生长的情况下,有效提高了饵料利用率,降低饲料浪费,达到精准按需投饲的目的。
英文摘要:
      In outdoor pond culturing systems, formulated feed is the most main expenditure. Improving the feeding efficiency is of great significance for reducing economic losses and alleviating ecological pollution. However, artificial feeding control remained the most widely applied method for aquaculture feeding systems, and usually provided excess feed to obtain profitable growth rates based on observation and experience. Thus, the objective of this paper was to develop an automatic feeding decision-making system based on the fuzzy control method to solve the problem of inefficiency. The specific principles of this system are as follows. Firstly, the dissolved oxygen saturation (DO) and temperature (T) in the feeding area are obtained by the water quality monitoring system, and transfer it to controller. Then, combining with feeding strategy to calculate the theoretical feeding, and adjust opening by controlling stepper motor. And then, set the inclination sensor to feedback opening information to controller. Furthermore, the performance of the precision feeding system and artificial feeding system were evaluated by the Nsah-Sutcliffe efficiency coefficient (NS), root mean square error (RMSE), and fish growth parameters, respectively. The results indicated that the precision feeding system was superior to that of the artificial feeding system for forecasting feed decisions, the NS was promoted -0.772 to 0.903 and the RMSE was reduced by 19.671. However, there was no significant differences in promoting fish growth (P>0.05), whereas the feed conversion rate is reduced by 9.23%. Consequently, applied the precision feeding system can significantly improve economic and environment efficiency, and may can guide to develop the new equipment or control systems in some other culture systems.
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