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机构地区:[1]宁波大学机械工程与力学学院,浙江宁波315211 [2]浙江大学宁波理工学院机电与能源工程学院,浙江宁波315100
出 处:《工程设计学报》2015年第6期528-533,共6页Chinese Journal of Engineering Design
基 金:宁波市重大农业科技专项(2015C110015)
摘 要:随着海洋养殖业的不断发展,传统投饵方式与设备已不能满足日益增长的需求.鱼群摄食具有一定的规律,实时判别鱼群摄食状态并用于控制投饵具有重要意义.采用机器视觉技术与嵌入式系统构建了实时图像采集和处理系统,通过实时图像处理技术提取了鱼群位置、数量特征值,得到了鱼群的摄食规律;建立了投饵机下料和抛料等执行机构运动学与动力学模型;结合实时图像处理结果得到的鱼群摄食规律和投饵机的执行机构模型构建了智能投饵系统,并对投饵效果进行了实验验证.实验结果表明,所开发的基于机器视觉实时决策的智能投饵系统能按照鱼群生长需求进行投饵,可提高饵料利用率,降低残余饵料对水体的污染,节约养殖成本,提升鱼类品质.In recent years,with the development of marine aquaculture technology,the traditional way and equipment of bait casting can not meet the growing demands any more.As fishes are fed with certain regularities,it is important to acquire the feeding conditions of the fishes,and on the basis,to control the bait casting equipment in real time.Applying machine vision technology and embedded system to collect and process the images about fish feeding,the eigenvalues of the fish feeding condition,such as the position,number,and degree of hungry of the fishes,could be obtained in real time.A smart bait casting machine was developed.The kinematic,dynamic,and control models of the baiting and throwing mechanisms of the machine were established.The smart control of the bait casting process was achieved based on the results of real time image process and the model of the machine.Experimental result showed that the smart machine developed based on machine vision and real time decision technology could cast the bait according to the growing requirement of the fishes,and therefore,the bait utilization could be increased,the bait waste and water pollution reduced,the aquatic cultivation cost saved,and the fish quality improved as well.
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