作　　者： (刘妍华）; ; (曾志雄）;

机构地区： 华南农业大学工程学院

出　　处： 《中国农机化学报》 2021年第4期183-189,204,共8页

摘　　要： 为实现妊娠母猪智能精准饲喂,降低劳动强度,并提高饲料转化效率,设计可智能下料湿拌的智能饲喂器。通过设计下料机构、湿拌机构、触碰传感器、控制系统等核心部件,采用分段多餐饲喂方案,实现采食量、饮水量等信息监测与上传,并对饲喂器进行下料下水精度和稳定性试验。试验结果表明:下料量平均相对误差在2.50%以内,变异系数均值在0.20%以内,实际下料量曲线与专家饲喂曲线较吻合;建立水压流量监测控制数学模型,当水压为0.140 MPa时,下水量相对误差在17%以内,变异系数在4%以内;针对不同容重的颗粒饲料,提出料量修正系数ξ,下料量平均相对误差降低1.68%。该研究对妊娠母猪智能饲喂器研发提供参考。 In order to realize intelligent and precise feeding of pregnant sows,reduce labor intensity,and improve feed conversion efficiency,an intelligent feeder that can intelligently feed and wet mix was designed.This was achieved by designing core components(feeding mechanism,wet mixing mechanism,touch sensor,control system),adopting segmented multi-meal feeding scheme to realize the monitoring and uploading of feed intake and drinking water amount,and feeding the feeder launching accuracy and stability test.The test results showed that the average relative error of the feeding volume was within 2.50%,and the average value of the coefficient of variation was within 0.20%.The actual feeding volume curve was in good agreement with the expert feeding curve.A mathematical model of water pressure flow monitoring and control was established,such that when the water pressure was at 0.140 MPa,the average relative error of the water volume was within 17%,and the average value of the coefficient of variation was within 4%.For pellets of different bulk density,a feed volume correction coefficientξwas proposed,and the average relative error of the feed volume was reduced by 1.68%.This research provides reference for the development of intelligent feeders for pregnant sows.

关 键 词： 妊娠母猪 智能饲喂 分段多餐 湿拌料 料量修正

领　　域： [农业科学—畜牧学] [农业科学—畜牧兽医]