俞国燕,王涛,郭国全,刘皞春

• 1:广东海洋大学机械工程学院
• 2:广东省海洋装备及制造工程技术研究中心
• 3:广东省南海海洋牧场智能装备重点实验室

摘要(Abstract)：

【目的】为解决网箱养殖中使用船载投料系统的饲料颗粒流落点控制问题，提出一种用于实时分割饲料颗粒流轨迹并精确预测其落点的方法（MLBP）。【方法】考虑到输料管管内参数及饲料颗粒流出口参数获取难度较大，本研究采用高速相机获取饲料颗粒流轨迹图像，并利用提出的混合网络模型分割饲料颗粒流轨迹，以获取轨迹关键信息；为准确预测饲料颗粒流落点，利用BP神经网络的优势，将轨迹信息及投料口高度作为其输入，实现饲料颗粒流落点的预测。【结果】与相关研究方法对比，结合混合网络模型与BP神经网络的MLBP方法的系统单次运行时间降低95%，同时落点预测准确度达到96%，落点的平均误差范围与平均误差百分比也分别降低32.0%和30.5%。【结论】本研究提出的MLBP方法预测精度及实时性均能满足网箱投饵作业需求，可为相关研究提供参考。

关键词(KeyWords)： 网箱养殖;船载式投料系统;落点预测模型;混合网络模型;BP神经网络

Abstract:

Keywords:

基金项目(Foundation): 湛江市现代海洋渔业装备重点实验室项目（2021A05023）;; 广东省研究生教育创新计划（2023JGXM＿075）

作者(Author): 俞国燕,王涛,郭国全,刘皞春

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