| 注册
首页|期刊导航|渔业现代化|面向池塘养殖的鱼类摄食行为监测算法

面向池塘养殖的鱼类摄食行为监测算法

杨慧威 杨航 张玉涛 王志俊 李国栋 张平

渔业现代化2026,Vol.53Issue(3):121-132,12.
渔业现代化2026,Vol.53Issue(3):121-132,12.DOI:10.26958/j.cnki.1007-9580.2026.03.012

面向池塘养殖的鱼类摄食行为监测算法

An algorithm for monitoring the feeding behavior of fish in pond aquaculture

杨慧威 1杨航 2张玉涛 2王志俊 2李国栋 2张平3

作者信息

  • 1. 大连海洋大学航海与船舶工程学院,辽宁大连 116023||中国水产科学研究院渔业机械仪器研究所,上海 200092
  • 2. 中国水产科学研究院渔业机械仪器研究所,上海 200092
  • 3. 中国科学院声学研究所东海研究站,上海 201815
  • 折叠

摘要

Abstract

China is a major aquaculture country,accounting for more than 70%of the global aquaculture output,with pond aquaculture being one of its primary forms.It provides a stable source of high-quality protein for the national population.However,the low efficiency of traditional aquaculture models and the lack of low-cost intelligent monitoring equipment have restricted the application and popularization of precision feeding technology.To address the above problems,based on the correlation laws between the feeding desire of fish schools in pond aquaculture and their spatial distribution,activity state and other characteristics,this study used sonar to monitor fish school echoes,and analyzed the characteristics of vertical position changes,aggregation density and activity level of fish schools in water through echo signal processing,so as to identify the feeding behavior states of fish schools as strong feeding,weak feeding or non-feeding.The fish school distribution characteristics were simulated by an acoustic echo model,and the dynamic feeding behavior was simulated with an improved Boids algorithm.K-means clustering was applied to divide the water body into different regions.The spatial position,aggregation degree and activity level of fish schools were comprehensively analyzed,and the feasibility and effectiveness of the proposed method were verified in a simulation environment.Finally,the effectiveness of the proposed detection algorithm was validated through actual tests.The results show that the recognition accuracy of the proposed method for fish school aggregation and activity states reaches 88.1%and 68.3%respectively,and the accuracy is improved by more than 16.8%after fusing spatial information.This research provides a reliable basis for the realization of adaptive feeding in pond aquaculture.

关键词

鱼群摄食欲望/池塘养殖/精准投饲/鱼群聚集度/鱼群活跃度

Key words

fish feeding desire/pond farming/precise feeding/fish school density/fish activity

分类

农业科技

引用本文复制引用

杨慧威,杨航,张玉涛,王志俊,李国栋,张平..面向池塘养殖的鱼类摄食行为监测算法[J].渔业现代化,2026,53(3):121-132,12.

基金项目

农业农村部科技项目 ()

中国水产科学研究院中央级公益性科研院所基本科研业务费专项(2023ID90) (2023ID90)

渔业现代化

1007-9580

访问量0
|
下载量0
段落导航相关论文