农业机械学报2025，Vol.56Issue(10)：45-53,81,10.DOI:10.6041/j.issn.1000-1298.2025.10.004
基于机器视觉与多传感器协同的鮰鱼无人称量系统研究
Unmanned Weighing System for Catfish Based on Machine Vision and Multi-sensor Collaboration
摘要
Abstract
The scale of China's aquaculture industry continues to expand,but the traditional method of weighing catfish exists in low efficiency,large error,serious fish stress damage and other problems.A catfish unmanned weighing system was proposed based on machine vision and multi-sensor synergy,fusing target detection algorithms and multi-source information measurement technology.Through the improved YOLO 11 model(HY-YOLO 11),deformable convolution(DCNv3)and spatial enhancement attention module(SEAM)were introduced to effectively solve the problem of fish sticking together,cage deformation and light fluctuation interference in dynamic scenes.The system integrated a floating monitoring platform,an industrial camera and a tensile force sensor,combined with an adaptive lifting mechanism and a buoyancy compensation mechanism,to realize the simultaneous and accurate measurement of the total mass and quantity of the fish.The experimental results showed that the average detection accuracy(mAP50)of the HY-YOLO 11 model reached 94.8％in the dense occlusion scenario,which was 3.7 percentage points higher than the baseline model,the average absolute error(MAE)of fish counting was 0.56,the relative error of mean weight calculation was less than 4％,and average time for a single weighing session was 58 s.The system provides an efficient and reliable technical solution for the intelligent management of aquaculture.关键词
鮰鱼/机器视觉/无接触称量系统/YOLO 11/可变形卷积/空间增强注意力模块Key words
catfish/machine vision/contactless weighing system/YOLO 11/DCNv3/SEAM分类
农业科技引用本文复制引用
肖茂华,吉姝颖,朱虹,李东方,汪冰清..基于机器视觉与多传感器协同的鮰鱼无人称量系统研究[J].农业机械学报,2025,56(10):45-53,81,10.基金项目
江苏省重点研发计划项目(BE2022385)和江苏省现代农机装备与技术推广项目(NJ2024-11) （BE2022385）
