| 融合电子鼻和视觉技术的鸡肉新鲜度检测装置研究 |
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| 引用本文： | 李玉花,史翰卿,熊赟葳,余思懿,王晨阳,邹修国.融合电子鼻和视觉技术的鸡肉新鲜度检测装置研究[J].农业机械学报,2022,53(11):433-440. |
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| 作者姓名： | 李玉花 史翰卿 熊赟葳 余思懿 王晨阳 邹修国 |
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| 作者单位： | 南京农业大学 |
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| 基金项目： | 江苏省国际科技合作项目（BZ2021022）、江苏省现代农机装备与技术示范推广项目（NJ202001）和江苏省农业科技自主创新资金项目（CX(21)3058） |
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| 摘 要： | 为实现鸡肉新鲜度的快速准确检测，设计了一种基于电子鼻和视觉数据融合的一体化检测装置。装置由控制系统、视觉系统和电子鼻系统3部分组成，可同时通过电子鼻传感器阵列检测鸡肉散发的气体浓度并由摄像机采集鸡肉视觉图像，控制板传输数据至Jetson Nano上位机进行特征提取、融合与分析。由该装置获取不同新鲜度鸡肉样本的气味和图像数据，采用主成分分析方法进行降维处理，再基于支持向量机建立鸡肉新鲜度分级模型，准确率可达98.7%。该装置具有准确率高、便携和稳定性强等特点，可为肉品新鲜度检测提供技术支持。
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| 关 键 词： | 鸡肉新鲜度 检测装置 电子鼻 机器视觉 数据融合 |
| 收稿时间： | 2022/7/3 0:00:00 |
Research of Chicken Freshness Detection Device Based on Electronic Nose and Vision Technology |
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| LI Yuhu,SHI Hanqing,XIONG Yunwei,YU Siyi,WANG Chenyang,ZOU Xiuguo.Research of Chicken Freshness Detection Device Based on Electronic Nose and Vision Technology[J].Transactions of the Chinese Society of Agricultural Machinery,2022,53(11):433-440. |
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| Authors: | LI Yuhu SHI Hanqing XIONG Yunwei YU Siyi WANG Chenyang ZOU Xiuguo |
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| Institution: | Nanjing Agricultural University |
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| Abstract: | In order to realize the fast and accurate detection of chicken freshness, an integrated detection device based on electronic nose and vision technology was designed. The structure of the device was divided into three parts, including the control system, the vision system, and the electronic nose system. It simultaneously detected the concentration of gas emitted from chicken samples through the sensor array of the electronic nose, and obtained the visual images of chicken samples by the camera. The gas concentration data were firstly transmitted from the control board to the Jetson Nano board, and then was fused with the visual images for feature extraction and further analysis. Computational fluid dynamics techniques were used to simulate the velocity cloud and velocity vector diagrams of the device under suction conditions to verify the feasibility of gas flow. Based on the gas concentration and image data of chicken samples of different freshness obtained by the device, principal component analysis method was adopted for dimensionality reduction, and chicken freshness grading model was established using support vector machine method with an accuracy rate of 98.7%. The device has the characteristics of high accuracy, portability and stability, which can provide technical support for meat freshness detection. |
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| Keywords: | chicken freshness detection device electronic nose machine vision data fusion |
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