基于卷积神经网络的红外监测系统设计  

Design of infrared monitoring system based on convolutional neural network

作　　者：焦翔 赵文策[2] 蒯亮 周淦 白永强[2] 任彦程 Jiao Xiang;Zhao Wence;Kuai Liang;Zhou Gan;Bai Yongqiang;Ren Yancheng(The Sixth Research Institute of China Electronics Corporation,Beijing 102209,China;Taiyuan Satellite Launch Center,Taiyuan 030027,China)

机构地区：[1]中国电子信息产业集团有限公司第六研究所,北京102209 [2]太原卫星发射中心,山西太原030027

出　　处：《电子技术应用》2023年第4期83-87,共5页Application of Electronic Technique

摘　　要：为了部队后勤物资有效、方便、统一管理,研究设计了一种用于监测物品在位状态的告警监测系统。该系统利用树莓派主板采集红外传感器检测物品在位状态的电平信号以及摄像头拍摄物品的图像数据,并将其转化为通用数据帧,通过指定源组播的方式发送至数据处理模块,最后使用基于卷积神经网络的图像识别算法判断物品的正确性,并在监测模块界面上实时显示其状态。经验证,该系统可以保证数据采集的实时性以及识别物品的准确性,实用性强。For the effective,convenient and unified management of materials about military logistics,this paper studies and designs a monitoring system for monitoring the presence of items.The system uses the motherboard of Raspberry Pi to collect the level signal of the infrared sensor about the presence of the items and the images taken by camera of the items.Then it converts the data into the general data frame,and sends the frame to the data processing module through the source-specific multicast.Finally,the image recognition based on the convolutional neural network is used to judge the correctness of the item,and display its status in real time through the monitoring interface.It has been verified that the system can ensure the real time of data acquisition and the accuracy of identifying items.It has strong practicability.

关 键 词：树莓派 红外检测 状态监测 图像识别 卷积神经网络 

分 类 号：TN215[电子电信—物理电子学] P315.69[天文地球—地震学]