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基于云平台的拌合站沥青罐液位监测系统设计 被引量:1

Design of cloud platform based liquid level monitoring system for asphalt tank in mixing station
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摘要 目前,拌合站沥青罐液位测量基本上采用人工估计和浮标测量,为解决测量误差较大、无法自动采集数据的问题,文中设计一个基于云平台的拌合站沥青罐液位监测系统。系统由传感器、监测主机、RabbitMQ(消息代理软件)和沥青罐监测云平台四部分组成。采用压力变送器和温度变送器获取沥青液位和温度信息,通过A/D转换器传入STM32单片机,利用NB-IoT(窄带物联网)网络将信息上传到RabbitMQ消息队列,对信息解析之后存入数据库。最后将数据库中的数据经过统计、计算之后展示在沥青罐监测云平台。标定实验结果显示,沥青液位测量精度高于5 cm,满足沥青罐液位测量精度的要求,计算得到的沥青质量可为拌合站的沥青库存管理和进货提供相关数据。 As the liquid level measurement of asphalt tank in mixing station widely adopts the manual estimation and buoy measurement,which has big measuring error and can not collect data automatically,a cloud platform based liquid level monitoring system for asphalt tank is designed.The system is composed of sensors,monitoring host,RabbitMQ(software of message broker)and asphalt tank monitoring cloud platform.The pressure transmitter and the temperature transmitter are used to collect the asphalt liquid level and temperature information,which is conveyed into STM32 through the AD convertor,uploaded to the RabbitMQ message queue by means of the NB-IoT(narrow band Internet of Things),and then parsed and stored in the database.After statistics and calculation,the data in the database are displayed on the monitoring cloud platform of asphalt tank.The calibration experiment results show that the accuracy of liquid level measurement of asphalt tank is better than 5 cm,which can meet the requirements of liquid level measurement accuracy of asphalt tank.Therefore,the asphalt quality obtained by calculation can provide relevant data for asphalt inventory management and purchase in the mixing station.
作者 杜永杰 陆艺 赵静 DU Yongjie;LU Yi;ZHAO Jing(College of Metrology&Measurement Engineering,China Jiliang University,Hangzhou 310018,China;Hangzhou Wolei Intelligent Technology Co.,Ltd.,Hangzhou 310018,China)
出处 《现代电子技术》 2022年第2期11-15,共5页 Modern Electronics Technique
基金 国家智能制造新模式示范项目(Z135060009002) 国家自然科学基金资助项目(51405463)。
关键词 液位监测 沥青罐 云平台 系统设计 数据采集 信息上传 远程监测 标定实验 liquid level monitoring asphalt tank cloud platform system design data collection information uploading remote monitoring calibration experiment
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