基于云计算的油烟在线监测系统的设计与实现

发布时间：2018-02-12 05:02

本文关键词： 油烟检测 STM32 GPRS通信网络通信　出处：《聊城大学》2017年硕士论文　论文类型：学位论文

【摘要】：油烟在未经过净化处理时,会排放大量的固态小颗粒,增加大气中雾霾的含量,同时也会将大量的有害气体排放到大气中,危害人类身体健康。因此,本文设计了基于云计算的油烟在线监测系统来监控油烟是否被净化。整体设计方案由油烟采集及显示设备、云端存储软件、监测中心软件三部分组成。油烟采集及显示设备是通过STM32F103C8T6微处理器芯片为主的嵌入式系统,利用TGS2600油烟气体传感器和GP2Y1050AU0F油烟固体小颗粒传感模块采集油烟气体浓度与油烟固体小颗粒浓度,在OLED(Organic Light-Emitting Diode,有机电激发光二极管)显示屏上显示,同时嵌入式系统通过串口连接GPRS(General Packet Radio Service通用分组无线业务)模块,将数据传送到云端;云端存储软件位于云端服务器,利用云计算服务将收到的数据存储到云端并发送到监控中心;监控中心软件是由Visual Studio 2013编写完成,首先是云端软件建立通信,然后接收云端软件传送过来的数据,应用数据换算、数据误差处理、数据融合等算法对其进行处理,以数字与曲线图的方式显示在界面上,并根据国家饮食业油烟排放标准判断在超标时给予报警提示。本系统从油烟采集及显示设备到云端,再从云端到监测中心的功能测试后都得到了实现。由于加入了数据融合算法,得到的数据更可靠,同时油烟采集及显示设备与监测中心之间加入了云端存储数据,既简化了设备又降低了传输成本。选取了一个小餐馆进行实地测试,根据得到的数据可以得出:净化前的油烟浓度都高于国家标准规定的2.0 mg/m3,相对的净化后的油烟浓度都低于国家标准。由此得出此系统设计在油烟的实时监控方面有重要的意义。
[Abstract]:When the oil fume is not purified, it will release a large number of small solid particles, increase the content of haze in the atmosphere, and at the same time, it will also release a large number of harmful gases into the atmosphere, which will endanger human health. In this paper, an on-line monitoring system based on cloud computing is designed to monitor whether the oil fume is purified. The overall design scheme is composed of oil fume acquisition and display equipment, cloud storage software, etc. The oil fume acquisition and display equipment is an embedded system based on STM32F103C8T6 microprocessor chip. Using TGS2600 oil fume gas sensor and GP2Y1050AU0F oil fume solid particle sensor module to collect the oil fume gas concentration and the oil fume solid particle concentration, which are displayed on the OLED(Organic Light-Emitting Diode (electromechanical stimulated light emitting diode) display screen. At the same time, the embedded system connects the GPRS(General Packet Radio Service general packet radio service module through the serial port, transfers the data to the cloud, the cloud storage software is located in the cloud server, Using cloud computing services, the received data is stored in the cloud and sent to the monitoring center, which is written by Visual Studio 2013 to establish communication with the cloud software and then receive data from the cloud software. Data conversion, data error processing, data fusion and other algorithms are used to process them, and they are displayed on the interface in the form of figures and graphs. According to the national standard of cooking fume emission, the alarm warning is given when the standard is exceeded. The system is from the oil fume collection and display equipment to the cloud. Then the function test from cloud to monitoring center is realized. Because of the data fusion algorithm, the obtained data is more reliable. At the same time, the cloud storage data is added between the oil fume collection and display equipment and the monitoring center. It simplifies the device and reduces transmission costs. A small restaurant is selected for field testing. According to the obtained data, it can be concluded that the concentration of oil fume before purification is higher than that stipulated by the national standard of 2.0 mg / m ~ (3), and the relative concentration of oil fume after purification is lower than that of national standard, which indicates that the design of this system is of great significance in the real-time monitoring of oil fume.
【学位授予单位】：聊城大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP274

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