摘要
针对化肥厂有害气体泄漏风险,本研究设计了一种基于云平台的检测系统。系统采用STM32与STC51单片机为主从架构,集成MQ系列传感器,实时采集甲烷、一氧化碳等多种气体浓度。通过LoRa模块实现下位机与主控制器的低功耗长距离通信,利用ESP8266-WiFi模块将数据上传至阿里云平台。结合Django后端与Vue前端构建多终端监控平台,支持实时数据显示、历史查询及远程阈值设置。系统创新性引入本地与云端双重阈值机制:超标时本地触发声光警报并联动通风、洒水等应急措施,云端同步短信通知管理人员,实现“现场应急+远程管控”双重防护。数据存储采用本地SD卡与云端数据库结合,保障数据可靠性。本研究为工业物联网在化工安全领域的应用提供了可扩展方案。
In response to the risk of harmful gas leakage in fertilizer plants,this study designs a cloud-platform-based detection system.The system adopts a master-slave architecture with an STM32 and an STC51 single-chip microcomputer.It integrates MQ series sensors to collect the concentrations of various gases such as methane and carbon monoxide in real-time.The LoRa module is used to achieve low-power and long-distance communication between the lower computer and the upper computer,and the ESP8266-WiFi module uploads the data to the Alibaba Cloud platform.A multi-terminal monitoring platform is constructed by combining the Django back-end and the Vue front-end,which supports real-time data display,historical data query,and remote threshold setting.The system innovatively introduces a dual-threshold mechanism for both the local and cloud ends.When the gas concentration exceeds the preset threshold,the local end triggers audible and visual alarms and activates emergency measures such as ventilation and water sprinkling.Meanwhile,the cloud end sends text messages to notify managers,realizing a dual-protection mode of"on-site emergency response+remote control".The data storage combines a local SD card and a cloud database to ensure data reliability.This research provides an extensible solution for the application of the Industrial Internet of Things in the field of chemical safety.
作者
刘源
雷冰冰
Liu Yuan;Lei Bingbing(College of Innovation and Entrepreneurship,North Minzu University,Yinchuan,China)
出处
《科学技术创新》
2025年第18期56-59,共4页
Scientific and Technological Innovation
基金
北方民族大学创新创业训练计划资助(202411407021)。
关键词
有害气体检测
物联网
远程自动化控制
系统
harmful gas detection
Internet of Things
remote automation control
system
