城市地下综合管廊监测与预警系统研究及应用

发布时间：2018-03-14 16:07

本文选题：综合管廊　切入点：共同沟　出处：《西安建筑科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：在经济发展飞速的今天,城市建设的脚步也在不断加快,城市地下空间的开发也是必不可少的。在综合管廊建设的同时,安全管理系统也在不断完善。由于综合管廊内部容纳管道较多,环境密闭复杂,为了避免发生管道爆炸、火灾等不安全事故。本文对综合管廊内部环境进行分析,对容易造成危害的主要参数进行监测,提出一种基于STM32嵌入式处理器的监测与预警系统。本文以综合管廊为研究对象,在分析国内外研究现状的基础上,完成的主要工作如下:(1)设计了基于STM32的综合管廊监测与预警系统。系统采用三层分布式结构。以STM32F103RCT6开发板为核心,搭建硬件平台。主要包括最小系统、采集电路、CAN总线通信、以太网通信、TFT-LCD显示以及SDIO存储模块等部分,完成了系统常用模块和外设的搭建。基于硬件平台进行下位机软件的开发。移植μC/OS-II操作系统,完成软件应用程序的开发,进行数据处理,实时存储和显示。(2)采用MCGS组态软件进行上位机开发,完成数据远程实时监测和预警。(3)针对综合管廊内部的可燃气体浓度预测,采用了基于回归的预测方法和基于卡尔曼滤波预测方法。通过对两种方法的研究和模拟实验,对比分析验证了基于卡尔曼滤波算法的预测浓度误差较小。(4)完成了系统软、硬件整体设计与调试,实现了对综合管廊内部环境的监测与预警,达到了预期目的。
[Abstract]:In the rapid economic development today, city construction pace is accelerating, the development of city underground space is necessary. In the pipe gallery building at the same time, the safety management system is constantly being improved. Due to the internal pipe gallery to accommodate more complex pipeline, closed environment, in order to avoid the occurrence of pipeline explosion, fire etc. safety accidents. The paper carries on the analysis to the internal environment of the pipe gallery, easy to cause the main parameters of hazards monitoring, a monitoring and early warning system based on STM32 embedded processor. Based on the comprehensive pipe gallery as the research object, based on the analysis on the present research, the main work is as follows: (1) design of comprehensive pipe gallery monitoring and early warning system based on STM32. The system uses three layer distributed structure. Based on the STM32F103RCT6 development board as the core of hardware platform, mainly including the minimum system, The acquisition circuit, CAN bus communication, Ethernet communication, TFT-LCD display and SDIO memory modules, complete set of system module and device. The development of the computer software based on the hardware platform. The transplanted C/OS-II operating system, software application development, data processing, real-time display and storage (2.) to develop the PC using MCGS configuration software, complete the data real-time remote monitoring and early warning. (3) to predict the concentration of combustible gas for internal pipe gallery, the prediction method based on regression and prediction method based on Calman filter. Through the study of the two methods and simulation experiments, comparative analysis verified the predicted concentration error small Calman filtering algorithm based on (4) completed the system software, hardware design and debugging, realized the monitoring and warning of pipe gallery internal environment, to achieve the expected goal .

【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP274;TP277;TU990.3

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