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彩信图像监测技术在河道冰-水情远程无人监测中的应用
  • ISSN号:1000-0984
  • 期刊名称:《数学的实践与认识》
  • 时间:0
  • 分类:TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]太原理工大学新型传感器与智能控制教育部重点实验室,山西太原830024, [2]黄河水利委员会宁蒙水文水资源局,内蒙古包头014030
  • 相关基金:2009年度高等学校博士学科点专项科研基金(20091402110004);山西省回国留学人员科研资助(2012-045)
中文摘要:

针对黄河中上游冰凌灾害预报系统的建设,设计研制了黄河河道冰、水情图像远程无人自动监测系统.该系统基于GPRS移动通信中彩信图像数据传输技术,利用单片机控制摄像探头采集和压缩黄河河道现场冰情图像信息,通过GPRS网络以彩信格式发送到用户手机,实现了对黄河河道冰情图像的无线远程实时监测.该系统可以使冰情检测人员在移动过程中随时获取河道实时冰情图像信息,更加适合野外环境下冰凌灾害预防的监测与预报,具有较大的工程应用价值.

英文摘要:

Based on the new research results, in the detection of ice-water obtained by the Institute of Measurement and Control Technology in Taiyuan University of Technology, remote automatic monitoring system for the ice-water of the Yellow river was developed according to the field test according to the the construction of the ice disaster prediction system for the upper reaches in the Yellow River. For the limitations of the the special environment of the channel, the mobile communication technology GPRS was used in research of the system to get the remote real-time image of the ice in the Yellow River ice flood season. By using the single chip computer technology, the GPRS wireless communication module with MMS agreement and the image acquisition and image compression function modules, the single-chip computer can control the serial camera to achieve the image processing and image compression and then the collecting image will be sented to the mobile phone user through the MMS forma, in order to realize the wireless remote monitoring of the ice thickness and ice image. Selecting the appropriate monitoring points is to achieve the remote monitoring to get the information of river regime, which can achieve the automatic monitoring and and emergency monitoring of the forming process of the Yellow River ice. The system has the advantages of regular monRoring, stable performance and low power consumption.

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期刊信息
  • 《数学的实践与认识》
  • 中国科技核心期刊
  • 主管单位:中国科学院
  • 主办单位:中国科学院数学与系统科学研究院
  • 主编:林群
  • 地址:北京大学数学科学学院
  • 邮编:100871
  • 邮箱:bjmath@math.pku.edu.cn
  • 电话:010-62759981
  • 国际标准刊号:ISSN:1000-0984
  • 国内统一刊号:ISSN:11-2018/O1
  • 邮发代号:2-809
  • 获奖情况:
  • 国内外数据库收录:
  • 美国数学评论(网络版),德国数学文摘,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:22973