自动化与仪器仪表2024,Issue(1) :126-130,136.DOI:10.14016/j.cnki.1001-9227.2024.01.126

智能机器人在高铁隧道能源设施自动监测中的应用研究

Research on the application of intelligent robots in automatic monitoring of energy facilities in high-speed railway tunnels

节忠伟 任任 白昊杰
自动化与仪器仪表2024,Issue(1) :126-130,136.DOI:10.14016/j.cnki.1001-9227.2024.01.126

智能机器人在高铁隧道能源设施自动监测中的应用研究

Research on the application of intelligent robots in automatic monitoring of energy facilities in high-speed railway tunnels

节忠伟 1任任 1白昊杰2
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作者信息

  • 1. 西南交通大学希望学院,成都 610400
  • 2. 中铁十七局集团城市建设有限公司,贵阳 550003
  • 折叠

摘要

高铁的飞速发展,不仅能够大幅缩短城市之间的距离,还能促进城市之间的经济交流和合作.高铁隧道中的能源设施对高铁的正常运行有很大的影响,而传统的人工监测方式存在诸多不足.为了解决这些问题研究构建了融合识别技术的高铁隧道电力设施智能监测机器人模型.首先对现有的监测系统进行优化,然后将识别技术融合到监测机器人的模型中,最后利用仿真实验去验证其性能.结果表明,对电力设施进行检测时,若存在电缆损坏的情况,监测机器人的检测率为95.37%;对设备运行情况的检测率为92.05%;避障成功率平均值为85.79%.验证了监测机器人在高铁隧道电力设施自动监测中的可靠性,且完全能够满足实际监测的要求.

Abstract

The rapid development of high-speed rail can not only greatly shorten the distance between cities,but also promote the economic exchange and cooperation between cities.The energy facilities in high-speed railway tunnels have a great impact on the nor-mal operation of high-speed rail,and the traditional manual monitoring method has many shortcomings.In order to solve these prob-lems the research constructs a robot model of intelligent monitoring of electric facilities in high-speed railway tunnels with fusion rec-ognition technology.Firstly,the existing monitoring system is optimized,then the recognition technology is fused into the monitoring robot model,and finally the performance is verified by using simulation experiments.The results show that the detection rate of the monitoring robot is 95.37%if there is cable damage when the electric facilities are inspected;the detection rate of equipment opera-tion is 92.05%;the average success rate of obstacle avoidance is 85.79%.It verifies the reliability of the monitoring robot in auto-matic monitoring of electric facilities in high-speed railway tunnels,and it can fully meet the requirements of actual monitoring.

关键词

智能机器人/铁路隧道/电力设备/自动监测

Key words

intelligent robot/railroad tunnels/power equipment/automatic monitoring

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基金项目

西南交通大学希望学院校级一流本科课程建设项目(第一批)(YLKC2022024)

出版年

2024
自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
参考文献量14
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