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作 者:景丽暄 耿明[2] 凌人 周明翔[2] Jing Lixuan;Geng Ming;Ling Ren;Zhou Ming xiang(School of Automaion,Nanjing University of Aeronautics and Astrona aticso Nanjing 210016,China;China Railway Fourth Survey and Design lnstitute Group Co.,Ltd.,Wuhan 430063,China;Ningbo Reil Transit Group Co.,Ltd.,Ningbo 315100,China)
机构地区:[1]南京航空航天大学自动化学院,南京210016 [2]中铁第四勘察设计院集团有限公司,武汉430063 [3]宁波市轨道交通集团有限公司,宁波315100
出 处:《电子测量技术》2022年第14期55-58,共4页Electronic Measurement Technology
基 金:国家重点研发计划(2018YFB2100903);科技部创新方法工作专项(2020IM020800)资助。
摘 要:地下管廊中管道的泄漏检测是管廊安全运行的重要保障之一,为了实现管廊的自动化运行,并针对传统检测方法的灵活性不足、信息交互性差的缺点,本文基于STM32F103设计了一种挂轨式管道泄漏检测机器人。机器人搭载MIC声音传感器作为泄漏检测装置,将采集到的信号利用神经网络进行音频特征的识别,监控主机对判断结果做出报警或其他措施。经过管道泄漏检测系统实验平台测试,机器人系统运行稳定,对于管道泄漏的检出率达到93%,满足实际应用需求。Leak detection of pipes in underground pipe gallery is one of the important guarantees for the safe operation of pipe gallery. In order to realize the automatic operation of pipe gallery, and for the shortcomings of insufficient flexibility and poor information interaction of traditional detection methods, this paper designs a new method based on STM32 F103. Rail-mounted pipeline leak detection robot. The robot is equipped with a MIC sound sensor as a leak detection device, and the collected signal uses a neural network to identify the audio features, and the monitoring host makes an alarm or other measures on the judgment result. After the test of the pipeline leakage detection system experimental platform, the robot system runs stably, and the detection rate of pipeline leakage reaches 93%, which meets the practical application requirements.
分 类 号:U216.3[交通运输工程—道路与铁道工程]
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