物联网学报 ›› 2020, Vol. 4 ›› Issue (3): 106-111.doi: 10.11959/j.issn.2096-3750.2020.00173

• 专题:智慧交通物联网 • 上一篇    下一篇

基于分布式光纤振动传感器的铁路安全监测算法

陈复扬1,2(),姜斌1,2,沙宇1   

  1. 1 南京航空航天大学自动化学院,江苏 南京 211106
    2 物联网与控制技术江苏省高校重点实验室,江苏 南京 211106
  • 修回日期:2020-05-28 出版日期:2020-09-30 发布日期:2020-09-07
  • 作者简介:陈复扬(1967- ),男,江苏扬州人,南京航空航天大学自动化学院教授,主要研究方向为物联网控制及自愈合控制|姜斌(1966- ),男,江西潘阳人,南京航空航天大学自动化学院教授,主要研究方向为故障诊断与容错控制|沙宇(1996- ),男,江苏南通人,南京航空航天大学自动化学院硕士生,主要研究方向为控制理论与控制工程

Railway safety monitoring algorithm based on distributed optical fiber vibration sensor

Fuyang CHEN1,2(),Bin JIANG1,2,Yu SHA1   

  1. 1 College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
    2 Jiangsu University Key Laboratory of Internet of Things and Control Technology,Nanjing 211106,China
  • Revised:2020-05-28 Online:2020-09-30 Published:2020-09-07

摘要:

针对铁路沿线存在人员攀爬栅栏网这一问题,将分布式光纤传感技术和信号分析技术相结合,提出了一种基于分布式光纤振动传感器的铁路安全监测算法。通过沿铁路周界栅栏网敷设的光缆感知并传导信号,搭建铁路与监测算法的物联网连接,实现对攀爬行为的智能化监测。针对铁路周围环境较复杂、干扰较多的情况,采用海明窗分帧加小波阈值去噪的方法对每帧信号进行滤波,提高了振动信号的信噪比。在特征选择上,从时域和频域上分别提取信号的功率和短时过电平率作为联合特征,对是否存在攀爬行为进行判别。因为攀爬行为具有空间上的连续性,在监测过程中设置最小报警范围滤除范围过小的报警,提高了监测系统的准确性。

关键词: 分布式光纤振动传感器, 铁路沿线, 信号处理, 入侵, 物联网

Abstract:

Aiming at the monitoring problem of the human climbing behaviour existing along the railway,a railway safety detection algorithm based on distributed optical fiber vibration sensors was proposed by combining the distributed optical fiber sensing technology and signal analysis technology.The surrounding vibration was sensed and transmitted through the optical cables laid along the fence network of the railway,and then the Internet of things (IoT) connection between the railway and monitoring algorithm was built to realize the intelligent monitoring of the climbing behavior.In view of the complicated surrounding environment of the railway and more interference,the Hamming window and wavelet threshold denoising method were used to filter the signal of each frame to improve the signal-to-noise ratio of the vibration signal.In the selection of features,the power spectrum and short-time over-level rate of the signal were extracted from the time domain and frequency domain respectively as a joint feature to determine whether there was climbing or creeping behavior.Since that the climbing behavior was spatially continuous,the minimum alarm range was set to filter out alarms with a too small range,which improved the accuracy of the monitoring system.

Key words: distributed optical fiber vibration sensor, along the railway, signal processing, intrusion, Internet of things

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