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田璞, 杨芳南, 李红辉, 张杰, 刘真. 分布式光纤传感在铁路通信光缆盗挖告警中的应用[J]. 铁路计算机应用, 2019, 28(11): 49-54.
引用本文: 田璞, 杨芳南, 李红辉, 张杰, 刘真. 分布式光纤传感在铁路通信光缆盗挖告警中的应用[J]. 铁路计算机应用, 2019, 28(11): 49-54.
TIAN Pu, YANG Fangnan, LI Honghui, ZHANG Jie, LIU Zhen. Distributed optical fiber sensing applied to railway communication optical cable stealing and excavating alarm[J]. Railway Computer Application, 2019, 28(11): 49-54.
Citation: TIAN Pu, YANG Fangnan, LI Honghui, ZHANG Jie, LIU Zhen. Distributed optical fiber sensing applied to railway communication optical cable stealing and excavating alarm[J]. Railway Computer Application, 2019, 28(11): 49-54.

分布式光纤传感在铁路通信光缆盗挖告警中的应用

Distributed optical fiber sensing applied to railway communication optical cable stealing and excavating alarm

  • 摘要: 与目前应用的光缆防护技术相比,分布式光纤传感具有成本较低、灵敏度高、抗电磁干扰、可复用、分布式连续测量等优点,因此,提出了一种基于分布式光纤传感的铁路通信光缆盗挖告警方法。该方法通过提取振动信号的时域特征和小波域特征作为特征向量,来识别盗挖过程中产生的振动事件类型。同时,还设计了一种两级振动模式识别方案,在正常情况下,系统只对时域特征进行监测,当时域特征的值超出设定的阈值时,再联合小波域特征进行模式识别。由此,提出的方法可以减少大量复杂的小波域变换计算,提高算法的时效性。

     

    Abstract: Compared with the current optical cable protection technology, the distributed optical fiber sensing has the advantages of low cost, high sensitivity, anti-electromagnetic interference, reusability, distributed continuous measurement, etc. Therefore, this paper proposed a method of distributed optical fiber sensing based railway communication optical cable stealing and excavating alarm. In this method, the time domain features and wavelet domain features of vibration signals were extracted as feature vectors to identify the types of vibration events in the process of stealing and excavating.At the same time, a two-level vibration pattern recognition scheme was designed. Under normal circumstances, the system only monitored the time-domain features. When the value of the domain features exceeded the set threshold value, the wavelet domain features were combined for pattern recognition. The proposed method can reduce a lot of complex wavelet transform calculation and improve the timeliness of the algorithm.

     

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