为了减小拉曼散射光波长相关损耗、光电探测器附加噪声及散射光中的瑞利噪声对分布式光纤温度传感器测温误差的影响，通过分析分布式光纤温度传感系统的解调原理提出了一种反斯托克斯光降噪方法。将光纤按照环形结构铺设，以每次测量的反斯托克斯光信号中菲涅耳反射峰后的基底噪声平均值作为动态本底噪声，利用两段处于不同温度的光纤消除动态本底噪声后的瑞利噪声。反斯托克斯光降噪解调法从原理上避免了参考斯托克斯光引入的测温误差，消除了本底噪声和瑞利噪声导致的测温误差。实验结果表明，修正的分布式光纤温度传感系统的最大测温误差从5.4 ℃降低到0.6 ℃，测温准确度有明显提高。

提出一种新型智能化长距离光纤预警系统,研究了该系统在真实工作环境下的预测准确性。该预警系统主要分为分布式传感和信号识别两个部分,其中相位敏感光时域反射(Φ-OTDR)技术用于系统的分布式传感部分,而神经网络技术用于信号识别部分,以对入侵事件进行识别和分类。在信号识别部分创新地提出了一种改进型神经网络结构,并使用基于小波包分解的神经网络和具有三个隐藏层的神经网络等其他两种方法进行效果对比。最后,通过三次不同的实验,探究了系统的识别准确性。结果表明,基于改进型神经网络的光纤预警系统在入侵事件识别方面具有优良的分类效果,平均识别率达到95%以上。

A novel multi-channel distributed optical fiber intrusion monitoring system with smart fiber link backup and on-line fault diagnosis functions was proposed. A 1×N optical switch was intelligently controlled by a peripheral interface controller (PIC) to expand the fiber link from one channel to several ones to lower the cost of the long or ultra-long distance intrusion monitoring system and also to strengthen the intelligent monitoring link backup function. At the same time, a sliding window auto-correlation method was presented to identify and locate the broken or fault point of the cable. The experimental results showed that the proposed multi-channel system performed well especially whenever any a broken cable was detected. It could locate the broken or fault point by itself accurately and switch to its backup sensing link immediately to ensure the security system to operate stably without a minute idling. And it was successfully applied in a field test for security monitoring of the 220-km-length national borderline in China.

研究基于Φ-光时域反射计(Φ-OTDR)技术的分布式光纤传感方法,分析了基于相干光时域反射计的分布式光纤振动传感机理。在此基础上系统采用一段40 km多芯通信光缆中的一芯光纤作为传感光纤进行通信光缆险情定位与预警试验。试验结果表明,该系统可对40 km通信光缆不同位置的入侵事件自动识别预警,显示险情位置,定位精度优于50 m。