Real-time positioning technology of train based on optical fiber coherent Rayleigh backscattering北大核心CSCD

With the rapid growth of railway mileage in China, the degree of heavy load of railway wagons continues to increase. An interference technology based on Rayleigh backscattering signal in optical fiber was proposed by using existing communication optical cables along railway lines. When the fiber vibrated slightly, the phase and refractive index of the fiber at disturbed position changed, which resulting in the Rayleigh backscattering light. By performing differential calculation on the Rayleigh signal curves before and after the operation, the location of the interference light intensity signal corresponded to the location of the disturbances was obtained. Based on this method, the recognition and positioning of railway vehicles were realized. By collecting and analyzing the time-domain and frequency-domain signal, the signal strength, train length, the number of carriages and other characteristics were extracted, and the model of railway vehicles were accurately recognized. Compared with traditional positioning technologies, this technology could realize long-distance monitoring, and the sensing fiber was buried underground on both sides of the railway, which was conducive to the concealment and protection of optical fiber. Experimental results show that the positioning error of the system is within ±10 m, and the detection of railway speed and position within 25 km can be realized. © 2022 Editorial office of Journal of Applied Optics. All rights reserved.     

基于相位敏感型光时域反射仪的袋式 除尘器漏袋检测技术

采用相位敏感型光时域反射仪的分布式光纤传感系统对除尘器内滤袋进行实时监测.通过对光纤在除尘器滤袋内敷设方式的设计,实现了对除尘器内滤袋的定位.对6种类型的破袋内光纤振动信号进行采集,且当这些滤袋没有破损时,对其光纤振动信号也进行采集.采用小波包分解法计算了滤袋内光纤振动信号的信息熵和相关系数,并将两参数合并构成二维特征参量.分析了在不同的二维特征参量下,好袋内光纤振动信号和破袋内光纤振动信号之间的特征差别.以类型3滤袋信号特征样本作为训练样本对反向传播神经网络进行训练,然后对6种类型的滤袋信号特征样本进行识别,结果显示该方法对6种类型的滤袋具有较高的识别稳定性,且平均滤袋识别率分别达到96.2%、88.7%、98.4%、98.5%、98.5%、98.5%.