光纤通信网络中故障优化诊断方法仿真

发布时间：2018-06-27 06:49

本文选题：光功率值 + 监测　；参考：《计算机仿真》2014年09期

【摘要】：在光纤通信网络故障诊断问题的研究中,为及时准确的诊断出光纤故障,对光纤通信网络故障的检测需根据光纤通光后的信号异常曲线变化,完成各种故障判断。但是,由于在长距离的光纤通信中,通光后的故障信号随着传输距离的扩大,会发生较大程度的衰减,造成故障信号曲线发生非正常形变。传统的光纤故障检测方法只能根据采集的信号的异常变化判断光纤故障,对于光纤故障信号的长距离衰减形变无法与正常故障信号进行区分,容易出现误判。提出一种利用光功率值监测方法的光纤故障诊断方法。根据OTDR发射的激光脉冲信号在光纤中的后向瑞利散射和菲涅尔反射对光纤通信网络的功率值进行监测,并将样本的光功率值数据进行均值化处理,获取准确的OTDR故障曲线,为故障点的定位提供准确的数据基础。综合OTDR接收到的反射光功率值变化情况,最终获取准确的光纤故障点的定位。实验结果表明,利用光功率值监测方法对光纤故障进行诊断,极大的提高了诊断结果的准确性,缩短了诊断时间。
[Abstract]:In the research of optical fiber communication network fault diagnosis, in order to diagnose the optical fiber fault in time and accurately, the detection of the optical fiber communication network fault must be based on the signal abnormal curve change after optical fiber switching, and complete all kinds of fault judgment. However, in the long distance optical fiber communication, the fault signal will attenuate with the increase of transmission distance, resulting in abnormal deformation of the fault signal curve. The traditional optical fiber fault detection method can only judge the optical fiber fault according to the abnormal change of the collected signal. The long distance attenuation deformation of the optical fiber fault signal can not be distinguished from the normal fault signal, so it is easy to misjudge. An optical fiber fault diagnosis method using optical power value monitoring method is proposed. According to the backward Rayleigh scattering and Fresnel reflection of the laser pulse signal emitted by OTDR in optical fiber, the power value of optical fiber communication network is monitored, and the optical power value data of the sample are processed to get the accurate OTDR fault curve. Provide accurate data base for fault location. According to the change of reflected light power received by OTDR, the accurate location of optical fiber fault point is obtained. The experimental results show that using optical power monitoring method to diagnose optical fiber faults can greatly improve the accuracy of the diagnosis results and shorten the diagnosis time.
【作者单位】：河南财经政法大学计算机与信息工程学院;信阳农林学院计算机科学系;
【分类号】：TN929.11

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