摘要
针对光网络中传统故障监测方法误差大、速度慢等问题,提出一种基于小波变换的链路故障监测算法。在该算法中采用动态周期轮询的方法监测链路光功率,利用小波变换在时—频域上的良好局部特性提取监测值中的故障信息。算法对监测到的光功率值进行多尺度分解以降低噪声影响,从而提高故障监测的准确性。仿真结果表明,与时域的分析方法相比,基于小波变换的故障监测算法能够较好地克服噪声影响,漏警率减少到0,误警率降低了5百分点;而且实验环境下的故障监测时间为2.53～3.12 ms,能够满足实时需要。
The traditional fault monitoring methods have some problems such as great deviation and slow speed. To solve these problems, a link fault monitoring algorithm based on the wavelet transform was presented. This algorithm used the dynamic polling scheme to detect the optical power and used the local characteristic in time-frequency domain of the wavelet transform to extract the fault information from the detection value. The monitoring optical power value was decomposed with multi-scale to eliminate the effects of noise, thereby improving the accuracy of the fault monitoring. The experimental results show that compared to the analytucal methods in time domain, the proposed fault monitoring algorithm based on wavelet transform is better to overcome the effects of noise. The leakage alarm rate is reduced to zero and the false alarm rate is decreased by five percentage. The monitoring time is between 2.53 ms and 3.12 ms, which can meet the real-time requirement.
出处
《计算机应用》
CSCD
北大核心
2013年第2期382-384,399,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(60972096
61001105)
重庆市自然科学基金资助项目(2011BA2041)
重庆市教委科学技术研究项目(KJ110531)
重庆市高校优秀人才支持计划项目(2011-29)
关键词
光网络
小波变换
故障监测
光功率
奇异性监测
optical network
wavelet transform
fault monitoring
optical power
singularity monitoring
