煤矿井下R-OTDR光纤EEMDMAF去噪算法研究

针对煤矿井下管道存在的潜在瓦斯泄露、粉尘爆炸等问题，提出了基于Ｒ-OTDＲ( Ｒaman Optical Time Domain Ｒeflectometry) 分布式光纤温度传感器的管道安全监测方法，分析了Ｒ-OTDＲ 光纤的技术原理。对于采集过程中温度信号噪声干扰问题，分别采用滑动平均滤波和EEMD( Ensemble Empirical Mode Decomposition) 两种方法进行去噪。仿真结果表明，单独使用两种方法都不能得到最优的去噪结果。将融合滑动平均滤波及EEMD去噪算法，并采用3 个指标用于效果判定。实验结果表明: 先滑动平均再EEMD 能有效去除信号中的干扰噪声，极大地提高了信噪比和系统测量精度，相比传统算法而言，系统传感效率更高。

Ｒesearch on Denoising Algorithm of Ｒ-OTDＲ Fiber EEMDMAF in Coal Mine

Aiming at the problems of potential gas leakage and dust explosion in coal mine underground pipelines，we proposed a pipeline safety monitoring method based on Ｒ-OTDＲ ( Ｒaman Optical Time DomainＲeflectometry) distributed optical fiber temperature sensor，and analyzed the technical principle of Ｒ-OTDＲ fiber． For the problem of temperature signal noise interference during the acquisition process，the two methods of moving average filtering and EEMD( Ensemble Empirical Mode Decomposition) are used for denoising． The simulation results show that the best noise reduction effect can not be obtained by using one method alone． This paper will combine the sliding average filtering and EEMD denoising algorithm，and use three indicators for effect determination． The experimental results show that the first moving average EEMD can effectively remove the interference noise in the signal，which greatly improves the signal-to-noise ratio and system measurement accuracy． Compared to the traditional algorithm，the system sensing efficiency is higher．