EMD联合小波阈值降噪在井下接收信号上的应用

井下闭环旋转导向钻井系统在钻进过程中受到复杂的振动，使井下通信接收装置接收到的信号包含大量的抖动噪声，影响有用信号的提取，从而导致井眼轨迹控制的稳定性变差。为有效降低背景噪声的影响，提高钻井效率，在传统小波变换理论的基础上，结合经验模态分解法(EMD)，提出一种 EMD联合小波阈值降噪滤波算法。通过EMD分解法将井下接收信号进行分解，并利用小波变换对高频固有模态函数（IMF）进行降噪处理。仿真结果表明此方法的降噪性能均优于传统降噪算法，实测数据滤波结果显示该方法复原误差较小、信号损失较小、信噪比较高，可有效滤除井下接收信号中的噪声，保证井下接收信号的正确解码。

Application of EDM Combined with Wavelet Threshold Denoising in Downhole Received Signal

The downhole closed-loop rotary steering drilling system is subject to complex vibration in the process of drilling, which makes the signals received by the downhole communication receiving device contain a lot of jitter noise, and affects the extraction of useful signals, thus leading to the poor stability of wellbore trajectory control. In order to effectively reduce the influence of background noise and improve drilling efficiency, based on the traditional wavelet transform theory, combined with empirical mode decomposition (EMD), an EMD combined with wavelet threshold denoising filtering algorithm is proposed. The received signal is decomposed by EMD method, and the high frequency intrinsic mode function (IMF) is denoised by wavelet transform. The simulation results show that the noise reduction performance of this method is better than the traditional noise reduction algorithm. The filtering results of measured data show that this method has smaller restoration error, smaller signal loss and higher signal-to-noise ratio. The method can effectively filter the noise in the received signal and ensure the correct decoding of the received signal.