摘要
为了更加准确高效地提取原始随钻钻井液脉冲信号,提出了一种基于互补集合经验模态分解(CEEMD)与平波整形算法的提取算法。采用基于固定'筛'数量停止准则的CEEMD对含噪信号进行分解,以连续均方误差(CMSE)指标为理论判据,重构信号的低频分量;提出平波预处理策略改进现行的脉冲整形算法,对重构后的信号进行整形处理,即可获得准确的钻井液脉冲信号。进行了仿真分析和实验研究,结果表明,该算法可以准确提取原始脉冲信号,提高了系统的实时性,且更加符合工程实际使用要求。
To extract the original pulse signal more accurately and efficiently in measurement while drilling,a denoising algorithm based on complementary ensemble empirical mode decomposition( CEEMD) and pulse shaping algorithm was presented. The CEEMD based on the fixed sifting number criterion was used to decompose the noisy signal,and the continuous mean square error( CMSE) was introduced to select the intrinsic modal functions( IMFs) to reconstruct the signal. The flattening shaping algorithm was proposed to improve the current pulse shaping algorithm,and the reconstructed signal was shaped by the flattening shaping algorithm to obtain the drilling fluid pulse signal. Finally,the numerical simulation and the measured signal experiments were carried out,the results have shown that the algorithm can extract the original pulse signal accurately and also improve its real-time performance,and it more accords with actual usage demand in engineering.
出处
《电子测量与仪器学报》
CSCD
北大核心
2018年第3期170-176,共7页
Journal of Electronic Measurement and Instrumentation
