摘要
由于隧道工程的复杂环境、电磁干扰和仪器误差等原因,现场实测爆破地震波信号中存在大量高频噪声。为有效降低实测信号的噪声成分,对原始信号进行自适应噪声的完全集合经验模态分解(CEEMDAN),对分解得到的模态函数(IMF)进行多尺度排列熵(MPE)的随机性检测,去除噪声IMF分量达到降噪的目的。对实测隧道爆破地震波信号处理表明:该方法不仅能够较好地去除高频噪声,而且对地震波信号所含主要信息的影响极小。波形分析和降噪效果指标均表明CEEMDAN-MPE算法均优于EEMD-MPE和CEEMDAN算法,验证了该方法的有效性。
Due to the complex environment,electromagnetic interference and instrument error of tunnel engineering,there are a lot of high-frequency noises in the seismic wave signals measured in field blasting.In order to effectively reduce the noise components of the measured signals,the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) is performed on the original signals,and randomness detection of the multi-scale permutation entropy(MPE) is performed on the intrinsic mode function(IMF),so as to remove the IMF component of the noise to achieve the purpose of noise reduction.The processing results of the measured blasting seismic signal show that the method can not only remove the high-frequency noise well but also has little influence on the main part of the seismic signal.Both waveform analysis and noise reduction effect indexes show that the CEEMDAN-MPE algorithm is superior to the EEMD-MPE and CEEMDAN algorithm,which verifies the effectiveness of this method.
作者
黄智刚
吕虎波
林一庚
彭亚雄
吴立
陈劲
HUANG Zhi-gang;LV Hu-bo;LIN Yi-geng;PENG Ya-xiong;WU Li;CHEN Jin(Faculty of Engineering,China University of Geosciences,Wuhan 430074,China;Fuzhou Water Affairs Pingtan Water Diversion Development Co.,Ltd.,Fuzhou 350001,China;Zhejiang Tunnel Engineering Group Co.,Ltd.,Hangzhou 310030,China;Fuzhou City Construction Design and Research Institute Co.,Ltd.,Fuzhou 350001,China;Hunan Provincial Key Laboratory of Geotechnical Engineering for Stability Control and Health Monitoring,Hunan University of Science and Technology,Xiangtan 411201,China)
出处
《爆破》
CSCD
北大核心
2020年第4期138-144,共7页
Blasting
基金
国家自然科学基金(41672260)
湖南省自然科学基金项目(2020JJ5163)
湖南省教育厅科学研究项目(19C0736)。
