摘要
由于矿山环境的复杂性、监测传感器的误差和磁场的干扰,实测爆破振动信号不可避免地包含大量高频噪声。为有效去除噪声成分,引入相关均方根误差获得了具有自适应能力的CEEMD算法,对矿山爆破振动信号进行精细化分解,得到频率由大到小排列的固有模态函数(IMF),对各IMF进行MPE随机性检测,将MPE值大于0.6的IMF成分去除,以达到去噪目的。将自适应CEEMD-MPE算法应用于矿山爆破振动信号去噪处理,研究结果表明:该算法具有较好的保真度和去噪效果,有效地去除了信号所含高频噪声成分,同时对真实振动信息影响较小。对比分析表明自适应CEEMD-MPE算法优于EMD-MPE和EEMD-MPE算法,验证了该算法的有效性。
Due to the complexity of mine environment,the error of monitoring sensors and the interference of magnetic field,the measured blasting vibration signal inevitably contains a lot of high-frequency noise.In order to remove the noise components,adaptive CEEMD algorithm was obtained by introducing the correlation root mean square error.This algorithm was used to fine decompose the blasting vibration signals,and obtain an intrinsic mode functions(IMF)with frequencies from large to small.Furthermore,the random MPE test was carried out for each IMF.In order to achieve the purpose of noise reduction,the IMF components with MPE value which was greater than 0.6 were removed.The results show that the algorithm has good fidelity and denoising effect.It eliminates the high frequency noise effectively and has little influence on the real information.Comparative analysis shows that the adaptive CEEMD-MPE algorithm is superior to the EMD-MPE and the EEMD-MPE algorithm,which verifies the effectiveness of the algorithm.
作者
孙兵
彭亚雄
苏莹
SUN Bing;PENG Ya-xiong;SU Ying(Wuhan City College,Wuhan 430083,China;School of Civil Engineering,Hunan University of Science and Technology,Xiangtan 411201,China)
出处
《爆破》
CSCD
北大核心
2022年第2期153-158,185,共7页
Blasting
基金
湖南省自然科学基金项目(2020JJ5163)
湖南省教育厅科学研究项目(20C0815)。
