基于移动窗口均值滤波算法处理地空瞬变电磁基线漂移
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摘要
人类获取地下矿产资源后遗留大量的采空区,采空区坍塌等地质灾害给矿山安全开采和周居民带来了极大的安全隐患.近年来,地下隐伏采空区的探测技术和方法得到飞速发展,本文以东川滥泥坪铜矿采空区的测探数据为例,针对大数据量的地空瞬变电磁数据,提出采用基于移动窗口的均值滤波算法.此算法是一种效率优先的算法,算法的时间复杂度为O(L).该算法假设一个周期内的基线符合一维线性分布,使用此算法时窗口长度宜选择一个供电周期的数据长度.将算法应用于KTEM地空瞬变电磁的基线漂移处理,处理后95%的基线数据处于±0.1 mV范围内,时间序列的基线漂移问题得到明显改善,利用CUDA技术并行计算,提升计算精度,探测结果得到更好的处理效果.
A large number of goaf are left behind after human beings acquire underground mineral resources. The collapse of goaf and other geological hazards bring great potential dangers to mining safety and surrounding residents. In recent years, the detection technology and methods of underground hidden goaf have developed rapidly. Based on the detection data of the goaf of Lanniping Copper Mine in Dongchuan, this paper proposes a moving window based mean filter algorithm for large amount of ground-to-air transient electromagnetic data. This algorithm is an efficiency first algorithm, and the time complexity of the algorithm is O(L). Assuming that the baseline in a cycle is in line with one-dimensional linear distribution, the window length should be chosen for a power supply cycle. The algorithm is applied to the baseline drift processing of KTEM Semi-Airborne Transient Electromagnetic(SATEM). 95% of the baseline data are in the range of(+0.1 mV) after processing, and the baseline drift problem of time series is obviously improved. Using CUDA technology in parallel computing can improve the accuracy of calculation and the detection results can be processed better.
A large number of goaf are left behind after human beings acquire underground mineral resources. The collapse of goaf and other geological hazards bring great potential dangers to mining safety and surrounding residents. In recent years, the detection technology and methods of underground hidden goaf have developed rapidly. Based on the detection data of the goaf of Lanniping Copper Mine in Dongchuan, this paper proposes a moving window based mean filter algorithm for large amount of ground-to-air transient electromagnetic data. This algorithm is an efficiency first algorithm, and the time complexity of the algorithm is O(L). Assuming that the baseline in a cycle is in line with one-dimensional linear distribution, the window length should be chosen for a power supply cycle. The algorithm is applied to the baseline drift processing of KTEM Semi-Airborne Transient Electromagnetic(SATEM). 95% of the baseline data are in the range of(+0.1 mV) after processing, and the baseline drift problem of time series is obviously improved. Using CUDA technology in parallel computing can improve the accuracy of calculation and the detection results can be processed better.
引文
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Su F. 2016. Design of the Semi-airborne Time-Domain Transient Electro-magnetic Receiving System[Master’s thesis]. Jilin: Jilin University.
Zhang L. 2017. The development of semi-airborne transient electromagnetic receiver[Master’s thesis].Chengdu:Chengdu University of Technology.
Zhang X Y. 2016. Research on Air-ground UAV transient electromagnetic data acquisition Technology[Master’s thesis]. Beijing: China Coal Research Institute CCRI.
Zhang X Y, Wu Y Q, Zhang J, et al. 2016. Research on Transient Electromagnetic Synchronous Acquisition Technology with Semi-aviation Pilotless Plane Based on Signal Peak[J]. Mining Safety & Environmental Protection, 43(2):41- 44.
Zhang Y Y, Li X. 2017. Research progress on ground-airborne transient electromagnetic method[J]. Progress in Geophysics,32(04):1735-1741, doi: 10.6038/pg20170443.
Zhu W F ,Qi C. 2006. An Applied Basel ine Filtering Algorithm[J]. Journal of Soochow University (Engineering Science Edition),26(01):62- 64.
方涛,张建军,付成群,等. 2015. 无人机地空瞬变电磁系统在冶山地下巷道探测中的应用[J]. 地球物理学进展,30(05):2366-2372, doi: 10.6038/Pg20150252.
高嵩,王金梅,张良,等. 2017. 半航空瞬变电磁接收机的测试装置研制[J]. 地球物理学进展,32(03):1339-1345, doi: 10.6038/pg20170352.
郭媛,赵学玒,张锐,等. 2013. 小波变换应用于谐波谱线的噪声滤除与基线校正[J]. 光谱学与光谱分析,33(08):2172-2176, doi:10.3964/j.issn. 1000- 0593(2013)08-2172- 05.
姜安,彭江涛,谢启伟,等. 2012. 一种改进的非对称最小二乘基线校正算法[J]. 计算机与应用化学,29(05):537-540, doi:10.16866/j.com.app.chem2012.05.006.
李肃义,林君,阳贵红,等. 2013. 电性源时域地空电磁数据小波去噪方法研究[J]. 地球物理学报,56(09):3145-3152, doi:10.6038/cjg20130927.
刘富波,李巨涛,刘丽华,等. 2017. 无人机平台半航空瞬变电磁勘探系统及其应用[J]. 地球物理学进展,32(05):2222-2229, doi: 10. 6038/pg20170551.
苏发. 2016. 半航空时间域瞬变电磁接收系统设计[硕士论文].长春:吉林大学.
张良. 2017. 半航空瞬变电磁接收机研制[硕士论文].成都:成都理工大学.
张晓宇. 2016. 空—地无人机瞬变电磁数据采集技术研究[硕士论文].北京:煤炭科学研究总院.
张晓宇,吴燕清,张军,等. 2016. 基于信号峰值的半航空无人机瞬变电磁同步采集技术研究[J]. 矿业安全与环保, 43(2):41- 44.
张莹莹,李貅. 2017. 地空瞬变电磁法研究进展[J]. 地球物理学进展,32(04):1735-1741, doi: 10.6038/pg20170443.
朱伟芳,齐春. 2006. 一种实用的去基线漂移滤波算法[J]. 苏州大学学报(工科版),26(01):62- 64.
Gao S, Wang J M, Zhang L, et al. 2017. Development of test device for semi-airborne transient electromagnetic receiver[J]. Progress in Geophysics,32(03):1339-1345, doi: 10.6038/pg20170352.
Guo Y, Zhao X H, Zhang R, et al. 2013. The Noise Filtering and Baseline Correction for Harmonic Spectrum Based on Wavelet Transform[J]. Pectroscopy and Spectral Analysis,33(08):2172-2176, doi:10.3964/j.issn. 1000- 0593(2013)08-2172- 05.
Jiang A, Peng J T, Xie Q W,et al. 2012. An improved asymmetric least squares baseline correction algorithm[J]. Computers and Applied Chemistry,29(05):537-540, doi:10.16866/j.com.app.chem2012.05.006.
Li S Y, Lin J, YANG Gui-hong, et al. 2013. Ground-Airborne Electromagnetic Signals De-noising using a Combined Wavelet Transform Algorithm[J]. Chinese Journal of Geophysics,56(09):3145-3152, doi:10.6038/cjg20130927.
Liu Fu-bo, Li J T, Liu L H, et al. 2017. Development and application of a new semi-airborne transient electromagnetic system with UAV platform[J]. Progress in Geophysics, 32(05):2222-2229, doi: 10. 6038/pg20170551.
Liu X B, Zhang Z M, Liang Y Z, et al. 2014. Baseline correction of high resolution spectral profile data based on exponential smoothing[J]. Chemometrics and Intelligent Laboratory Systems,2014(139): 97-108, doi:10.1016/j.chemolab.2014.09.018.
?ukasz G, Filip C, Ma?gorzata J. 2014. Automatic baseline correction in voltammetry[J]. Electrochimica Acta, 2014(136):195-203, doi:10.1016/j.electacta.2014.05.076.
Su F. 2016. Design of the Semi-airborne Time-Domain Transient Electro-magnetic Receiving System[Master’s thesis]. Jilin: Jilin University.
Zhang L. 2017. The development of semi-airborne transient electromagnetic receiver[Master’s thesis].Chengdu:Chengdu University of Technology.
Zhang X Y. 2016. Research on Air-ground UAV transient electromagnetic data acquisition Technology[Master’s thesis]. Beijing: China Coal Research Institute CCRI.
Zhang X Y, Wu Y Q, Zhang J, et al. 2016. Research on Transient Electromagnetic Synchronous Acquisition Technology with Semi-aviation Pilotless Plane Based on Signal Peak[J]. Mining Safety & Environmental Protection, 43(2):41- 44.
Zhang Y Y, Li X. 2017. Research progress on ground-airborne transient electromagnetic method[J]. Progress in Geophysics,32(04):1735-1741, doi: 10.6038/pg20170443.
Zhu W F ,Qi C. 2006. An Applied Basel ine Filtering Algorithm[J]. Journal of Soochow University (Engineering Science Edition),26(01):62- 64.
方涛,张建军,付成群,等. 2015. 无人机地空瞬变电磁系统在冶山地下巷道探测中的应用[J]. 地球物理学进展,30(05):2366-2372, doi: 10.6038/Pg20150252.
高嵩,王金梅,张良,等. 2017. 半航空瞬变电磁接收机的测试装置研制[J]. 地球物理学进展,32(03):1339-1345, doi: 10.6038/pg20170352.
郭媛,赵学玒,张锐,等. 2013. 小波变换应用于谐波谱线的噪声滤除与基线校正[J]. 光谱学与光谱分析,33(08):2172-2176, doi:10.3964/j.issn. 1000- 0593(2013)08-2172- 05.
姜安,彭江涛,谢启伟,等. 2012. 一种改进的非对称最小二乘基线校正算法[J]. 计算机与应用化学,29(05):537-540, doi:10.16866/j.com.app.chem2012.05.006.
李肃义,林君,阳贵红,等. 2013. 电性源时域地空电磁数据小波去噪方法研究[J]. 地球物理学报,56(09):3145-3152, doi:10.6038/cjg20130927.
刘富波,李巨涛,刘丽华,等. 2017. 无人机平台半航空瞬变电磁勘探系统及其应用[J]. 地球物理学进展,32(05):2222-2229, doi: 10. 6038/pg20170551.
苏发. 2016. 半航空时间域瞬变电磁接收系统设计[硕士论文].长春:吉林大学.
张良. 2017. 半航空瞬变电磁接收机研制[硕士论文].成都:成都理工大学.
张晓宇. 2016. 空—地无人机瞬变电磁数据采集技术研究[硕士论文].北京:煤炭科学研究总院.
张晓宇,吴燕清,张军,等. 2016. 基于信号峰值的半航空无人机瞬变电磁同步采集技术研究[J]. 矿业安全与环保, 43(2):41- 44.
张莹莹,李貅. 2017. 地空瞬变电磁法研究进展[J]. 地球物理学进展,32(04):1735-1741, doi: 10.6038/pg20170443.
朱伟芳,齐春. 2006. 一种实用的去基线漂移滤波算法[J]. 苏州大学学报(工科版),26(01):62- 64.