矿山震动信号预处理及其对时频的影响
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摘要
矿山震动信号在研究微震特征、震动衰减规律、震动灾害评估方面起到至关重要作用。然而,实测的信号往往受到低频的基线漂移和50 Hz的工频干扰的影响,从而影响信号的质量,尤其是当信号能量较低时。为了解决这个问题,提出了一种根据信号自适应改变参数的矿山滤波器,作为实测信号的补充预处理程序。首先,根据线性相位FIR滤波器原理给出了能自动化计算滤波参数的切比雪夫设计方法。然后根据矿山实际的需求,加入了自动调整步骤,该步骤可根据50 Hz频率与周边频率的差距改变滤波器在该频率附近的衰减幅度。最后,评估了信号在滤波前、后的PPV、主频、傅里叶谱、小波时频谱和绝对加速度反应谱的变化。结果表明,提出的矿山自适应滤波器能够很好地过滤干扰信号,并且尽可能地保留信号原有的时频特征。
Mining vibration plays an important role in research such as microseismic characteristics,vibration attenuations,and the hazard evaluation of vibration. However,the baseline drift caused by low frequencies and the 50 Hz power line interferences often reduces the quality of the measured signals,especially when the signals have a low energy.To address this issue,a finite impulse response( FIR) filter,with linear-phase and the ability of self-adaption,is suggested for the vibration signals measured in mine as a supplementary preprocessor. First,based on the linear-phase FIR theory,the automatic design procedure of the Chebyshev optimal approximation method is given. Then,according to the practical requirements in mine,a self-adaption step is added to the automatic design procedure,in order to adapt the scaling near 50 Hz based on each signal's characteristics automatically. Finally,the differences of the PPV,the dominant frequency,the Fourier spectrum,the wavelet coefficient spectrum and the absolute accelerate response spectrum between the signals before and after filtered are assessed. The result shows that the proposed filter can filter the interference signal efficiently,and retain the time-frequency characteristics as well as possible.
Mining vibration plays an important role in research such as microseismic characteristics,vibration attenuations,and the hazard evaluation of vibration. However,the baseline drift caused by low frequencies and the 50 Hz power line interferences often reduces the quality of the measured signals,especially when the signals have a low energy.To address this issue,a finite impulse response( FIR) filter,with linear-phase and the ability of self-adaption,is suggested for the vibration signals measured in mine as a supplementary preprocessor. First,based on the linear-phase FIR theory,the automatic design procedure of the Chebyshev optimal approximation method is given. Then,according to the practical requirements in mine,a self-adaption step is added to the automatic design procedure,in order to adapt the scaling near 50 Hz based on each signal's characteristics automatically. Finally,the differences of the PPV,the dominant frequency,the Fourier spectrum,the wavelet coefficient spectrum and the absolute accelerate response spectrum between the signals before and after filtered are assessed. The result shows that the proposed filter can filter the interference signal efficiently,and retain the time-frequency characteristics as well as possible.
引文
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[18]胡爱琴,袁洪福,宋春风,等.近红外离散波长光谱基线漂移校正方法研究[J].光谱学与光谱分析,2014,34(10):2606-2611.Hu Aiqin,Yuan Hongfu,Song Chunfeng,et al.A correction method of baseline drift of discrete spectrum of NIR[J].Spectroscopy and Spectral Analysis,2014,34(10):2606-2611.
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[22]Fan X,Zuo M J.Gearbox fault detection using Hilbert and wavelet packet transform[J].Mechanical Systems and Signal Processing,2006,20(4):966-982.
[23]GB 50011—2010,建筑抗震设计规范[S].
[24]Nigam N C,Jennings P C.Calculation of response spectra from strong-motion earthquake records[J].Bulletin of the Seismological Society of America,1969,59(2):909-922.
[2]薛光辉,赵新赢,柳二猛,等.基于振动信号时域特征的综放工作面煤岩识别[J].煤炭科学技术,2015,43(12):92-97.Xue Guanghui,Zhao Xinying,Liu Ermeng,et al.Time-domain characteristic extraction of coal and rock vibration signal in fully-mechanized top coal caving face[J].Coal Science and Technology,2015,43(12):92-97.
[3]李新平,陈俊桦,李友华,等.溪洛渡电站地下洞室群爆破地震效应的研究[J].岩石力学与工程学报,2010,29(3):493-501.Li Xinping,Chen Junhua,Li Youhua,et al.Study of blasting seismic effects of underground chamber group in Xiluodu Hydropower Station[J].Chinese Journal of Rock Mechanics and Engineering,2010,29(3):493-501.
[4]单仁亮,宋立伟,白瑶,等.爆破作用下冻结岩壁损伤评价的模型试验研究[J].岩石力学与工程学报,2014,33(10):1945-1952.Shan Renliang,Song Liwei,Bai Yao,et al.Model test studies of damage evaluation of frozen rock wall under blasting loads[J].Chinese Journal of Rock Mechanics and Engineering,2014,33(10):1945-1952.
[5]Hefny A.Experimental study on prediction model for maximum rebound ratio[J].Journal of Central South University of Technology,2007,14(1):115-119.
[6]夏祥,李俊如,李海波,等.爆破荷载作用下岩体振动特征的数值模拟[J].岩土力学,2005,26(1):50-56.Xia Xiang,Li Junru,Li Haibo,et al.Udec modeling of vibration characteristics of jointed rock mass under explosion[J].Rock and Soil Mechanics,2005,26(1):50-56.
[7]GB 6722—2003,爆破安全规程[S].
[8]Duvall W I,Fogelson D E.Review of criteria for estimating damage to residences from blasting vibrations(No.BM-RI-5968)[R].Bureau of Mines College Park,1962.
[9]刘敦文,粟闯,龚运高.一种基于爆破振动信号小波分析的爆破危害评判新方法[J].中南大学学报(自然科学版),2010,41(4):1574-1577.Liu Dunwen,Li Chuang,Gong Yungao.New method for blasting hazards evaluation based on wavelet analysis of blasting vibration signals[J].Journal of Central South University,2010,41(4):1574-1577.
[10]凌同华,李夕兵.多段微差爆破振动信号频带能量分布特征的小波包分析[J].岩石力学与工程学报,2005,24(7):1117-1122.Ling Tonghua,Li Xibing.Analysis of energy distributions of millisecond blast vibration signals using the wavelet packet method[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(7):1117-1122.
[11]张义平,李夕兵,赵国彦,等.爆破震动信号的时频分析[J].岩土工程学报,2006,27(12):1472-1477.Zhang Yiping,Li Xibing,Zhao Guoyan,et al.Time-frequency analysis of blasting vibration signals[J].Chinese Journal of Geotechnical Engineering,2006,27(12):1472-1477.
[12]尹俊红,李青宁,张瑞杰,等.基于精细积分法的结构碰撞反应谱研究[J].振动与冲击,2015,34(4):175-183.Yin Junhong,Li Qingning,Zhang Ruijie,et al.Structural impact response spectra based on precise time-integration method[J].Journal of Vibration and Shock,2015,34(4):175-183.
[13]杨溥,赖明.结构时程分析法输入地震波的选择控制指标[J].土木工程学报,2000,33(6):33-37.Yang Fu,Lai Ming.A new method for selecting inputting waves for time-history analysis[J].China Engineering Journal,2000,33(6):33-37.
[14]李进扬.大型地网接地电阻的测量[J].高电压技术,2006,32(10):141-142.Li Jinyang.Measurement of earth resistance of a huge ground grid[J].High Voltage Engineering,2006,32(10):141-142.
[15]石坚,杨永明.50Hz陷波器在脑电数据采集系统中的应用[J].重庆大学学报:自然科学版,2005,28(8):25-27.Shi Jian,Yang Yongming.Application of trap filter of 50 Hz in brainwave data acquisition system[J].Journal of Chongqing University(Natural Science Edition),2005,28(8):25-27.
[16]王楠,秦其明,陈理,等.天然源超低频电磁探测技术在煤储层识别中的应用[J].煤炭学报,2014,39(1):141-146.Wang Nan,Qin Qiming,Chen Li,et al.Natural source super-low frequency electromagnetic prospecting in the application of coalbed methane reservoir identification[J].Journal of China Coal Society,2014,39(1):141-146.
[17]张泾周,寿国法,戴冠中.基于小波变换的心电信号噪声处理[J].西北工业大学学报,2005,23(1):11-14.Zhang Jingzhou,Shou Guofa,Dai Guanzhong.Denoising of ECG signals based on wavelet transform[J].Journal of Northwestern Polytechnical University,2005,23(1):11-14.
[18]胡爱琴,袁洪福,宋春风,等.近红外离散波长光谱基线漂移校正方法研究[J].光谱学与光谱分析,2014,34(10):2606-2611.Hu Aiqin,Yuan Hongfu,Song Chunfeng,et al.A correction method of baseline drift of discrete spectrum of NIR[J].Spectroscopy and Spectral Analysis,2014,34(10):2606-2611.
[19]Mc Clellan J,Parks T.A unified approach to the design of optimum FIR linear-phase digital filters[J].Circuit Theory,IEEE Transactions on,1973,20(6):697-701.
[20]Mc Clellan J H,Parks T W,Rabiner L.A computer program for designing optimum FIR linear phase digital filters[J].Audio and Electroacoustics,IEEE Transactions on,1973,21(6):506-526.
[21]Amiri G G,Bagheri A,Seyed Razaghi S A.Generation of multiple earthquake accelerograms compatible with spectrum via the wavelet packet transform and stochastic neural networks[J].Journal of Earthquake Engineering,2009,13(7):899-915.
[22]Fan X,Zuo M J.Gearbox fault detection using Hilbert and wavelet packet transform[J].Mechanical Systems and Signal Processing,2006,20(4):966-982.
[23]GB 50011—2010,建筑抗震设计规范[S].
[24]Nigam N C,Jennings P C.Calculation of response spectra from strong-motion earthquake records[J].Bulletin of the Seismological Society of America,1969,59(2):909-922.