基于时差估计的管道漏点定位方法
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摘要
时差估计精度是影响管道漏点定位准确与否的重要因素。针对复杂噪声环境下管道泄漏点定位不准确问题,提出一种基于经验模态分解重构的互相关时差估计管道漏点定位方法。首先对含噪信号进行经验模态分解,得到一系列按频率从高到低排列的本征模态函数,利用Pearson相关系数法在本征模态函数中判定出噪声分量与信号分量的分界,把信号分量重构,实现信号降噪;最后基于广义互相关法对降噪后的求取两路信号的时差后,再使用线性定位法对管道泄漏位置定位。实验表明,该方法能有效滤除漏点定位监测过程中的非平稳随机噪声,获得了较高的时差估计精度,提高了管道漏点定位的准确性。
The precision of time delay estimation is an important factor affecting the accuracy of pipeline leakage location.To solve the problem of inaccurate pipeline leakage location in noisy environments,apipeline leakage location method based on empirical mode decomposition and cross-correlation time delay estimation was presented.Firstly,empirical mode decomposition was conducted on the noisy signals and a series of eigenmode functions arrayed from high frequency to low frequency were obtained.Pearson correlation coefficients were used to determine the demarcation between noise components and signal components in the eigenmode functions so as to reconstruct signal components and reduce signal noise.Finally,the pipeline leakage was located by using the linear method after the time delay between the two signals was obtained based on the generalized cross-correlation method for noise reduction.Experiments show that this method can effectively filter out the random nonstationary noise in the monitoring process of leakage location,obtain higher time delay estimation precision,and improve the accuracy of pipeline leakage location.
The precision of time delay estimation is an important factor affecting the accuracy of pipeline leakage location.To solve the problem of inaccurate pipeline leakage location in noisy environments,apipeline leakage location method based on empirical mode decomposition and cross-correlation time delay estimation was presented.Firstly,empirical mode decomposition was conducted on the noisy signals and a series of eigenmode functions arrayed from high frequency to low frequency were obtained.Pearson correlation coefficients were used to determine the demarcation between noise components and signal components in the eigenmode functions so as to reconstruct signal components and reduce signal noise.Finally,the pipeline leakage was located by using the linear method after the time delay between the two signals was obtained based on the generalized cross-correlation method for noise reduction.Experiments show that this method can effectively filter out the random nonstationary noise in the monitoring process of leakage location,obtain higher time delay estimation precision,and improve the accuracy of pipeline leakage location.
引文
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[22]ALVANITOPOULOS P F,PAPAVASILEIOU M,ANDREADIS I,et al.Seismic intensity feature construction based on the Hilbert-Huang transform[J].IEEE Transactions on Instrumentation and Measurement,2012:61(2):326-337.
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[24]BEENAMOL M,PRABAVATHY S,MOHANALIN J.Wavelet based seismic signal de-noising using Shannon and Tsallis entropy[J].Computers &Mathematics with Applications,2012,64(11):3580-3593.
[25]CHATLANI N,SORAGHAN JJ.EMD-based filtering(EMDF)of low-frequency noise for speech enhancement[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(4):1158-1166.
[26]王玉静,康守强,张云,等.基于集合经验模态分解敏感固有模态函数选择算法的滚动轴承状态识别方法[J].电子与信息学报,2014,36(3):595-600.WANG Yujing,KANG Shouqiang,ZHANG Yun,et al.Condition recognition method of rolling bearing based on ensemble empirical mode decomposition sensitive intrinsic mode function selection algorithm[J].Journal of Electronics &Information Technology,2014,36(3):595-600.
[27]PENG Z K,TSE P W,CHU F L.A comparison study of improved Hilbert-Huang transform and wavelet transform:Application to fault diagnosis for rolling bearing[J].Mechanical Systems and Signal Processing,2005,19(5):974-988.
[28]孙立瑛,李一博,曲志刚,等.EMD信号分析方法的声发射管道泄漏检测研究[J].振动与冲击,2007,26(10):161-164.SUN Li ying,LI Yibo,QU Zhigang,et al.Study on acoustic emission detection for pipeline leakage based on EMD signal analysis method[J].Journal of Vibration and Shock,2007,26(10):161-164.
[2]庄须叶,王浚璞,邓勇刚,等.光纤传感技术在管道泄漏检测中的应用与进展[J].光学技术,2011,37(5):543-550.ZHUANG Xuye,WANG Junpu,DENG Yonggang,et al.Optical fiber sensing technologies for pipeline leakage detection[J].Optical technique,2011,37(5):543-550.
[3]孙良,王建林.气体管道泄漏的仿真建模[J].系统仿真学报,2011,23(7):1310-1314.SUN Liang,WANG Jianlin.Modeling simulation of leaking gas pipeline[J].Journal of System Simulation,2011,23(7):1310-1314.
[4]孟令雅,刘翠伟,刘超,等.基于特征量提取的输气管道微泄漏检测[J].中国石油大学学报(自然科学版),2014,38(6):153-160.MENG Lingya,LIU Cuiwei,LIU Chao,et al.Characteristics extraction of acoustic leakage signal for natural gas pipeline[J].Journal of China University of Petroleum(Edition of Natural Science),2014,38(6):153-160.
[5]郝永梅,徐明,李秀中,等.基于广义概念的城市燃气管道泄漏精确定位[J].工业安全与环保,2016,4(1):80-84.HAO Yongmei,XU Ming,LI Xiuzhong,et al.The precise location of city gas pipeline leak based on the generalized concept[J].Industrial Safety and Environmental Protection,2016,4(1):80-84.
[6]杨进,文玉梅,李平.非泄漏固定声源干扰下的管网泄漏定位技术研究[J].仪器仪表学报,2012,33(2):248-254.YANG Jin,WEN Yumei,LI Ping.Research on leak location in the presence of non-leakage noises in water distribution pipelines[J].Chinese Journal of Scientific Instrumentation,2012,33(2):248-254.
[7]钱征文,程礼,李应红.利用奇异值分解的信号降噪方法[J].振动、测试与诊断,2011,31(4):459-463.QIAN Zhengwen,CHENG Li,LI Yinghong.Noise reduction method based on singular value decomposition[J].Journal of Vibration,Measurement&Diagnosis,2011,31(4):459-463.
[8]姜洲,丁华平,沈庆宏.具有瞬时较大波动的信号降噪方法研究[J].电子测量技术,2015,38(3):116-119.JIANG Zhou,DING Huaping,SHEN Qinghong.Research of denoising method of signal with temporal large fluctuation[J].Electronic Measurement Technology,2015,38(3):116-119.
[9]郭晨城,文玉梅,李平,等.采用EMD的管道泄漏声信号增强[J].仪器仪表学报,2015,36(6):1397-1405.GUO Chencheng,WEN Yumei,LI Ping,et al.Enhancement of leak signals using EMD in pipeline[J].Chinese Journal of Scientific Instrument,2015,36(6):1397-1405.
[10]贾瑞生,赵同彬,孙红梅,等.基于经验模态分解及独立成分分析的微震信号降噪方法[J].地球物理学报,2015,58(3):1013-1023.JIA Ruisheng,ZHAO Tongbin,SUN Hongmei,et al.Microseismic signal denoising method based on empirical mode decomposition and independent component analysis[J].Chinese Journal of Geophysics,2015,58(3):1013-1023.
[11]HUANG N E,SHEN Z,Long S R,et al.The empirical mode decompositionandthe Hilbert spectrumfornonlinear andnonstationary time series analysis[J].Proceedings:Mathematical,Physical and Engineering Sciences,1998,454(1971):903-995.
[12]PENG J G,WANG W L,FANG M.Hilbert-Huang transform(HHT)based analysis of signal characteristics of vortex flowmeter in oscillatory flow[J].Flow Measurement and Instrumentation,2012,26(4):37-45.
[13]苗晟,王威廉,姚绍文.Hilbert-Huang变换发展历程及其应用[J].电子测量与仪器学报,2014,28(8):812-818.MIAO Sheng,WANG Weilian,YAO Shaowen.Historical development of HTT and its application[J].Journal of Electronic Measurement and Instrumentation,2014,28(8):812-818.
[14]路晓妹,寇文珍,段渭军.基于EMD分解重构的互相关时延估计方法[J].测控技术,2013,32(7):45-48.LU Xiaomei,KOU Wenzhen,DUAN Weijun.Cross-correlation delay estimation method based on EMD decomposition and reconstruction algorithm[J].Measurement&Control Technology,2013,32(7):45-48.
[15]孙洁娣,肖启阳,温江涛,等.局域均值分解分析的管道泄漏孔径识别及定位[J].仪器仪表学报,2014,35(12):2835-2842.SUN Jiedi,XIAO Qiyang,WEN Jiangtao,et al.Pipeline leak aperture classification and location based on local mean decomposition analysis[J].Chinese Journal of Scientific Instrumentation,2014,35(12):2835-2842.
[16]OZEVIN D,HARDING J.Novel leak localization inpressurized pipeline networks using acoustic emission and geometric connectivity[J].International Journal of Pressure Vessels and Piping,2012,92(4):63-69.
[17]OMOLOGO M,SVAIZER P.Use of the crosspower-spectrum phase in acoustic event location[J].IEEE Transactions on Acoustics,Speech and Signal Processing,1997,5(3):288-292.
[18]CHEN J D,BENESTY J,HUANG Y T.Performance of GCC and AMDF based time delay estimation in practical reverberant environments[J].EURASIP Journal on Advances in Signal Processing,2005(1):25-36.
[19]DUFF A L,HAMDI SE,PLANTIER G,et al.Time delay estimation for acoustic source location by means of short-time cross correlation[C]//Sensors,IEEE,2011:1885-1888.
[20]KNAPPP C H,CARTER G C.The generalized correlation method for estimation of time delay[J].IEEE Transactions on Acoustics,Speech and Signal Processing,1976,24(4):320-27.
[21]金中薇,姜明顺,隋青美,等.基于广义互相关时延估计算法的声发射定位技术[J].传感技术学报,2013,26(11):1513-1518.JIN Zhongwei,JIANG Mingshun,SUI Qingmei,et al.Acoustic emission location technique based on generalized cross-correlation time difference estimation algorithm[J].Chinese Journal of Sensors and Actuators,2013,26(11):1513-1518.
[22]ALVANITOPOULOS P F,PAPAVASILEIOU M,ANDREADIS I,et al.Seismic intensity feature construction based on the Hilbert-Huang transform[J].IEEE Transactions on Instrumentation and Measurement,2012:61(2):326-337.
[23]GACI S.The use of wavelet-based denoising techniques to enhance the first-arrivalpicking on seismic traces[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(8):4558-4563.
[24]BEENAMOL M,PRABAVATHY S,MOHANALIN J.Wavelet based seismic signal de-noising using Shannon and Tsallis entropy[J].Computers &Mathematics with Applications,2012,64(11):3580-3593.
[25]CHATLANI N,SORAGHAN JJ.EMD-based filtering(EMDF)of low-frequency noise for speech enhancement[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(4):1158-1166.
[26]王玉静,康守强,张云,等.基于集合经验模态分解敏感固有模态函数选择算法的滚动轴承状态识别方法[J].电子与信息学报,2014,36(3):595-600.WANG Yujing,KANG Shouqiang,ZHANG Yun,et al.Condition recognition method of rolling bearing based on ensemble empirical mode decomposition sensitive intrinsic mode function selection algorithm[J].Journal of Electronics &Information Technology,2014,36(3):595-600.
[27]PENG Z K,TSE P W,CHU F L.A comparison study of improved Hilbert-Huang transform and wavelet transform:Application to fault diagnosis for rolling bearing[J].Mechanical Systems and Signal Processing,2005,19(5):974-988.
[28]孙立瑛,李一博,曲志刚,等.EMD信号分析方法的声发射管道泄漏检测研究[J].振动与冲击,2007,26(10):161-164.SUN Li ying,LI Yibo,QU Zhigang,et al.Study on acoustic emission detection for pipeline leakage based on EMD signal analysis method[J].Journal of Vibration and Shock,2007,26(10):161-164.