隧道掘进电法超前地质监测信息处理方法研究
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摘要
在盾构机的施工过程中,对掘进面前方的地质条件和可能的地质灾害开展超前地质预报,对隧道的正常施工和顺利贯通发挥举足轻重的作用。盾构机前地质勘探预报,是以探测地下介质电阻率的异常为基础。本课题主要研究隧道掘进检测过程中的信号处理方法,根据检测数据得出挖掘面前方介质电阻率异常体位置参数,即参数的反演和优化处理。
反演最终归结为求目标函数的最小值,从数学角度上看是一个优化问题。但通常来说,大地测量和地球物理模型是强烈非线性的,参数的偏导数非常复杂,计算时间非常长。本课题采用遗传算法来进行地电模型的参数反演,此种算法无需进行复杂的偏导数计算,收敛速度较快。本课题采用遗传算法的十进制(实数)编码和二进制编码这两种编码方式来进行参数的反演运算,对这两种编码方式得到的参数反演结果进行分析比较,选择更适合本课题的编码方式。
本课题以两极装置(直线测量和环状测量)下的地下球状异常体(石头)引起的视电阻率异常为模型,通过遗传算法的反演计算,分析找出更接近真实值的异常体电阻率和大地电阻率的大小,以及球状异常体的半径,地下深度和水平位置。
反演过程中所用的实测数据是在实验室搭建的实验测试平台上经过实地的测量和数据采集得到的。实验测试平台的数据采集系统以LabVIEW为软件设计平台,以发射和接受电极、数据采集模块PMD1608FS和计算机构成。此系统为用户提供友好的人机交互界面,用户可以在前面板上查看采集到的波形和数据以及设置系统的采样率、采样点数和滤波方式、阶次等。
通过对遗传算法的十进制和二进制两种编码方式在二极装置和中间梯度装置的地电模型下得到的参数反演结果的比较,得出十进制编码方式更适合应用在二极装置(直线测量和环状测量)的地电模型的参数反演中。
The advance geological prediction of forward section geological condition and possible geological hazard make decisive factor during tunnel boring machine (TBM) operation. The forecast of geology prospecting during tunnel boring machine working is based on the detection of underground medium resistivity anomaly. The paper mainly researches the signal processing method during detection process of tunnel driving. According to the detection data, it deduces medium resistivity anomalies body positional parameters in front of a heading face. Namely, the method needs parameter inversion and optimization treatment.
The final result of inversion, an optimization method in mathematics, is obtaining the minimum of the objective function. The earth measurement and earth physical model is strong nonlinear, and the partial derivative of parameter is very complex and the calculation time is very long .In the paper, the parameter inversion uses Genetic Algorithm (GA),the algorithm do not need complex partial derivative calculation and the speed of convergence is very fast. GA uses binary and decimal system coding method. Paper analyses and compares these parameters inversion results, which obtain from two kinds of encoding, and choose more suitable one.
The paper uses the model with bipolar device (linear measurement and ring measurement) and underground spheroid (stone) which causes abnormal resistivity. Through GA inverse calculation and analysis, the value nearer practice of abnormal resistivity and earth resistivity, abnormal spheroid radius, underground depth and horizontal position can be found.
Experimental data is obtained by experimental test bench through field measurement. Experimental test bench data collecting software is LabVIEW which consists of emission electrode, receiving electrode, data acquisition module PMD1608FS and computer. This system has a good man-machine interface; the panel can show collected dada, collected wave and set sampling rate, sampling points and filtering methods, the order times of system.
Through the comparing inversion results of two kind coding modes and middle-gradient device in bipolar device model, it concluded that decimal encoding method is more suitable for applications in diode devices (linear measurements and cyclic measurement) parameters inversion of the ground electricity model.
反演最终归结为求目标函数的最小值,从数学角度上看是一个优化问题。但通常来说,大地测量和地球物理模型是强烈非线性的,参数的偏导数非常复杂,计算时间非常长。本课题采用遗传算法来进行地电模型的参数反演,此种算法无需进行复杂的偏导数计算,收敛速度较快。本课题采用遗传算法的十进制(实数)编码和二进制编码这两种编码方式来进行参数的反演运算,对这两种编码方式得到的参数反演结果进行分析比较,选择更适合本课题的编码方式。
本课题以两极装置(直线测量和环状测量)下的地下球状异常体(石头)引起的视电阻率异常为模型,通过遗传算法的反演计算,分析找出更接近真实值的异常体电阻率和大地电阻率的大小,以及球状异常体的半径,地下深度和水平位置。
反演过程中所用的实测数据是在实验室搭建的实验测试平台上经过实地的测量和数据采集得到的。实验测试平台的数据采集系统以LabVIEW为软件设计平台,以发射和接受电极、数据采集模块PMD1608FS和计算机构成。此系统为用户提供友好的人机交互界面,用户可以在前面板上查看采集到的波形和数据以及设置系统的采样率、采样点数和滤波方式、阶次等。
通过对遗传算法的十进制和二进制两种编码方式在二极装置和中间梯度装置的地电模型下得到的参数反演结果的比较,得出十进制编码方式更适合应用在二极装置(直线测量和环状测量)的地电模型的参数反演中。
The advance geological prediction of forward section geological condition and possible geological hazard make decisive factor during tunnel boring machine (TBM) operation. The forecast of geology prospecting during tunnel boring machine working is based on the detection of underground medium resistivity anomaly. The paper mainly researches the signal processing method during detection process of tunnel driving. According to the detection data, it deduces medium resistivity anomalies body positional parameters in front of a heading face. Namely, the method needs parameter inversion and optimization treatment.
The final result of inversion, an optimization method in mathematics, is obtaining the minimum of the objective function. The earth measurement and earth physical model is strong nonlinear, and the partial derivative of parameter is very complex and the calculation time is very long .In the paper, the parameter inversion uses Genetic Algorithm (GA),the algorithm do not need complex partial derivative calculation and the speed of convergence is very fast. GA uses binary and decimal system coding method. Paper analyses and compares these parameters inversion results, which obtain from two kinds of encoding, and choose more suitable one.
The paper uses the model with bipolar device (linear measurement and ring measurement) and underground spheroid (stone) which causes abnormal resistivity. Through GA inverse calculation and analysis, the value nearer practice of abnormal resistivity and earth resistivity, abnormal spheroid radius, underground depth and horizontal position can be found.
Experimental data is obtained by experimental test bench through field measurement. Experimental test bench data collecting software is LabVIEW which consists of emission electrode, receiving electrode, data acquisition module PMD1608FS and computer. This system has a good man-machine interface; the panel can show collected dada, collected wave and set sampling rate, sampling points and filtering methods, the order times of system.
Through the comparing inversion results of two kind coding modes and middle-gradient device in bipolar device model, it concluded that decimal encoding method is more suitable for applications in diode devices (linear measurements and cyclic measurement) parameters inversion of the ground electricity model.
引文
[1]徐则明,黄润秋.深埋特长隧道及其施工地质灾害.成都:西南交通大学出版社,2000.
[2]刘春.关于修建乌鞘岭隧道采用TBM的可行性分析.铁道工程学报,2002,(4):86-90.
[3]张志龙.越岭长大公路隧道地质预报中的关键技术问题研究:(博士学位论文).成都:成都理工大学,2006.
[4]龚固培.超前地质预报在北京八达岭高速公路隧道施工中的应用.世界隧道,2000,(5):38-41.
[5]陈建峰.隧道施工地质超前预报研究技术比较.地下空间,2003,23(l):5-8.
[6]何发亮,李苍松.隧道施工期地质超前预报技术的发展.现代隧道技术,2001,38(3):12-15.
[7]蒋邦远.实用近区磁源瞬变电磁法勘探.北京:地质出版社,1998.
[8]赵永贵,等.隧道地质超前预报研究进展.地球物理学进展,2003,18(3):460-464.
[9]赵永贵.中国工程物理研究的进展与未来.地球物理学进展,2002,17(2):301-304.
[10]刘志刚,刘秀峰.断层参数预测法预报隧道断层.岩石力学与工程学报,2003,22(9):1547-1550.
[11]刘志刚,赵勇.隧道隧洞施工地质技术.北京:中国铁道出版社,2001.
[12]王洪勇,张继奎,李志辉.长大隧道红外辐射测温超前预报含水体方法研究与应用实例分析.物探化探计算技术,2003,25(l):11-17.
[13]钟世航,曹大明.隧道中用陆地声纳法在开挖的岩面或衬砌表面测围岩松弛带深度.岩石力学与工程学报,2005,24(10):1722-1727.
[14]钟世航.陆地声纳法的原理及其在铁路地质勘测和隧道施工中的应用.中国铁道科学,1995,16(4):48-55.
[15]中国科学院地质研究所.军都山隧道快速施工超前地质预报指南.北京:中国铁道出版社,1990.
[16]朱劲.超前地质预报新技术在铜锣山隧道的应用及综合分析研究:(硕士学位论文).成都:成都理工大学,2007.
[17]董劲松.电法勘探数据与解释的可视化方法研究:(硕士学位论文).西安:西安科技大学,2006.
[18]曲海锋,刘志刚,朱合华.隧道信息化施工中综合超前地质预报技术.岩石力学与工程学报,2006,25(6):1246-1251.
[19]朱劲,李天斌,李永林等.BEAM超前地质预报技术在铜锣山隧道的应用.工程地质学报,2007,15(2):258-263.
[20] Kailkonen P. Numerical VLF modeling. Geophysical Prospecting, 1979, 27:815-834.
[21]罗延钟,张桂青.频率域激电法原理.北京:地质出版社,1988.
[22]孙明礼,胡仁喜,崔海蓉等.ANSYS10.0电磁学有限元分析.北京:机械工业出版社,2007.
[23]傅良魁.电法勘探教程.北京:地质出版社,1983.
[24]何继善.双频激电法.北京:高等教育出版社,2006.
[25]李金铭.激发极化法方法技术指南.北京:地质出版社,2004.
[26]黄俊革,阮百尧,王家林等.水下激发极化测深异常特征研究.地球物理学报,2006,49(6):1851-1857.
[27] G V Keller and F C Frischknecht. Electrical methods in geophysical prospecting, PERGAMONPREss, 1986.
[28]席振铢.层状极化介质频率域激发极化效应研究:(硕士学位论文).长沙:中南大学,2002.
[29]赛吉尔.地球物理勘探专辑:第七辑(激发激化法).北京:中国工业出版社,1985.
[30] Rijo L. Modeling of electric and electromagnetic data: [Ph. D. Thesis].Univ. of Utah, 1977.
[31] Barker R and Moore J. The application of time-lapse electrical tomography in groundwater studies. The leading Edge, 1998, 17: 1454-1458.
[32]傅良魁.激发极化法.北京:地质出版社,1982.
[33]傅良魁.电法勘探文集.北京:地质出版社.1986.
[34]罗延钟,史保连,朴化荣等.勘查地球物理勘查地球化学文集(第20集).北京:地质出版社,1996:78-90.
[35]徐斌.盾构机前地质勘探成像方法的研究:(硕士学位论文).沈阳:沈阳工业大学,2009.
[36]郑晓亮.工程电测CT仪系统研制:(硕士学位论文).淮南:安徽理工大学,2005.
[37]雷英杰,张善文,李续武等.MATLAB遗传算法工具箱及其应用.西安:西安电子科技大学出版社,2005:96-117.
[38] Davis L. Handbook of genetic algoriths, Van Nostrand Reinhold New York, 1991.
[39] Holland J H. Adaptation in natural and artificial systems, lst ed., 1975, 2nd ed., Cambridge, MA: Press, 1992.
[40] Rosenberg R S. A computer simulation of a biological population. Unpublished Manuscript, 1966.
[41] De Jong, K A. An analysis of the behavior of a class of genetic adaptive systems, PH.D. Dissertation, University Microfilms, No.76-9381, University of Michigan, Ann Arber, 1975.
[42] Goldberg D E. Simple genetic algorithms and the minimal deceptive problem. In L.Davis (Ed.), Genetic Algorithms and Simulation Annealing, London Pitman, 1987, 74-78.
[43] Bagley J D. The behavior of adaptive systems which employ genetic and correlation algorithms. Dissertation Abstracts international, 1967, 28(12).
[44] Franz D R. Non-linearities in genetic adaptive search, Doctoral Dissertation, Univ. of Mivhigan, Dissertation Abstract, Abstracts Int , 1972, 33(11):5240B-5241B.
[45]王凌.智能优化算法及其应用.北京:清华大学出版社,施普林格出版社,2001:17-62.
[46] Salvatore C, Matteo P. Two-dimensional microwave imaging approach based on a genetic algorithm. IEEE Trans. On Antennas and Propagation, 2000, 48(3): 356-371.
[47]雷英杰,张善文,李续武等.MATLAB遗传算法工具箱及应用.西安:西安电子科技大学,2006,6-31.
[48]赵娟.盾构机前媒质材料与电磁传播特性的研究:(硕士学位论文).沈阳:沈阳工业大学,2009.
[2]刘春.关于修建乌鞘岭隧道采用TBM的可行性分析.铁道工程学报,2002,(4):86-90.
[3]张志龙.越岭长大公路隧道地质预报中的关键技术问题研究:(博士学位论文).成都:成都理工大学,2006.
[4]龚固培.超前地质预报在北京八达岭高速公路隧道施工中的应用.世界隧道,2000,(5):38-41.
[5]陈建峰.隧道施工地质超前预报研究技术比较.地下空间,2003,23(l):5-8.
[6]何发亮,李苍松.隧道施工期地质超前预报技术的发展.现代隧道技术,2001,38(3):12-15.
[7]蒋邦远.实用近区磁源瞬变电磁法勘探.北京:地质出版社,1998.
[8]赵永贵,等.隧道地质超前预报研究进展.地球物理学进展,2003,18(3):460-464.
[9]赵永贵.中国工程物理研究的进展与未来.地球物理学进展,2002,17(2):301-304.
[10]刘志刚,刘秀峰.断层参数预测法预报隧道断层.岩石力学与工程学报,2003,22(9):1547-1550.
[11]刘志刚,赵勇.隧道隧洞施工地质技术.北京:中国铁道出版社,2001.
[12]王洪勇,张继奎,李志辉.长大隧道红外辐射测温超前预报含水体方法研究与应用实例分析.物探化探计算技术,2003,25(l):11-17.
[13]钟世航,曹大明.隧道中用陆地声纳法在开挖的岩面或衬砌表面测围岩松弛带深度.岩石力学与工程学报,2005,24(10):1722-1727.
[14]钟世航.陆地声纳法的原理及其在铁路地质勘测和隧道施工中的应用.中国铁道科学,1995,16(4):48-55.
[15]中国科学院地质研究所.军都山隧道快速施工超前地质预报指南.北京:中国铁道出版社,1990.
[16]朱劲.超前地质预报新技术在铜锣山隧道的应用及综合分析研究:(硕士学位论文).成都:成都理工大学,2007.
[17]董劲松.电法勘探数据与解释的可视化方法研究:(硕士学位论文).西安:西安科技大学,2006.
[18]曲海锋,刘志刚,朱合华.隧道信息化施工中综合超前地质预报技术.岩石力学与工程学报,2006,25(6):1246-1251.
[19]朱劲,李天斌,李永林等.BEAM超前地质预报技术在铜锣山隧道的应用.工程地质学报,2007,15(2):258-263.
[20] Kailkonen P. Numerical VLF modeling. Geophysical Prospecting, 1979, 27:815-834.
[21]罗延钟,张桂青.频率域激电法原理.北京:地质出版社,1988.
[22]孙明礼,胡仁喜,崔海蓉等.ANSYS10.0电磁学有限元分析.北京:机械工业出版社,2007.
[23]傅良魁.电法勘探教程.北京:地质出版社,1983.
[24]何继善.双频激电法.北京:高等教育出版社,2006.
[25]李金铭.激发极化法方法技术指南.北京:地质出版社,2004.
[26]黄俊革,阮百尧,王家林等.水下激发极化测深异常特征研究.地球物理学报,2006,49(6):1851-1857.
[27] G V Keller and F C Frischknecht. Electrical methods in geophysical prospecting, PERGAMONPREss, 1986.
[28]席振铢.层状极化介质频率域激发极化效应研究:(硕士学位论文).长沙:中南大学,2002.
[29]赛吉尔.地球物理勘探专辑:第七辑(激发激化法).北京:中国工业出版社,1985.
[30] Rijo L. Modeling of electric and electromagnetic data: [Ph. D. Thesis].Univ. of Utah, 1977.
[31] Barker R and Moore J. The application of time-lapse electrical tomography in groundwater studies. The leading Edge, 1998, 17: 1454-1458.
[32]傅良魁.激发极化法.北京:地质出版社,1982.
[33]傅良魁.电法勘探文集.北京:地质出版社.1986.
[34]罗延钟,史保连,朴化荣等.勘查地球物理勘查地球化学文集(第20集).北京:地质出版社,1996:78-90.
[35]徐斌.盾构机前地质勘探成像方法的研究:(硕士学位论文).沈阳:沈阳工业大学,2009.
[36]郑晓亮.工程电测CT仪系统研制:(硕士学位论文).淮南:安徽理工大学,2005.
[37]雷英杰,张善文,李续武等.MATLAB遗传算法工具箱及其应用.西安:西安电子科技大学出版社,2005:96-117.
[38] Davis L. Handbook of genetic algoriths, Van Nostrand Reinhold New York, 1991.
[39] Holland J H. Adaptation in natural and artificial systems, lst ed., 1975, 2nd ed., Cambridge, MA: Press, 1992.
[40] Rosenberg R S. A computer simulation of a biological population. Unpublished Manuscript, 1966.
[41] De Jong, K A. An analysis of the behavior of a class of genetic adaptive systems, PH.D. Dissertation, University Microfilms, No.76-9381, University of Michigan, Ann Arber, 1975.
[42] Goldberg D E. Simple genetic algorithms and the minimal deceptive problem. In L.Davis (Ed.), Genetic Algorithms and Simulation Annealing, London Pitman, 1987, 74-78.
[43] Bagley J D. The behavior of adaptive systems which employ genetic and correlation algorithms. Dissertation Abstracts international, 1967, 28(12).
[44] Franz D R. Non-linearities in genetic adaptive search, Doctoral Dissertation, Univ. of Mivhigan, Dissertation Abstract, Abstracts Int , 1972, 33(11):5240B-5241B.
[45]王凌.智能优化算法及其应用.北京:清华大学出版社,施普林格出版社,2001:17-62.
[46] Salvatore C, Matteo P. Two-dimensional microwave imaging approach based on a genetic algorithm. IEEE Trans. On Antennas and Propagation, 2000, 48(3): 356-371.
[47]雷英杰,张善文,李续武等.MATLAB遗传算法工具箱及应用.西安:西安电子科技大学,2006,6-31.
[48]赵娟.盾构机前媒质材料与电磁传播特性的研究:(硕士学位论文).沈阳:沈阳工业大学,2009.
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