城市隧道临近建筑物超深基坑支护理论与安全控制技术研究
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摘要
在城市用地日益紧张的情况下,经常遇见在已有建筑周边进行深基坑开挖,并施做支护结构。基坑周边土体应力状态由静止土压力状态逐步转向主动土压力状态,导致支护结构向基坑内位移,较大的水平位移最终导致基坑影响范围内的地面出现沉降。这种沉降的大小除了与基坑开挖深度和范围有关外,还与基坑支护类型、周围地质条件和支护结构的变形大小相关。尽管基坑工程事先都进行了精心设计,但由于土体有很多不确定因素,基坑支护有关的理论还不完善,因此展开城市隧道建设临近建筑物超深基坑支护技术研究十分必要。为此,本文结合国家自然科学基金“基于能量渐进耗散的流固耦合作用下土石混合体滑坡演化机制研究”(50878213/E080603),依托重庆南坪城市隧道建设临近建筑物超深基坑工程,在基坑工程监测的基础上,基于模糊神经网络理论,借助极限分析法,结合非线性有限元及随机介质理论,展开城市隧道建设临近建筑物超深基坑支护理论与安全控制技术研究,形成完整的评价体系,确保隧道建设临近建筑物超深基坑施工安全和邻近结构物的稳定。主要工作内容为：
(1)基于模糊神经网络理论,构建基坑支护方法选择的模型,实现基坑支护选择和设计的最优化。
(2)采用极限平衡法对基坑及其支护结构进行稳定性研究,计算其稳定系数；通过使用变位分析对支护结构的变形和内力进行计算,对设计参数进行研究,并根据研究结果对设计进行调整和优化,确保基坑支护结构和周边建筑物的安全。
(3)使用有限元法对不同支护形式下基坑动态施工进行三维数值模拟,得到各级开挖下基坑和基坑支护结构的位移、应力场情况,并比较未采用支护结构下基坑位移、应力场情况,以此来研究基坑对周边建筑物的影响。将计算得到的数据与实际监测的结果进行对比分析。
(4)采用随机介质理论,对基坑工程开挖引起的地表移动与变形的两种因素(疏水以及基坑侧壁失去支撑)的地表移动与变形的随机介质模型加以研究,并将计算数据与工程实测结果加以比较,以保证工程的安全。
(5)结合爆破振动测试,应用小波包理论对实测峰值振速进行分析,与爆破效应的数值模拟结果进行对比分析,得到峰值振速预报值,在城市隧道建设临近建筑物超深基坑支护技术研究与安全性评价的基础上,对复杂周边环境超深基坑开挖扰动效应下的施工方案、施工工艺进行优化,最终达到指导施工的目的。
Increasing tensions in the urban land situation, often encountered in the existing buildings surrounding the deep excavation, and the facilities to do the supporting structure. Slope soil stress state by the state of earth pressure at rest and gradually turned to the active earth pressure state, leading to the supporting structure inside the pit displacement, horizontal displacement of the larger sphere of influence leading to pit the ground subsidence. In addition to this settlement the size of the excavation depth and scope, but also relate to the type of foundation pit, surrounded by geological conditions and the deformation size of the supporting structure. Although the excavation have been carefully designed in advance, but because of the pit there are many uncertain factors in the soil and the theory for excavation is not enough perfect, so the city started construction of the tunnel near the building ultra-deep foundation pit research is necessary. So, this paper is combined whit the National Natural Science Foundation of "Gradual Dissipation of Energy Based on Solid-fluid Interaction under A Mixture of Earth and Rock Slide Mechanism of Evolution, relying on the tunnel construction near Chongqing Nanping city building ultra-deep excavation, whit the excavation monitoring, by the use of limit analysis, basing on Nonlinear Finite Element and Random Medium Theory, settling about tunnel construction near the city building ultra-deep excavation research and safety assessment, a complete evaluation system to ensure that the tunnel construction near the building ultra-deep excavation safety and the stability of adjacent structures. Main tasks are:
(1) On the base of fuzzy and neutral net, the selection model of pit-reinforcement is set up, the optimum design and selection of pit reinforcement will be realized.
(2) Using Limit equilibrium analysis, stochastic medium theory and nonlinear finite element techniques for urban tunnel construction near the building ultra-deep excavation for a comprehensive study of technical and safety evaluation for Nanping station cut to provide ultra-deep excavation technical guidance and security guarantees.
(3) Retaining wall for the piles, anchor piles pull the board rib bolting, gravity retaining wall supporting four kinds of support form had been gone about limit balance analysis and deformation analysis under gradually excavation disturbed. Analysis considered a variety of conditions and the surrounding complex environment. Studies have shown that the higher pit stability factor, better stability, the smaller supporting structure of the internal forces and deformation. A reasonable foundation pit form, protecting surrounding buildings during construction and after the completion of the stability and security.
(4) Nanping station cut for ultra-deep pit in Anchor piles, sheet, plate bolt type three supporting rib form of dynamic simulation, and compared with the actual monitoring analysis, comparison indicates that the model accurately. Anchor pulling piles, piles board two kinds of support form in the excavation process, the supporting structure deformation, mainly in the upper part of the deformation, a small settlement around the pit, a small impact on the surrounding buildings. Rib bolting plate form in the excavation process, the supporting structure deformation, the upper bolt by force, the lower anchor force is small, a small settlement around the pit, a small impact on the surrounding buildings.
(5) Combined with blasting monitor,and wavelet packet theory is applied in peak vibrating velocity,compared with numerical simulation results,and got the point peak vibrating velocity is simulated in this paper. Urban tunnel construction near the ultra-deep foundation pit support in building technology research and safety evaluation on the basis of the complexity of the surrounding environment deep foundation excavation disturbance effect under construction program construction process optimization, and ultimately to guide the construction purpose.
(1)基于模糊神经网络理论,构建基坑支护方法选择的模型,实现基坑支护选择和设计的最优化。
(2)采用极限平衡法对基坑及其支护结构进行稳定性研究,计算其稳定系数；通过使用变位分析对支护结构的变形和内力进行计算,对设计参数进行研究,并根据研究结果对设计进行调整和优化,确保基坑支护结构和周边建筑物的安全。
(3)使用有限元法对不同支护形式下基坑动态施工进行三维数值模拟,得到各级开挖下基坑和基坑支护结构的位移、应力场情况,并比较未采用支护结构下基坑位移、应力场情况,以此来研究基坑对周边建筑物的影响。将计算得到的数据与实际监测的结果进行对比分析。
(4)采用随机介质理论,对基坑工程开挖引起的地表移动与变形的两种因素(疏水以及基坑侧壁失去支撑)的地表移动与变形的随机介质模型加以研究,并将计算数据与工程实测结果加以比较,以保证工程的安全。
(5)结合爆破振动测试,应用小波包理论对实测峰值振速进行分析,与爆破效应的数值模拟结果进行对比分析,得到峰值振速预报值,在城市隧道建设临近建筑物超深基坑支护技术研究与安全性评价的基础上,对复杂周边环境超深基坑开挖扰动效应下的施工方案、施工工艺进行优化,最终达到指导施工的目的。
Increasing tensions in the urban land situation, often encountered in the existing buildings surrounding the deep excavation, and the facilities to do the supporting structure. Slope soil stress state by the state of earth pressure at rest and gradually turned to the active earth pressure state, leading to the supporting structure inside the pit displacement, horizontal displacement of the larger sphere of influence leading to pit the ground subsidence. In addition to this settlement the size of the excavation depth and scope, but also relate to the type of foundation pit, surrounded by geological conditions and the deformation size of the supporting structure. Although the excavation have been carefully designed in advance, but because of the pit there are many uncertain factors in the soil and the theory for excavation is not enough perfect, so the city started construction of the tunnel near the building ultra-deep foundation pit research is necessary. So, this paper is combined whit the National Natural Science Foundation of "Gradual Dissipation of Energy Based on Solid-fluid Interaction under A Mixture of Earth and Rock Slide Mechanism of Evolution, relying on the tunnel construction near Chongqing Nanping city building ultra-deep excavation, whit the excavation monitoring, by the use of limit analysis, basing on Nonlinear Finite Element and Random Medium Theory, settling about tunnel construction near the city building ultra-deep excavation research and safety assessment, a complete evaluation system to ensure that the tunnel construction near the building ultra-deep excavation safety and the stability of adjacent structures. Main tasks are:
(1) On the base of fuzzy and neutral net, the selection model of pit-reinforcement is set up, the optimum design and selection of pit reinforcement will be realized.
(2) Using Limit equilibrium analysis, stochastic medium theory and nonlinear finite element techniques for urban tunnel construction near the building ultra-deep excavation for a comprehensive study of technical and safety evaluation for Nanping station cut to provide ultra-deep excavation technical guidance and security guarantees.
(3) Retaining wall for the piles, anchor piles pull the board rib bolting, gravity retaining wall supporting four kinds of support form had been gone about limit balance analysis and deformation analysis under gradually excavation disturbed. Analysis considered a variety of conditions and the surrounding complex environment. Studies have shown that the higher pit stability factor, better stability, the smaller supporting structure of the internal forces and deformation. A reasonable foundation pit form, protecting surrounding buildings during construction and after the completion of the stability and security.
(4) Nanping station cut for ultra-deep pit in Anchor piles, sheet, plate bolt type three supporting rib form of dynamic simulation, and compared with the actual monitoring analysis, comparison indicates that the model accurately. Anchor pulling piles, piles board two kinds of support form in the excavation process, the supporting structure deformation, mainly in the upper part of the deformation, a small settlement around the pit, a small impact on the surrounding buildings. Rib bolting plate form in the excavation process, the supporting structure deformation, the upper bolt by force, the lower anchor force is small, a small settlement around the pit, a small impact on the surrounding buildings.
(5) Combined with blasting monitor,and wavelet packet theory is applied in peak vibrating velocity,compared with numerical simulation results,and got the point peak vibrating velocity is simulated in this paper. Urban tunnel construction near the ultra-deep foundation pit support in building technology research and safety evaluation on the basis of the complexity of the surrounding environment deep foundation excavation disturbance effect under construction program construction process optimization, and ultimately to guide the construction purpose.
引文
[1]太沙基著.理论土力学[M]徐志英译北京：地质出版社,1960.
[2]Peck R B. Deep excavations and tunneling in soft ground[A]. Proc.7th Int. Conf. SMFE. Mexico City. State of the ArtVolume[C].1969:225-290.
[3]李涛,王超.高承压水地层开挖基坑底板隆起稳定性分析[J].岩土工程学报2009.8：1236-1241.
[4]金亚兵,刘吉波.基坑支护设计中的若干问题探讨[J].岩石力学与工程学报2009,28(z2)：3844-3849
[5]张怀文.临近建筑物有限宽度土体深基坑支护设计与施工[J].岩土工程技术,2008,22(6)：312-315.
[6]黄广龙.坑内土体开挖对工程桩变位影响分析[J].南京工业大学学报,2006,28(3)：6-10.
[7]郭磊,傅鹤林.考虑流固耦合效应的水下隧道岸坡深基坑开挖数值模拟[J].现代隧道技术,2010,47(4)：12-15.
[8]张海林.深基坑开挖对邻近地下管线影响的数值分析[J].岩土工程与基础处理,2010,5(3)：1-5.
[9]郭树学,基坑支护方案可行性进行有限元验证[J].路基工程,2010,4：11-15.
[10]陈新乐.桩基础与深基坑施工的相互作用分析[J].建筑与工程,2009,33：1052-1054.
[11]黄建华.预应力锚杆复合土钉支护三维非线性分析[J].福建工程学院学报,2010,8(4)：326-329.
[12]张胜龙.复杂环境下地铁明挖深基坑的爆破施工[J].施工技术,2010,2：11-15.
[13]王鸿运.深基坑爆破的安全监控与数值模拟[J].工程爆破,2010,16(1)：20-24.
[14]吴亚中.论逆作法现场建筑施工与监控[J].建筑施工,2010,8：12-13.
[15]陈向波,涂安.逆作法施工在深基坑支护工程中的应用[J].安徽建筑2010(4).
[16]徐扬清等.煤岩部武汉设计院(武汉)岩土工程勘察的现状和趋势1998.11.1.
[17]吴恒,张信贵水土作用与土体细观结构研究[J]岩石力学与工程学报 2000,19(2).
[18]何满潮,乾增珍,汪仁和BP神经网络在深基坑工程支护方案优选的应用[J]矿业研究与开发2004,24(2).
[19]阮永芬,杨昆华,王东基于模糊一致矩阵理论的施工方案优选[J]四川建筑科学研究2009,35(4).
[20]谷拴成,侯公羽,陈新年高层建筑深基坑的开挖与支护[J]西安矿业学院学报1999,19(z1).
[21]高文华,杨林德,沈蒲生.基坑变形预测与周围环境保护[J]岩石力学与工程学报2001,20(4).
[22]Litwiniszyn J A model for the initiation of coal-gas outbursts 1985.
[23]刘宝琛.露天开挖及疏水引起的地面沉降及变形[J].煤炭学报,1999,24(1)：39-43.
[24]阳军生,刘宝琛.沉桩引起的邻近地表移动及变形[J].工程勘察,1999.3：1-4.
[25]贺跃光.工程开挖地表移动变形预计的随机介质模型[J].中国锰业,2008,26(4)：22-25.
[26]Clough R W, Bemus K L, Wilson E L. Earthquake Response of Tall Buildings, In:Proc. of 3rd WCEE,1965, (2):68-84.
[27]H.Woode. A New method for quantitative analysiS of dam displacement [C].3rd. International Conference on Computation Methods and Experimental Measurement, PortoCarras, Greece 1987.213-220.
[28]DUNCAN J M, BVIiNE E WONG K S, et al. Strength, stress·strain and bulk modulus parameters for finite element analyses of stresses and movements in soil masses[R]. Report No. UCB/GT/78-02, University of California, Berkeley,1978.
[29]CHANG C Y, DUNCAN J M Nonlinear analysis of stress and strain in soils[J]. Journal of the Soft Mechanics and Foundafions Division, ASCE,1970, (5):1629-1653.
[30]Clough H; George J; Duncan A Psychosis due to non-bacterial thrombotic endocarditis. Age and Ageing 2010,39(2).
[31]Cavalcante, F. A.; Monteiro, F. S.; Martins, I. R. R.; Barbosa, T. P.; Camara, C. A.; Pinto. C.; Vargas, M. D.; da Silva, B. A. Synthetic lapachol derivatives relax guinea-pig ileum by blockade of the voltage-gated calcium channels. Zeitschrift fur Naturforschung. C, A Journal of Biosciences.
[32]宋二祥,娄鹏,陆新征,沈伟某特深基坑支护的非线性三维有限元分析[J]岩土力学2004,25(4).
[33]赵海燕,黄金枝.深基坑支护结构变形的三维有限元分析与模拟[J].上海交通大学学报,2001,35(4)：610-613.
[34]张尚根,华瑞平,刘新宇等.基坑支护结构内力及变形动态分析[J].工程勘察,2000(2)：44-46.
[35]张崇文,何广民,王牲,三维空间桩与土作用的有限层-有限元混合法[J].天津大学学报,1994,27(5)：629-636.
[36]严驰,刘润,刘晓立.将断裂理论引进基坑开挖的有限元分析中[J].中国港湾建设,2000,1：59-63.
[37]刘长文,陈怪凡,李旭东.考虑空间效应的深基坑周围地表沉降分析[J].辽宁工程技术大学学报(自然科学版),2000,19(2)：145-147.
[38]高文华,杨林德.软土深基坑围护结构变形的三维有限元分析[J].工程力学,2000,17(2)：134-141.
[39]邹冰.深基坑支护体系的空间变形性状分析[J].科技通报,2000,16(6)：416-420.
[40]Chih-Chung Chang, Chih-Jen Lin. a library for Support Vector Machines [EB/OL]. http://www.csie.ntu.edu.tw/-cjlin/libsvm.
[41]Burges C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery.1998,2(2):121-167
[42]Burges C. J. C. Simplified Support vector decision rules.13th International Conference on Machine Learning,1996,71-78.
[43]Street W. N., Mangasarain O. L. Improved generalization via tolerant training. Journal of Optimization Theory and Application,1998, 96:259-279.
[44]Scholkopf B., Burges C. J. C., Smola A. J. Advances in Kernel Methods- support vector learning. MIT Press,1999.
[45]Scholkopf B., Mika S., Burges C. J. C. Input space vs. feature space in kernel based methods. Neural Networks, IEEE Transactions on 1999,10(5): 1000-1017.
[46]Smola A. J. Learning with kernel. PhD thesis, Technische University at Berlin,1998.
[47]Smola A. J., Scholkopf B. On a kernel based method for pattern recognition, regression, approximation and operator inversion. Algorithmica,1998,22:211-231.
[48]Mangasarian O. L., Musican D. R. Successive over-relaxation for support vector machines. Technical Report Mathematical Programming. TR 98-18, University of Wisconsin in Madison,1998.
[49]Mangasarian O. L. Generalized support vector machines. In A. J. Smola, P. Bartlett, B. Scholkopf, and C. Schuurmans, editors, Advances in Large Margin Classifiers. MIT Press,1999.
[50]Mangasarian 0. L., Musican D. R. Data discrimination via nonlinear generalized support vector machines, Technical Report Mathematical Programming. TR 99-03, University of Wisconsin in Madison,1999.
[51]Mangasarian 0. L., Musican D. R. Lagrangian support vector machines. Journal of Machine Learning Research, Vol.1,2001,161-177.
[52]Cristianini N., Taylor J. S., Campbell C. Dynamically adapting kernels in support vector machines. In Keans, M.S., Solla, S. A., and Cohn, D. A., editors, Advances in Neural Information Processing Systems,11, MIT Press,1998 (ESANN),1999.
[53]Cristianini N., Campbell C., Taylor J. S. A multiplicative updating algorithm for training support vector machine. In Proceedings of the 6th European Symposium on Artificial Neural Networks.
[54]Watkins C. Dynamic alignment kernels. In Smola, A. J., Bartlett, P., B. Scholkopf & Schuurmans, C. Advances in Large Margin Classifiers. MIT Press,1999.
[55]Smola A. J, Scholkopf B., and Muller K.-R. General cost functions for support vector regression. In T. Downs, M. Frean, and M. Gallagher, editors, Proc. of the Ninth Australian Conf. on Neural Networks, University of Queensland,1998,79-83.
[56]Watkins C. Kernels from matching operations. Technical Report CSD-TR-98-07, Royal Holloway, University of London, Computaer Science Department, July 1999.
[57]Keerthi S. S., Shevade S. K., Bhattacharyya C. and Murthy K. R. K. A Fast Iterative nearest point algorithm for support vector machine classifier design, IEEE Trans. On NN, Vol.11, No.1, Jan 2000,124-136.
[58]Tsuda K. Optimal Hyperplane Classifier with Adaptive Norm:[ETL technical report TR-99-9],1999.
[59]汪培庄,李洪兴.模糊系统理论与模糊计算机[M].北京：科学出版社,1996.92-121.
[60]张吉礼.模糊—神经网络控制原理与工程应用[M].哈尔滨：哈尔滨工业大学出版社,2004.61-66.
[61]赵振宇等.模糊理论和神经网络的基础与应用[M].北京：清华大学出版社,1996.123-148.
[62]李洪兴,汪群,段钦治等.工程模糊数学方法及应用[M].天津：天津科学技术出版社,1993.169-201.
[63]S. C. Lee,E. T. Lee. Fuzzy neurons and automata. In:Proc.4th Princeton Conf Inform. Sci:Syst,1970,381-385.
[64]王士同.神经模糊系统及其应用研究[M].北京：北京航空航天大学出版社,1998.69-82.
[65]林雄.模糊神经网络及其在智能控制中的应用[J].电脑与信息技术,2002,(1)：20-22.
[66]刘增良,刘有才.模糊逻辑与神经网络—理论研究与探索[M].北京：北京航空航天大学出版社,1996.189-217.
[67]Y. Hayashi, J. J. Buckley, E. Czogala. Fuzzy neuroal network with fuzzy signals and weights[J]. Int J Intell Stst,1993, (8):527-537.
[68]Feuring T, Lippe W. The fuzzy neural network approximation lemma[J]. Fuzzy Sets and Systems,1999, (102):227-236.
[69]Ostermark R. A fuzzy neural network algorithm for multigroup classification[J]. Fuzzy Sets and Systems,1999, (105):113-122.
[70]Xieweixin. Fuzzy-neural-network hybrid system and its application [J]. Chinese Journal of Electronics,1995,4(4):78-85.
[71]Chen K H. Amulticlass neural network classifier with fuzzy teaching inputs[J]. Fuzzy Sets and Systems,1997, (91):15-35.
[72]Buckley J J, Hayashi Y.Fuzzy Sets and Systems[J]. Fuzzy neural networks,1994, (66):1-13.
[73]Hudoson, Harrison. A New Approach to Studying Complete Rock Engineering Problems[J]. QJ Engng Geol,1986,25:93-105.
[74]夏元友,李新平,朱瑞赓.基于人工神经网络的边坡稳定性工程地质评价方法[J].岩土力学,1996,17(3)：27-33.
[75]申力.模糊数学在边坡稳定性动态分析中的应用[J].露天采煤技术,1996,(1)：16-19.
[76]Jiao. Y, Hudson. J. A. The Fully-Coupled Model for Rock Engineering Systems[J].RockMech Min Sci Geomech, Abstr,32(5):491-512.
[77]周平根等.长江山峡工程库区不同成因类型平缓斜坡的稳定性评价[J].中国地质灾害与防治学报,1997,(2)：24-32.
[78]张吉军.模糊层次分析法[J].模糊系统与数学,2000,14(2)：80-88.
[79]刘端伶,谭国焕等.岩石边坡稳定性和Fuzzy综合评判法[J].岩石力学与工程学报,1999,18(2)：170-175.
[80]张国良,曾静,柯熙政等.模糊控制及其MATLAB应用[M].西安：西安交通大学出版社,2002.6-22.
[81]杜建凤,宋梅等.模糊神经网络在决策专家系统中的研究与应用[J].系统工程与电子技术,2002,24(2)：45-53.
[82]周伟,张生瑞,高行山.基于模糊理论和神经网络技术的公路网综合评价方法研究[J].中国公路学报,1997,10(4)：76-83.
[83]李琳,程昌银.模糊神经网络故障诊断研究[J].武汉理工大学学报,2002,24(1)：15-18.
[84]D. Hanselman, B. Littlefield. Mastering MATLAB 6(精通MATLAB 6,张航,黄攀译)[M].北京：清华大学出版社,2002.96-148.
[85]郑颖人,赵尚毅,时卫民等.边坡稳定分析的一些进展[J].地下空间,2001,21(4)：213-216.
[86]钱家欢,殷宗泽.土工原理与计算(第二版)[M].北京：水利电力出版社,1994.123-186.
[87]谭新.考虑雨水入渗的边坡稳定性分析[D]：[硕士学位论文].武汉：中国科学院武汉岩土力学研究所,2002.
[88]陈祖煜.土质边坡稳定分析[M].北京：中国水利水电出版社,2003.181-261.
[89]李景勇.有限元法[M].北京：邮电大学出版社,1999.69-78.
[90]魏玉龙.长江三峡水库奉节新城区库岸斜坡稳定性研究[D]：[硕士学位论文].成都：成都理工大学,2002.
[91]赵尚毅,时卫民等.边坡稳定分析的有限元法[J].地下空间,2001,21(5)：450-454.
[92]朱伯芳.有限单元法原理与应用(第二版)[M].北京：中国水利水电出版社,1998.292-527.
[93]徐干成,郑颖人.岩土工程中屈服准则应用的研究[J].岩土工程学报,1990,12(2)：93-99.
[94]郑颖人,赵尚毅等.边坡稳定分析的一些进展[J].地下空间,2001,21(4)：262-338.
[95]张鲁渝,时卫民,郑颖人.平面应变条件下土坡稳定有限元分析[J].岩土工程学报,2002,24(4)：487-591.
[96]郑颖人,龚晓南.岩土塑性力学基础[M].北京：中国建筑工业出版社,1989.69-76.
[97]张汝清,詹先义.非线性有限元分析[M].重庆：重庆大学出版社,1990.123-136.
[98]蒋友谅.非线性有限元法[M].北京：北京工业出版社,1998.79-83.
[99]赵尚毅,郑颖人.用有限元强度折减法求边坡稳定安全系数[J].岩土工程学报,2002,24(3)：343-346.
[100]傅鹤林.块裂岩质边坡稳定性理论分析及应用研究[D]：[博士学位论文].长沙：中南大学,2000.
[101]郑宏,李春光等.求解安全系数的有限元法[J].岩土工程学报,2002,24(5)：626-628.
[102]连镇营,韩国城,孔宪京.强度折减法研究开挖边坡的稳定性[J].岩土工程学报,2001,23(4)：407-411.
[103]史恒通,王成华.土坡有限元稳定分析若干问题探讨[J].岩土力学,2000,21(2)：152-155.
[104]赵尚毅,时卫民等.边坡稳定分析的有限元法[J].地下空间,2001,21(5)：450-454.
[105]邵龙潭,唐洪祥,韩国城.有限元边坡稳定分析方法及其应用[J].计算力学学报,2001,18(1)：81-87.
[106]JGJ120-99建筑基坑支护技术规程[S].北京：中国建筑工业出版社,1999.
[107]刘建航,侯学渊.基坑工程手册[M].北京：中国建筑工业出版社,1997.
[108]董长虹编著.Matlab神经网络与应用[M].北京：国防工业出版社,2005.
[109]袁金荣,赵福勇.基坑变形预测的时间序列分析[J].土木工程学报,2001,34(6)：55-60.
[110]黄修云,曹国安,张清.人工神经元网络在地下工程预测中的应用[J].北方交通大学学报,1998,22(1)：39-43.
[111]傅鹤林,周宁,郭建峰.板裂介质理论在牟珠洞滑坡机理分析中的应 用[J].中南大学学报(自然科学版,2006,37(1))
[112]周宁,傅鹤林,郭建峰.引入修正因子的非等时距时变参数灰色预测模型及应用[J].岩土工程学报,2006,28(6).
[113]申卫兵,张保平.不同煤阶煤岩力学参数测试[J].岩石力学与工程学报,2000(zk).
[114]李云鹏;杨治林,王芝银.顺层边坡岩体结构稳定性位移理论[J].岩石力学与工程学报,2000(06).
[115]李树森;任光明,左三胜.层状结构岩体顺层斜坡失稳机理的力学分析[J].地质灾害与环境保护,1995(02).
[116]傅鹤林,范臻辉,朱汉华.板裂介质围岩中的隧道衬砌与围岩相互作用机理研究[J].公路交通科技,2003(05).
[117]黄洪波,符文熹,尚岳全.层状岩质边坡的屈曲破坏分析[J].山地学报,2003(01).
[118]黄晓华,黄汝祥,刘杰.煤系地层采空区公路路堑高边坡的加固治理[J].重庆交通学院学报,2002(01).
[119]刘小丽,周德培.用弹性板理论分析顺层岩质边坡的失稳[J].岩土力学,2002(02).
[120]刘钧.顺层边坡弯曲破坏的力学分析[J].工程地质学报,1997(04).
[121]蒋刚,林鲁生,刘祖德.边坡变形的灰色预测模型[J].岩土力学,2000(03).
[122]李朝甫,徐迎,谭跃虎.灰色系统理论在滑坡位移信息分析中的运用[J].系统工程理论与实践,2001(02).
[123]张仪萍,俞亚南,张土乔.时变参数预测模型及其在沉降预测中的应用[J].土木工程学报,2003(12).
[124]王金柱.灰色GM(1,1)模型中时变参数估计问题的研究[J].青岛大学学报(工程技术版),2000(02).
[125]刘思峰,邓聚龙.GM(1,1)模型的适用范围[J].系统工程理论与实践,2000(05).
[126]张海洋,刘金果.黄土深基坑支护结构变形优化研究[J].山西建筑,2010(15).
[127]王文.基于时空效应的基坑施工有限元研究[J].陕西理工学院学报(自然科学版),2009(2))
[128]贾金青,陈国周,孟祥波.改进的杆系有限元在预应力锚杆支护法中应用[J].岩土力学,2007(11).
[129]何则干,陈胜宏.加锚节理岩体的复合单元法研究[J].岩土力 学,2007(8).
[130]王良华,沈德浩,谢玉斌.深圳横龙山分岔式隧道喇叭口段预应力锚杆施工技术[J].广西城镇建设,2007(8).
[131]何则干,倪雅茜.赛珠水电站地下厂房工程的复合单元法研究[J].广东水利水电,2007(5).
[132]杨群,邓荣贵,谢立广.深基坑多层预应力锚杆加固技术研究[J].路基工程,2007(3).
[133]张良斌,雷学文.深基坑预应力锚杆结合注浆花管支护的有限元分析[J].土工基础,2007(1).
[134]薛超.周边复杂环境下深基坑的支护与变形监测[J].天津建设科技,2009,19(3).
[135]孙凯,许振刚,刘庭金.深基坑的施工监测及其数值模拟分析[J].岩石力学与工程学报,2004(02).
[136]李建峰,曾永祥,王秀红.桩、锚、喷三结合支护深基坑[J].西安科技大学学报,2005(01).
[137]唐盂雄,赵锡宏.深基坑周围任意点移动变形计算及应用[J].同济大学学报,1996,24(3)：238-244.
[138]庸盂雄,赵锡宏.深基坑周围地表移动及变形分析[J].建筑科学,1996(4)：31-35.
[139]王光遗,劲峰.超大面积深基坑周围护坡桩与场地变形监测[J].建筑技术,2001,31(4)；747-748.
[140]荣耀.公路隧道爆破荷载的计算分析[J].公路交通技术,2005(01)：91-94.
[141]徐学勇.爆破震动信号的小波分析方法研究[D].武汉：武汉理工大学,2006：2-15.
[2]Peck R B. Deep excavations and tunneling in soft ground[A]. Proc.7th Int. Conf. SMFE. Mexico City. State of the ArtVolume[C].1969:225-290.
[3]李涛,王超.高承压水地层开挖基坑底板隆起稳定性分析[J].岩土工程学报2009.8：1236-1241.
[4]金亚兵,刘吉波.基坑支护设计中的若干问题探讨[J].岩石力学与工程学报2009,28(z2)：3844-3849
[5]张怀文.临近建筑物有限宽度土体深基坑支护设计与施工[J].岩土工程技术,2008,22(6)：312-315.
[6]黄广龙.坑内土体开挖对工程桩变位影响分析[J].南京工业大学学报,2006,28(3)：6-10.
[7]郭磊,傅鹤林.考虑流固耦合效应的水下隧道岸坡深基坑开挖数值模拟[J].现代隧道技术,2010,47(4)：12-15.
[8]张海林.深基坑开挖对邻近地下管线影响的数值分析[J].岩土工程与基础处理,2010,5(3)：1-5.
[9]郭树学,基坑支护方案可行性进行有限元验证[J].路基工程,2010,4：11-15.
[10]陈新乐.桩基础与深基坑施工的相互作用分析[J].建筑与工程,2009,33：1052-1054.
[11]黄建华.预应力锚杆复合土钉支护三维非线性分析[J].福建工程学院学报,2010,8(4)：326-329.
[12]张胜龙.复杂环境下地铁明挖深基坑的爆破施工[J].施工技术,2010,2：11-15.
[13]王鸿运.深基坑爆破的安全监控与数值模拟[J].工程爆破,2010,16(1)：20-24.
[14]吴亚中.论逆作法现场建筑施工与监控[J].建筑施工,2010,8：12-13.
[15]陈向波,涂安.逆作法施工在深基坑支护工程中的应用[J].安徽建筑2010(4).
[16]徐扬清等.煤岩部武汉设计院(武汉)岩土工程勘察的现状和趋势1998.11.1.
[17]吴恒,张信贵水土作用与土体细观结构研究[J]岩石力学与工程学报 2000,19(2).
[18]何满潮,乾增珍,汪仁和BP神经网络在深基坑工程支护方案优选的应用[J]矿业研究与开发2004,24(2).
[19]阮永芬,杨昆华,王东基于模糊一致矩阵理论的施工方案优选[J]四川建筑科学研究2009,35(4).
[20]谷拴成,侯公羽,陈新年高层建筑深基坑的开挖与支护[J]西安矿业学院学报1999,19(z1).
[21]高文华,杨林德,沈蒲生.基坑变形预测与周围环境保护[J]岩石力学与工程学报2001,20(4).
[22]Litwiniszyn J A model for the initiation of coal-gas outbursts 1985.
[23]刘宝琛.露天开挖及疏水引起的地面沉降及变形[J].煤炭学报,1999,24(1)：39-43.
[24]阳军生,刘宝琛.沉桩引起的邻近地表移动及变形[J].工程勘察,1999.3：1-4.
[25]贺跃光.工程开挖地表移动变形预计的随机介质模型[J].中国锰业,2008,26(4)：22-25.
[26]Clough R W, Bemus K L, Wilson E L. Earthquake Response of Tall Buildings, In:Proc. of 3rd WCEE,1965, (2):68-84.
[27]H.Woode. A New method for quantitative analysiS of dam displacement [C].3rd. International Conference on Computation Methods and Experimental Measurement, PortoCarras, Greece 1987.213-220.
[28]DUNCAN J M, BVIiNE E WONG K S, et al. Strength, stress·strain and bulk modulus parameters for finite element analyses of stresses and movements in soil masses[R]. Report No. UCB/GT/78-02, University of California, Berkeley,1978.
[29]CHANG C Y, DUNCAN J M Nonlinear analysis of stress and strain in soils[J]. Journal of the Soft Mechanics and Foundafions Division, ASCE,1970, (5):1629-1653.
[30]Clough H; George J; Duncan A Psychosis due to non-bacterial thrombotic endocarditis. Age and Ageing 2010,39(2).
[31]Cavalcante, F. A.; Monteiro, F. S.; Martins, I. R. R.; Barbosa, T. P.; Camara, C. A.; Pinto. C.; Vargas, M. D.; da Silva, B. A. Synthetic lapachol derivatives relax guinea-pig ileum by blockade of the voltage-gated calcium channels. Zeitschrift fur Naturforschung. C, A Journal of Biosciences.
[32]宋二祥,娄鹏,陆新征,沈伟某特深基坑支护的非线性三维有限元分析[J]岩土力学2004,25(4).
[33]赵海燕,黄金枝.深基坑支护结构变形的三维有限元分析与模拟[J].上海交通大学学报,2001,35(4)：610-613.
[34]张尚根,华瑞平,刘新宇等.基坑支护结构内力及变形动态分析[J].工程勘察,2000(2)：44-46.
[35]张崇文,何广民,王牲,三维空间桩与土作用的有限层-有限元混合法[J].天津大学学报,1994,27(5)：629-636.
[36]严驰,刘润,刘晓立.将断裂理论引进基坑开挖的有限元分析中[J].中国港湾建设,2000,1：59-63.
[37]刘长文,陈怪凡,李旭东.考虑空间效应的深基坑周围地表沉降分析[J].辽宁工程技术大学学报(自然科学版),2000,19(2)：145-147.
[38]高文华,杨林德.软土深基坑围护结构变形的三维有限元分析[J].工程力学,2000,17(2)：134-141.
[39]邹冰.深基坑支护体系的空间变形性状分析[J].科技通报,2000,16(6)：416-420.
[40]Chih-Chung Chang, Chih-Jen Lin. a library for Support Vector Machines [EB/OL]. http://www.csie.ntu.edu.tw/-cjlin/libsvm.
[41]Burges C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery.1998,2(2):121-167
[42]Burges C. J. C. Simplified Support vector decision rules.13th International Conference on Machine Learning,1996,71-78.
[43]Street W. N., Mangasarain O. L. Improved generalization via tolerant training. Journal of Optimization Theory and Application,1998, 96:259-279.
[44]Scholkopf B., Burges C. J. C., Smola A. J. Advances in Kernel Methods- support vector learning. MIT Press,1999.
[45]Scholkopf B., Mika S., Burges C. J. C. Input space vs. feature space in kernel based methods. Neural Networks, IEEE Transactions on 1999,10(5): 1000-1017.
[46]Smola A. J. Learning with kernel. PhD thesis, Technische University at Berlin,1998.
[47]Smola A. J., Scholkopf B. On a kernel based method for pattern recognition, regression, approximation and operator inversion. Algorithmica,1998,22:211-231.
[48]Mangasarian O. L., Musican D. R. Successive over-relaxation for support vector machines. Technical Report Mathematical Programming. TR 98-18, University of Wisconsin in Madison,1998.
[49]Mangasarian O. L. Generalized support vector machines. In A. J. Smola, P. Bartlett, B. Scholkopf, and C. Schuurmans, editors, Advances in Large Margin Classifiers. MIT Press,1999.
[50]Mangasarian 0. L., Musican D. R. Data discrimination via nonlinear generalized support vector machines, Technical Report Mathematical Programming. TR 99-03, University of Wisconsin in Madison,1999.
[51]Mangasarian 0. L., Musican D. R. Lagrangian support vector machines. Journal of Machine Learning Research, Vol.1,2001,161-177.
[52]Cristianini N., Taylor J. S., Campbell C. Dynamically adapting kernels in support vector machines. In Keans, M.S., Solla, S. A., and Cohn, D. A., editors, Advances in Neural Information Processing Systems,11, MIT Press,1998 (ESANN),1999.
[53]Cristianini N., Campbell C., Taylor J. S. A multiplicative updating algorithm for training support vector machine. In Proceedings of the 6th European Symposium on Artificial Neural Networks.
[54]Watkins C. Dynamic alignment kernels. In Smola, A. J., Bartlett, P., B. Scholkopf & Schuurmans, C. Advances in Large Margin Classifiers. MIT Press,1999.
[55]Smola A. J, Scholkopf B., and Muller K.-R. General cost functions for support vector regression. In T. Downs, M. Frean, and M. Gallagher, editors, Proc. of the Ninth Australian Conf. on Neural Networks, University of Queensland,1998,79-83.
[56]Watkins C. Kernels from matching operations. Technical Report CSD-TR-98-07, Royal Holloway, University of London, Computaer Science Department, July 1999.
[57]Keerthi S. S., Shevade S. K., Bhattacharyya C. and Murthy K. R. K. A Fast Iterative nearest point algorithm for support vector machine classifier design, IEEE Trans. On NN, Vol.11, No.1, Jan 2000,124-136.
[58]Tsuda K. Optimal Hyperplane Classifier with Adaptive Norm:[ETL technical report TR-99-9],1999.
[59]汪培庄,李洪兴.模糊系统理论与模糊计算机[M].北京：科学出版社,1996.92-121.
[60]张吉礼.模糊—神经网络控制原理与工程应用[M].哈尔滨：哈尔滨工业大学出版社,2004.61-66.
[61]赵振宇等.模糊理论和神经网络的基础与应用[M].北京：清华大学出版社,1996.123-148.
[62]李洪兴,汪群,段钦治等.工程模糊数学方法及应用[M].天津：天津科学技术出版社,1993.169-201.
[63]S. C. Lee,E. T. Lee. Fuzzy neurons and automata. In:Proc.4th Princeton Conf Inform. Sci:Syst,1970,381-385.
[64]王士同.神经模糊系统及其应用研究[M].北京：北京航空航天大学出版社,1998.69-82.
[65]林雄.模糊神经网络及其在智能控制中的应用[J].电脑与信息技术,2002,(1)：20-22.
[66]刘增良,刘有才.模糊逻辑与神经网络—理论研究与探索[M].北京：北京航空航天大学出版社,1996.189-217.
[67]Y. Hayashi, J. J. Buckley, E. Czogala. Fuzzy neuroal network with fuzzy signals and weights[J]. Int J Intell Stst,1993, (8):527-537.
[68]Feuring T, Lippe W. The fuzzy neural network approximation lemma[J]. Fuzzy Sets and Systems,1999, (102):227-236.
[69]Ostermark R. A fuzzy neural network algorithm for multigroup classification[J]. Fuzzy Sets and Systems,1999, (105):113-122.
[70]Xieweixin. Fuzzy-neural-network hybrid system and its application [J]. Chinese Journal of Electronics,1995,4(4):78-85.
[71]Chen K H. Amulticlass neural network classifier with fuzzy teaching inputs[J]. Fuzzy Sets and Systems,1997, (91):15-35.
[72]Buckley J J, Hayashi Y.Fuzzy Sets and Systems[J]. Fuzzy neural networks,1994, (66):1-13.
[73]Hudoson, Harrison. A New Approach to Studying Complete Rock Engineering Problems[J]. QJ Engng Geol,1986,25:93-105.
[74]夏元友,李新平,朱瑞赓.基于人工神经网络的边坡稳定性工程地质评价方法[J].岩土力学,1996,17(3)：27-33.
[75]申力.模糊数学在边坡稳定性动态分析中的应用[J].露天采煤技术,1996,(1)：16-19.
[76]Jiao. Y, Hudson. J. A. The Fully-Coupled Model for Rock Engineering Systems[J].RockMech Min Sci Geomech, Abstr,32(5):491-512.
[77]周平根等.长江山峡工程库区不同成因类型平缓斜坡的稳定性评价[J].中国地质灾害与防治学报,1997,(2)：24-32.
[78]张吉军.模糊层次分析法[J].模糊系统与数学,2000,14(2)：80-88.
[79]刘端伶,谭国焕等.岩石边坡稳定性和Fuzzy综合评判法[J].岩石力学与工程学报,1999,18(2)：170-175.
[80]张国良,曾静,柯熙政等.模糊控制及其MATLAB应用[M].西安：西安交通大学出版社,2002.6-22.
[81]杜建凤,宋梅等.模糊神经网络在决策专家系统中的研究与应用[J].系统工程与电子技术,2002,24(2)：45-53.
[82]周伟,张生瑞,高行山.基于模糊理论和神经网络技术的公路网综合评价方法研究[J].中国公路学报,1997,10(4)：76-83.
[83]李琳,程昌银.模糊神经网络故障诊断研究[J].武汉理工大学学报,2002,24(1)：15-18.
[84]D. Hanselman, B. Littlefield. Mastering MATLAB 6(精通MATLAB 6,张航,黄攀译)[M].北京：清华大学出版社,2002.96-148.
[85]郑颖人,赵尚毅,时卫民等.边坡稳定分析的一些进展[J].地下空间,2001,21(4)：213-216.
[86]钱家欢,殷宗泽.土工原理与计算(第二版)[M].北京：水利电力出版社,1994.123-186.
[87]谭新.考虑雨水入渗的边坡稳定性分析[D]：[硕士学位论文].武汉：中国科学院武汉岩土力学研究所,2002.
[88]陈祖煜.土质边坡稳定分析[M].北京：中国水利水电出版社,2003.181-261.
[89]李景勇.有限元法[M].北京：邮电大学出版社,1999.69-78.
[90]魏玉龙.长江三峡水库奉节新城区库岸斜坡稳定性研究[D]：[硕士学位论文].成都：成都理工大学,2002.
[91]赵尚毅,时卫民等.边坡稳定分析的有限元法[J].地下空间,2001,21(5)：450-454.
[92]朱伯芳.有限单元法原理与应用(第二版)[M].北京：中国水利水电出版社,1998.292-527.
[93]徐干成,郑颖人.岩土工程中屈服准则应用的研究[J].岩土工程学报,1990,12(2)：93-99.
[94]郑颖人,赵尚毅等.边坡稳定分析的一些进展[J].地下空间,2001,21(4)：262-338.
[95]张鲁渝,时卫民,郑颖人.平面应变条件下土坡稳定有限元分析[J].岩土工程学报,2002,24(4)：487-591.
[96]郑颖人,龚晓南.岩土塑性力学基础[M].北京：中国建筑工业出版社,1989.69-76.
[97]张汝清,詹先义.非线性有限元分析[M].重庆：重庆大学出版社,1990.123-136.
[98]蒋友谅.非线性有限元法[M].北京：北京工业出版社,1998.79-83.
[99]赵尚毅,郑颖人.用有限元强度折减法求边坡稳定安全系数[J].岩土工程学报,2002,24(3)：343-346.
[100]傅鹤林.块裂岩质边坡稳定性理论分析及应用研究[D]：[博士学位论文].长沙：中南大学,2000.
[101]郑宏,李春光等.求解安全系数的有限元法[J].岩土工程学报,2002,24(5)：626-628.
[102]连镇营,韩国城,孔宪京.强度折减法研究开挖边坡的稳定性[J].岩土工程学报,2001,23(4)：407-411.
[103]史恒通,王成华.土坡有限元稳定分析若干问题探讨[J].岩土力学,2000,21(2)：152-155.
[104]赵尚毅,时卫民等.边坡稳定分析的有限元法[J].地下空间,2001,21(5)：450-454.
[105]邵龙潭,唐洪祥,韩国城.有限元边坡稳定分析方法及其应用[J].计算力学学报,2001,18(1)：81-87.
[106]JGJ120-99建筑基坑支护技术规程[S].北京：中国建筑工业出版社,1999.
[107]刘建航,侯学渊.基坑工程手册[M].北京：中国建筑工业出版社,1997.
[108]董长虹编著.Matlab神经网络与应用[M].北京：国防工业出版社,2005.
[109]袁金荣,赵福勇.基坑变形预测的时间序列分析[J].土木工程学报,2001,34(6)：55-60.
[110]黄修云,曹国安,张清.人工神经元网络在地下工程预测中的应用[J].北方交通大学学报,1998,22(1)：39-43.
[111]傅鹤林,周宁,郭建峰.板裂介质理论在牟珠洞滑坡机理分析中的应 用[J].中南大学学报(自然科学版,2006,37(1))
[112]周宁,傅鹤林,郭建峰.引入修正因子的非等时距时变参数灰色预测模型及应用[J].岩土工程学报,2006,28(6).
[113]申卫兵,张保平.不同煤阶煤岩力学参数测试[J].岩石力学与工程学报,2000(zk).
[114]李云鹏;杨治林,王芝银.顺层边坡岩体结构稳定性位移理论[J].岩石力学与工程学报,2000(06).
[115]李树森;任光明,左三胜.层状结构岩体顺层斜坡失稳机理的力学分析[J].地质灾害与环境保护,1995(02).
[116]傅鹤林,范臻辉,朱汉华.板裂介质围岩中的隧道衬砌与围岩相互作用机理研究[J].公路交通科技,2003(05).
[117]黄洪波,符文熹,尚岳全.层状岩质边坡的屈曲破坏分析[J].山地学报,2003(01).
[118]黄晓华,黄汝祥,刘杰.煤系地层采空区公路路堑高边坡的加固治理[J].重庆交通学院学报,2002(01).
[119]刘小丽,周德培.用弹性板理论分析顺层岩质边坡的失稳[J].岩土力学,2002(02).
[120]刘钧.顺层边坡弯曲破坏的力学分析[J].工程地质学报,1997(04).
[121]蒋刚,林鲁生,刘祖德.边坡变形的灰色预测模型[J].岩土力学,2000(03).
[122]李朝甫,徐迎,谭跃虎.灰色系统理论在滑坡位移信息分析中的运用[J].系统工程理论与实践,2001(02).
[123]张仪萍,俞亚南,张土乔.时变参数预测模型及其在沉降预测中的应用[J].土木工程学报,2003(12).
[124]王金柱.灰色GM(1,1)模型中时变参数估计问题的研究[J].青岛大学学报(工程技术版),2000(02).
[125]刘思峰,邓聚龙.GM(1,1)模型的适用范围[J].系统工程理论与实践,2000(05).
[126]张海洋,刘金果.黄土深基坑支护结构变形优化研究[J].山西建筑,2010(15).
[127]王文.基于时空效应的基坑施工有限元研究[J].陕西理工学院学报(自然科学版),2009(2))
[128]贾金青,陈国周,孟祥波.改进的杆系有限元在预应力锚杆支护法中应用[J].岩土力学,2007(11).
[129]何则干,陈胜宏.加锚节理岩体的复合单元法研究[J].岩土力 学,2007(8).
[130]王良华,沈德浩,谢玉斌.深圳横龙山分岔式隧道喇叭口段预应力锚杆施工技术[J].广西城镇建设,2007(8).
[131]何则干,倪雅茜.赛珠水电站地下厂房工程的复合单元法研究[J].广东水利水电,2007(5).
[132]杨群,邓荣贵,谢立广.深基坑多层预应力锚杆加固技术研究[J].路基工程,2007(3).
[133]张良斌,雷学文.深基坑预应力锚杆结合注浆花管支护的有限元分析[J].土工基础,2007(1).
[134]薛超.周边复杂环境下深基坑的支护与变形监测[J].天津建设科技,2009,19(3).
[135]孙凯,许振刚,刘庭金.深基坑的施工监测及其数值模拟分析[J].岩石力学与工程学报,2004(02).
[136]李建峰,曾永祥,王秀红.桩、锚、喷三结合支护深基坑[J].西安科技大学学报,2005(01).
[137]唐盂雄,赵锡宏.深基坑周围任意点移动变形计算及应用[J].同济大学学报,1996,24(3)：238-244.
[138]庸盂雄,赵锡宏.深基坑周围地表移动及变形分析[J].建筑科学,1996(4)：31-35.
[139]王光遗,劲峰.超大面积深基坑周围护坡桩与场地变形监测[J].建筑技术,2001,31(4)；747-748.
[140]荣耀.公路隧道爆破荷载的计算分析[J].公路交通技术,2005(01)：91-94.
[141]徐学勇.爆破震动信号的小波分析方法研究[D].武汉：武汉理工大学,2006：2-15.