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铁路客运专线特大桥沉降预测模型

张文胜 崔志伟

张文胜, 崔志伟. 铁路客运专线特大桥沉降预测模型[J]. 交通运输工程学报, 2011, 11(6): 31-36. doi: 10.19818/j.cnki.1671-1637.2011.06.005
引用本文: 张文胜, 崔志伟. 铁路客运专线特大桥沉降预测模型[J]. 交通运输工程学报, 2011, 11(6): 31-36. doi: 10.19818/j.cnki.1671-1637.2011.06.005
ZHANG Wen-sheng, CUI Zhi-wei. Settlement prediction model of super large bridge for passenger dedicated railway[J]. Journal of Traffic and Transportation Engineering, 2011, 11(6): 31-36. doi: 10.19818/j.cnki.1671-1637.2011.06.005
Citation: ZHANG Wen-sheng, CUI Zhi-wei. Settlement prediction model of super large bridge for passenger dedicated railway[J]. Journal of Traffic and Transportation Engineering, 2011, 11(6): 31-36. doi: 10.19818/j.cnki.1671-1637.2011.06.005

铁路客运专线特大桥沉降预测模型

doi: 10.19818/j.cnki.1671-1637.2011.06.005
基金项目: 

河北省科技支撑计划项目 09215627D

河北省科技支撑计划项目 11220904D

河北省交通科技计划项目 J-2010114

石家庄市科技研究与发展计划项目 101131081A

详细信息
    作者简介:

    张文胜(1971-), 男, 宁夏隆德人, 石家庄铁道大学副教授, 工学博士, 从事交通信息技术研究

  • 中图分类号: U443.22

Settlement prediction model of super large bridge for passenger dedicated railway

More Information
    Author Bio:

    ZHANG Wen-sheng (1971-), male, associate professor, PhD, +86-311-87936787, zws163@163.com

  • 摘要: 针对客运专线特大桥沉降提出混沌行为测定方法, 利用非线性理论与混沌时间序列方法, 建立了铁路客运专线特大桥沉降预测模型。采用嵌入定理, 对特大桥沉降时间序列进行重构。通过计算相关维度、Kolmogorov熵、最大Lyapunov指数来测定该时间序列的混沌行为特征, 并以石武客运专线某座特大桥A、B桥墩为例进行实例研究。计算结果表明: 利用沉降预测模型, A桥墩的最大沉降量为0.072 5mm, 最小沉降量为0.020 1mm, B桥墩最大沉降量为0.069 7mm, 最小沉降量为0.030 4mm, 预测值和实际值误差均在±0.005 0mm范围内。可见, 预测模型有效, 预测结果满足桥梁沉降变形监测技术要求。

     

  • 图  1  空间轨迹

    Figure  1.  Space trajectory

    图  2  相关维度

    Figure  2.  Correlation dimension

    图  3  Kolmogorov熵

    Figure  3.  Kolmogorov entropy

    图  4  最大Lyapunov指数

    Figure  4.  Maximum Lyapunov exponent

    图  5  A桥墩沉降量对比

    Figure  5.  Comparison of settlements for pier A

    图  6  B桥墩沉降量对比

    Figure  6.  Comparison of settlements for pier B

    表  1  A桥墩沉降量

    Table  1.   Settlements of pier A

    观测日期 累计天数/d 时间间隔/d 所处位置 本次沉降量/mm 总沉降量/mm 沉降速度/(mm·d-1)
    2009-02-09 0 0 线路右侧小里程 0.00 0.00 0.000
    2009-02-16 7 7 线路右侧小里程 -0.02 -0.02 -0.003
    2009-02-23 14 7 线路右侧小里程 -0.02 -0.04 -0.003
    2009-03-02 21 7 线路右侧小里程 -0.02 -0.06 -0.003
    2009-03-09 28 7 线路右侧小里程 -0.01 -0.07 -0.001
    2009-03-16 35 7 线路右侧小里程 0.03 -0.04 0.003
    2009-03-23 42 7 线路右侧小里程 -0.07 -0.11 -0.014
    2009-03-30 49 7 线路右侧小里程 -0.02 -0.13 -0.003
    2009-04-06 56 7 线路右侧小里程 -0.02 -0.15 -0.003
    2009-04-13 63 7 线路右侧小里程 0.04 -0.11 0.006
    2009-04-20 70 7 线路右侧小里程 -0.07 -0.18 -0.010
    下载: 导出CSV
  • [1] 钟承奎, 牛明飞. 关于无穷维耗散非线性动力系统全局吸引子的存在性[J]. 兰州大学学报: 自然科学版, 2003, 39(2): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-LDZK200302000.htm

    ZHONG Cheng-kui, NIU Ming-fei. On the existence of global attractor for a class of infinite dimensional dissipative nonlinear dynamic systems[J]. Journal of Lanzhou University: Natural Sciences, 2003, 39(2): 1-5. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LDZK200302000.htm
    [2] 李凡, 段建立, 吴敏. 采用混沌变异演化算法在边坡稳定分析中的应用[J]. 合肥工业大学学报: 自然科学版, 2002, 25(1): 109-112. doi: 10.3969/j.issn.1003-5060.2002.01.026

    LI Fan, DUAN Jian-li, WU Min. Application of an evolution program with chaos mutation to the analysis of slope stability[J]. Journal of Hefei University of Technology: Natural Science, 2002, 25(1): 109-112. (in Chinese) doi: 10.3969/j.issn.1003-5060.2002.01.026
    [3] 毕龙珠, 王腾军, 杨海彦, 等. 混沌时间序列在建筑物沉降预测中的应用研究[J]. 测绘信息与工程, 2009, 34(2): 49-51. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG200902024.htm

    BI Long-zhu, WANG Teng-jun, YANG Hai-yan, et al. Application of chaos time series to subsidence forecasting[J]. Journal of Geomatics, 2009, 34(2): 49-51. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG200902024.htm
    [4] 夏银飞, 张季如, 夏元友. 混沌时间序列在路基工后沉降中的应用[J]. 华中科技大学学报: 城市科学版, 2005, 22(3): 89-93. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ200503022.htm

    XIA Yin-fei, ZHANG Ji-ru, XIA Yuan-you. Application of chaotic time series on road foundation's sedimentation[J]. Journal of Huazhong University of Science and Technology: Urban Science Edition, 2005, 22(3): 89-93. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ200503022.htm
    [5] 李峰, 宋建军, 董来启, 等. 基于混沌神经网络理论的城市地面沉降量预测模型[J]. 工程地质学报, 2008, 16(5): 715-720. doi: 10.3969/j.issn.1004-9665.2008.05.026

    LI Feng, SONG Jian-jun, DONG Lai-qi, et al. Chaos neural network theory based model for quantitative prediction of urban ground subsidence[J]. Journal of Engineering Geology, 2008, 16(5): 715-720. (in Chinese) doi: 10.3969/j.issn.1004-9665.2008.05.026
    [6] ROSE B T. Tennessee rockfall management system[D]. Blacksburg: Virginia Polytechnic Institute and State University, 2005.
    [7] GHOLIPOUR A, ARAABI B, LUCAS C. Predicting chaotic time series using neural and neurofuzzy models: a comparative study[J]. Neural Process Letters, 2006, 24(3): 217-239. doi: 10.1007/s11063-006-9021-x
    [8] 陈健. 基坑变形的混沌时间序列分析方法及应用研究[J]. 测绘, 2011, 34(2): 57-59. https://www.cnki.com.cn/Article/CJFDTOTAL-SCCH201102004.htm

    CHEN Jian. Analytic method and application about chaotic foundation pit deformation time-series[J]. Surveying and Mapping, 2011, 34(2): 57-59. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SCCH201102004.htm
    [9] 陈铿, 韩伯棠. 混沌时间序列分析中的相空间重构技术综述[J]. 计算机科学, 2005, 32(4): 67-70. doi: 10.3969/j.issn.1002-137X.2005.04.021

    CHEN Keng, HAN Bo-tang. A survey of state space reconstruction of chaotic time series analysis[J]. Computer Science, 2005, 32(4): 67-70. (in Chinese) doi: 10.3969/j.issn.1002-137X.2005.04.021
    [10] 汤琳, 杨永国. 混沌时间序列分析及应用研究[J]. 武汉理工大学学报, 2010, 32(19): 189-192. https://www.cnki.com.cn/Article/CJFDTOTAL-WHGY201019046.htm

    TANG Lin, YANG Yong-guo. Chaotic time series analysis and its application research[J]. Journal of Wuhan University of Technology, 2010, 32(19): 189-192. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHGY201019046.htm
    [11] 孙海云, 曹庆杰. 混沌时间序列建模及预测[J]. 系统工程理论与实践, 2001, 21(5): 106-113. doi: 10.3321/j.issn:1000-6788.2001.05.017

    SUN Hai-yun, CAO Qing-jie. The modeling and forecasting of chaotic time series[J]. Systems Engineering—Theory and Practice, 2001, 21(5): 106-113. (in Chinese) doi: 10.3321/j.issn:1000-6788.2001.05.017
    [12] 马红光, 李夕海, 王国华, 等. 相空间重构中嵌入维和时间延迟的选择[J]. 西安交通大学学报, 2004, 38(4): 335-338. doi: 10.3321/j.issn:0253-987X.2004.04.002

    MA Hong-guang, LI Xi-hai, WANG Guo-hua, et al. Selection of embedding dimension and delay time in phase space reconstruction[J]. Journal of Xi'an Jiaotong University, 2004, 38(4): 335-338. (in Chinese) doi: 10.3321/j.issn:0253-987X.2004.04.002
    [13] 李红霞, 许士国, 徐向舟, 等. 混沌理论在水文领域中的研究现状及展望[J]. 水文, 2007, 27(6): 1-5, 58. https://www.cnki.com.cn/Article/CJFDTOTAL-SWZZ200706000.htm

    LI Hong-xia, XU Shi-guo, XU Xiang-zhou, et al. Current status and prospect of chaos theory research in hydrology[J]. Journal of China Hydrology, 2007, 27(6): 1-5, 58. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SWZZ200706000.htm
    [14] 高雷阜. 煤与瓦斯突出的混沌动力系统演化规律研究[D]. 阜新: 辽宁工程技术大学, 2006.

    GAO Lei-fu. Study on chaotic dynamical system evolution of coal and gas outburst[D]. Fuxin: Liaoning Technical University, 2006. (in Chinese)
    [15] AYATT N E, CHERIET M, SUEN C Y. Automatic model selection for the optimization of SVM kernels[J]. Pattern Recognition, 2005, 38(10): 1733-1745. doi: 10.1016/j.patcog.2005.03.011
    [16] LEE P H, CHEN Yi, PEI S C, et al. Evidence of the correlation between positive lyapunov exponents and good chaotic random number sequences[J]. Computer Physics Communications, 2004, 160(3): 187-203. doi: 10.1016/j.cpc.2004.04.001
    [17] KIM H S, EYKHOH R, SALAS J D. Nonlinear dynamics, delay times, and embedding windows[J]. Physicra D: Nonlinear Phenomena, 1999, 127(1/2): 48-60.
    [18] KOJIMA C, RAPISARDA P, TAKABA K. Lyapunov stability analysis of higher-order 2-D systems[C]∥IEEE. Pre-ceedings of the 48th IEEE Conference on Decision and Control. Shanghai: IEEE, 2010: 1734-1739.
    [19] 陈益峰, 吕金虎, 周创兵. 基于Lyapunov指数改进算法的边坡位移预测[J]. 岩石力学与工程学报, 2001, 20(5): 671-675. doi: 10.3321/j.issn:1000-6915.2001.05.014

    CHEN Yi-feng, LU Jin-hu, ZHOU Chuang-bing. Prediction of slope displacement by using Lyapunov exponent improved technique[J]. Chinese Journal of Rock Mechanics and Engineering, 2001, 20(5): 671-675. (in Chinese) doi: 10.3321/j.issn:1000-6915.2001.05.014
    [20] 郁俊莉, 王其文. Lyapunov指数混沌特性判定研究[J]. 武汉理工大学学报, 2004, 26(2): 90-92. doi: 10.3321/j.issn:1671-4431.2004.02.028

    YU Jun-li, WANG Qi-wen. Research of judging the chaotic characteristics with the Lyapunov exponents[J]. Journal of Wuhan University of Technology, 2004, 26(2): 90-92. (in Chinese) doi: 10.3321/j.issn:1671-4431.2004.02.028
    [21] 张安兵, 高井祥, 刘新侠, 等. 边坡变形时序非线性判定及混沌预测研究[J]. 中国安全科学学报, 2008, 18(4): 55-60. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK200804009.htm

    ZHANG An-bing, GAO Jing-xiang, LIU Xin-xia, et al. Nonlinear test and chaotic prediction of slope deformation sequences[J]. China Safety Science Journal, 2008, 18(4): 55-60. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK200804009.htm
    [22] 付义祥, 刘志强. 边坡位移的混沌时间序列分析方法及应用研究[J]. 武汉理工大学学报: 交通科学与工程版, 2003, 27(4): 473-476. doi: 10.3963/j.issn.2095-3844.2003.04.013

    FU Yi-xiang, LIU Zhi-qiang. Analytic method and application about chaotic slope deformation destruction time series[J]. Journal of Wuhan University of Technology: Transportation Science and Engineering, 2003, 27(4): 473-476. (in Chinese) doi: 10.3963/j.issn.2095-3844.2003.04.013
    [23] 张勇, 关伟. 基于最大Lyapunov指数的多变量混沌时间序列预测[J]. 物理学报, 2009, 58(2): 756-763. doi: 10.3321/j.issn:1000-3290.2009.02.012

    ZHANG Yong, GUAN Wei. Predication of multivariable chaotic time series based on maximal Lyapunov exponen[J]. Acta Physica Sinica, 2009, 58(2): 756-763. (in Chinese) doi: 10.3321/j.issn:1000-3290.2009.02.012
    [24] 张勇, 关伟. 基于最大李亚普诺夫指数的改进混沌时间序列预测[J]. 信息与控制, 2009, 38(3): 360-364. doi: 10.3969/j.issn.1002-0411.2009.03.019

    ZHANG Yong, GUAN Wei. An improved method for forecasting chaotic time series based on maximum Lyapunov exponent[J]. Information and Control, 2009, 38(3): 360-364. (in Chinese) doi: 10.3969/j.issn.1002-0411.2009.03.019
    [25] 向昌盛, 张林峰. 混沌时间序列预测模型参数同步优化[J]. 计算机工程与应用, 2011, 47(1): 4-7. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201101003.htm

    XIANG Chang-sheng, ZHANG Lin-feng. Simultaneous optimization of chaotic time series prediction model parameters[J]. Computer Engineering and Applications, 2011, 47(1): 4-7. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201101003.htm
    [26] 韩敏, 魏茹. 基于改进典型相关分析的混沌时间序列预测[J]. 大连理工大学学报, 2008, 48(2): 292-297. https://www.cnki.com.cn/Article/CJFDTOTAL-DLLG200802026.htm

    HAN Min, WEI Ru. Chaotic time series prediction based on modified canonical correlation analysis[J]. Journal of Dalian University of Technology, 2008, 48(2): 292-297. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLLG200802026.htm
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  • 收稿日期:  2011-07-23
  • 刊出日期:  2011-12-25

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