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。
Aiming at the settlement of super large bridge for passenger dedicated railway, the calibration method of chaotic behavior was put out. The nonlinear theory and chaotic time sequence method were used, and the settlement prediction model of super large bridge for passenger dedicated railway was set up. Based on embedding theory, the settlement time sequence of super large bridge was reconstructed. Through calculating the values of correlation dimension, Kolmogorov entropy and maximum Lyapunov exponent, the chaotic behavior characteristic of time sequence was verified. The piers A and B of a super large bridge for Shijiazhuang-Wuhan Passenger Dedicated Railway were taken as examples, and the settlements were calculated. Calculation result shows that by using the settlement prediction model, the maximum settlement of pier A is 0. 072 5 mm, and the minimum settlement of pier A is 0. 020 1 mm. The maximum settlement of pier B is 0. 069 7 mm, the minimum settlement of pier B is 0. 030 4 mm, and the errors between prediction values and actual values are less than ±0. 005 0 mm. So the prediction model is effective, and the prediction results meet the technical requirement of bridge settlement deformation monitoring. 1 tab, 6 figs, 26 refs.
出处
《交通运输工程学报》
EI
CSCD
北大核心
2011年第6期31-36,共6页
Journal of Traffic and Transportation Engineering
基金
河北省科技支撑计划项目(09215627D
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)
关键词
铁路客运专线
特大桥
沉降变形
混沌理论
时间序列
预测模型
passenger dedicated railway super large bridge settlement deformation chaotic theory time sequence
prediction model
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。
