变权组合预测模型在郑西高铁某路桥过渡段不均匀沉降监测中的应用
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摘要
路桥过渡段不均匀沉降是造成高速铁路行车安全重要隐患之一.以郑州-西安高速铁路某路桥过渡段为例,在分析不均匀沉降机理基础上基于灰色GM(1,1)模型和二次曲线趋势外推法建立了变权组合预测模型,并利用针对该过渡段设计的监测方案所获取的沉降监测数据进行验证.结果表明:该模型在后5个监测期内,D_1、D_2监测点实测值和预测值最大差值是0.20 mm,预测误差平方最大值为0.048,满足预测精度要求.未来3年内监测点D_1、D_2累计沉降量分别为7.55 mm和15.31 mm,在无其他特殊因素作用下,该路桥过渡段的不均匀沉降将继续保持稳定状态,不会影响行车安全.
The uneven settlement of road and bridge itd is one of the important hidden dangers of high-speed railway traffic safety. Taking an itd of a road and bridge of Zhengzhou-Xi'an high-speed railway as an example,this paper establishes a variable weight combination prediction model based on gray GM(1,1)model and conic trend extrapolation method on the basis of analyzing the uneven settlement mechanism,and verifies the settlement monitoring data obtained from the monitoring scheme designed for the itd. The results show that in the latter five monitoring periods,the maximum difference between the measured values and the predicted values of D_1 and D_2 monitoring points is 0.20 mm,and the maximum square error of the prediction is 0.048,meeting the prediction accuracy requirements. In the next three years,the cumulative settlement of monitoring points D_1 and D_2 is 7.55 mand 15.31 mm,respectively. Under the action of no other special factors,the uneven settlement of the road and bridge itd will continue to maintain a stable state and will not affect traffic safety.
The uneven settlement of road and bridge itd is one of the important hidden dangers of high-speed railway traffic safety. Taking an itd of a road and bridge of Zhengzhou-Xi'an high-speed railway as an example,this paper establishes a variable weight combination prediction model based on gray GM(1,1)model and conic trend extrapolation method on the basis of analyzing the uneven settlement mechanism,and verifies the settlement monitoring data obtained from the monitoring scheme designed for the itd. The results show that in the latter five monitoring periods,the maximum difference between the measured values and the predicted values of D_1 and D_2 monitoring points is 0.20 mm,and the maximum square error of the prediction is 0.048,meeting the prediction accuracy requirements. In the next three years,the cumulative settlement of monitoring points D_1 and D_2 is 7.55 mand 15.31 mm,respectively. Under the action of no other special factors,the uneven settlement of the road and bridge itd will continue to maintain a stable state and will not affect traffic safety.
引文
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[15]葛苗苗,李宁,张炜,等.黄土高填方沉降规律分析及工后沉降反演预测[J].岩石力学与工程学报,2017,36(3):745-753.
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[17]谢朋朋,黄腾,刘阳.变权组合预测模型在大坝沉降监测中的应用[J].测绘工程,2015,24(4):74-76.
[18]YIN S,LIU L,HOU J.A multivariate statistical combination forecasting method for product quality evaluation[J].Information Sciences,2016(355):229-236.
[2]LIU H,NIU F J,NIU Y H,et al.Study on thermal regime of roadbed-culvert transition section along a high speed railway in seasonally frozen regions[J].Cold Regions Science and Technology,2014(106):216-231.
[3]李欣.郑西高铁湿陷黄土路基沉降监测及预警系统研究[D].西安:长安大学,2012.
[4]谭衢霖,魏健,胡吉平.基于小波神经网络的建筑工程沉降变形预测[J].应用基础与工程科学学报,2015,23(3):629-636.
[5]肖衡林,李丽华,郭小川,等.山区高填方路堤沉降预测方法[J].应用基础与工程科学学报,2015,23(1):154-161.
[6]SUN J G,DUAN S J,CUI C X.Dynamic analysis of the track on roadbed-bridge transition section and research on its reasonable length[J].Procedia-Social and Behavioral Sciences,2013,96(6):2267-2273.
[7]庄妍,张永攀,袁江.预应力管桩加固有轨电车路桥过渡段现场监测研究[J].河南科学,2016,34(11):1869-1874.
[8]YAO K,YAO Z Y,SONG X G.Settlement evaluation of soft ground reinforced by deep mixed columns[J].International Journal of Pavement Research and Technology,2016,9(6):460-465.
[9]张玉芝,杜彦良,孙宝臣.季节性冻土地区高速铁路路桥过渡段路基变形特征分析[J].中国铁道科学,2016,37(1):39-44.
[10]ZHOU J,ZHENG M,WANG C,et al.Dynamic response analysis of road-bridge transition section without slab[J].International Journal of Pavement Research and Technology,2017,10(6):526-535.
[11]王安辉,丁选明,章定文.在役高速公路软基不均匀沉降病害注浆处治技术[J].东南大学学报(自然科学版),2017,47(2):397-403.
[12]王宝,易领兵,于海洋,等.地铁盾构施工对郑西高铁跨绕城高速特大桥影响的数值分析及对地表的影响[J].施工技术,2016,45(增):443-446.
[13]杨玉生,李靖,邢义川,等.压实黄土增湿变形性质及其影响因素试验研究[J].岩土工程学报,2017,39(4):626-635.
[14]包卫星,郭小龙,杨万精.干旱荒漠区天然砂砾路基填料压实特性分析[J].中国公路学报,2017,30(2):18-24.
[15]葛苗苗,李宁,张炜,等.黄土高填方沉降规律分析及工后沉降反演预测[J].岩石力学与工程学报,2017,36(3):745-753.
[16]MA X,HU Y S,LIU Z B.A novel kernel regularized nonhomogeneous grey model and its applications[J].Commun Nonlinear Sci Numer Simulat,2017(48):51-62.
[17]谢朋朋,黄腾,刘阳.变权组合预测模型在大坝沉降监测中的应用[J].测绘工程,2015,24(4):74-76.
[18]YIN S,LIU L,HOU J.A multivariate statistical combination forecasting method for product quality evaluation[J].Information Sciences,2016(355):229-236.