基于温度与支座位移相关性的斜拉桥损伤预警
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摘要
为了充分利用桥梁健康监测系统采集的海量数据,健全大跨钢箱梁斜拉桥结构健康评估方法,以辽河特大桥健康监测系统为依托,运用小波分析法对辽河特大桥南北塔为期10个月的支座位移数据进行了滤波与重构.通过大量试验选取神经网络参数,构建了BP神经网络,对重构后的支座位移与环境温度相关性模型进行训练,建立人工神经网络评估模型,并对模型进行检验,检验结果表明:对神经网络预测值与实际值误差取5%的显著性水平作为误差代表值能够有效地反映结构健康状况.
In order to make full use of the massive data collected by bridge health monitoring system and improve the large-span steel box girder cable-stayed bridge structure health assessment method,based on Liaohe super large bridge's health monitoring system,the south and north tower pedestal displacement data of the bridge are filtered and reconstructed for a period of 10 months with wavelet analysis method.Meanwhile through a large number of tests,the parameters of the neural network are selected and BP neural network is established.The pedestal displacement and temperature correlation model is trained after reconstruction,and artificial neural network evaluation model is established and tested.The results show that:selecting 5% of the significance level error as the representative value of the neural network forecasting value and the actual value can effectively reflect the health condition of the structure.
In order to make full use of the massive data collected by bridge health monitoring system and improve the large-span steel box girder cable-stayed bridge structure health assessment method,based on Liaohe super large bridge's health monitoring system,the south and north tower pedestal displacement data of the bridge are filtered and reconstructed for a period of 10 months with wavelet analysis method.Meanwhile through a large number of tests,the parameters of the neural network are selected and BP neural network is established.The pedestal displacement and temperature correlation model is trained after reconstruction,and artificial neural network evaluation model is established and tested.The results show that:selecting 5% of the significance level error as the representative value of the neural network forecasting value and the actual value can effectively reflect the health condition of the structure.
引文
[1]李爱群,丁幼亮,王浩,等.桥梁健康监测海量数据分析与评估:“结构健康监测”研究进展[J].中国科学:技术科学,2012,42(8):972-984.(Li Aiqun,Ding Youliang,Wang Hao,et al.Analysis and Assessment of Bridge Health Monitoring Mass Data:Progress in Research/Development of“Structural Health Monitoring”[J].Scientia Sinica:Technologica,2012,42(8):972-984.)
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[3]Lam H F,Yin T.Application of Two-Dimensional Spatial Wavelet Transform in the Detection of an Obstructed Crack on a Thin Plate[J].Structural Control and Health Monitoring,2012,19(2):260-277.
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[9]郑婷婷,虞庐松.基于神经网络的斜拉索损伤识别研究[J].兰州交通大学学报:自然科学版,2006,25(4):32-34.(Zheng Tingting,Yu Lusong.Study of Cable-Stayed Cable Damage Identification Based on Neural Network[J].Journal of Lanzhou Jiaotong University:Natural Sciences,2006,25(4):32-34.)
[10]李如玮,鲍长春,窦慧晶.基于双正交小波包分解的自适应阈值语音增强[J].仪器仪表学报,2008,29(10):2135-2140.(Li Ruwei,Bao Changchun,Dou Huijing.Speech Enhancement Using Adaptive Threshold Based on BiOrthogonal Wavelet Packet Decomposition[J].Chinese Journal of Scientific Instrument,2008,29(10):2135-2140.)
[11]邓林峰,赵荣珍,龚俊.一种改进的转子振动信号消噪方法研究[J].仪器仪表学报,2011,32(9):1961-1966.(Deng Linfeng,Zhao Rongzhen,Gong Jun.Research on an Improved De-noising Method for Rotor Vibration Signals[J].Chinese Journal of Scientific Instrument,2011,32(9):1961-1966.)
[12]尚鑫,徐岳,马保林,等.基于神经网络的混凝土斜拉桥健康状态评估技术研究[J].武汉理工大学学报,2011,33(8):79-83.(Shang Xin,Xu Yue,Ma Baolin,et al.Health Condition Assessment of Concrete Cable-stayed Bridge Based on ANN[J].Journal of Wuhan University of Technology,2011,33(8):79-83.)
[13]许东,吴铮.基于MATLAB 6.0的系统分析与设计神经网络[M].西安:西安电子科技大学出版社,2002.(Xu Dong,Wu Zheng.System Analysis and Design Based on MATLAB 6.0 Neural Network[M].Xi'an:Xi'an Electronic Sience&Technology University Press,2002.)
[2]Doebling S W,Farrar C R,Prime M B,et al.Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in their Vibration Characteristics:A Literature Review[R].Los Alamos,Los Alamos National Laboratory Report LA-13070-MS,1996.
[3]Lam H F,Yin T.Application of Two-Dimensional Spatial Wavelet Transform in the Detection of an Obstructed Crack on a Thin Plate[J].Structural Control and Health Monitoring,2012,19(2):260-277.
[4]Jung U,Koh B H.Structural Damage Localization Using Wavelet-based Silhouette Statistics[J].Journal of Sound and Vibration,2009,321(3/4/5):590-604.
[5]姜涛,刘邦禹,王会利.桥梁水毁成因分析及防治措施综述[J].沈阳大学学报:自然科学版,2014,26(2):143-147.(Jiang Tao,Liu Bangyu,Wang Huili.Review of Causes and Prevention Measures for Bridge Washout[J].Journal of Shenyang University:Natural Science,2014,26(2):143-147.)
[6]左广超,王会利,秦泗凤.双层钢桁架吊桥锚箱疲劳分析[J].沈阳大学学报:自然科学版,2013,25(3):241-245.(Zuo Guangchao,Wang Huili,Qin Sifeng.Fatigue Analysis of Anchor Box of Double-Layer Steel Truss Suspension Bridge[J].Journal of Shenyang University:Natural Science,2013,25(3):241-245.)
[7]郭健,顾正维,孙炳楠,等.基于小波分析的桥梁健康监测方法[J].工程力学,2006,23(12).129-135.(Guo Jian,Gu Zhengwei,Sun Bingnan,et al.Method of Bridge Health Monitoring Based on Wavelet Analysis[J].Engineering Mechanics,2006,23(12):129-135.)
[8]李忠献,杨晓明,丁阳.应用人工神经网络技术的大型斜拉桥子结构损伤识别研究[J].地震工程与工程振动,2003,23(3):92-99.(Li Zhongxian,Yang Xiaoming,Ding Yang.Research on Substructural Damage identification of Large Cable-Stayed Bridges Using Artificial Neural Networks[J].Earthquake Engineering and Engineering Vibration,2003,23(3):92-99.)
[9]郑婷婷,虞庐松.基于神经网络的斜拉索损伤识别研究[J].兰州交通大学学报:自然科学版,2006,25(4):32-34.(Zheng Tingting,Yu Lusong.Study of Cable-Stayed Cable Damage Identification Based on Neural Network[J].Journal of Lanzhou Jiaotong University:Natural Sciences,2006,25(4):32-34.)
[10]李如玮,鲍长春,窦慧晶.基于双正交小波包分解的自适应阈值语音增强[J].仪器仪表学报,2008,29(10):2135-2140.(Li Ruwei,Bao Changchun,Dou Huijing.Speech Enhancement Using Adaptive Threshold Based on BiOrthogonal Wavelet Packet Decomposition[J].Chinese Journal of Scientific Instrument,2008,29(10):2135-2140.)
[11]邓林峰,赵荣珍,龚俊.一种改进的转子振动信号消噪方法研究[J].仪器仪表学报,2011,32(9):1961-1966.(Deng Linfeng,Zhao Rongzhen,Gong Jun.Research on an Improved De-noising Method for Rotor Vibration Signals[J].Chinese Journal of Scientific Instrument,2011,32(9):1961-1966.)
[12]尚鑫,徐岳,马保林,等.基于神经网络的混凝土斜拉桥健康状态评估技术研究[J].武汉理工大学学报,2011,33(8):79-83.(Shang Xin,Xu Yue,Ma Baolin,et al.Health Condition Assessment of Concrete Cable-stayed Bridge Based on ANN[J].Journal of Wuhan University of Technology,2011,33(8):79-83.)
[13]许东,吴铮.基于MATLAB 6.0的系统分析与设计神经网络[M].西安:西安电子科技大学出版社,2002.(Xu Dong,Wu Zheng.System Analysis and Design Based on MATLAB 6.0 Neural Network[M].Xi'an:Xi'an Electronic Sience&Technology University Press,2002.)
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