环境温度对圆拱形钢结构模态频率的影响研究
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摘要
为研究圆拱形钢结构模态频率在环境温度下的时变特征,本文以潍坊市白浪河摩天轮钢结构为研究对象,首先采用数值模拟和实测数据统计分析的方法揭示其模态频率的温度影响规律,然后采用BP神经网络建立起该结构模态频率与环境温度之间的回归模型,并基于该模型消除环境温度对结构模态频率的影响.结果表明:环境温度主要通过使结构材料的力学性能和结构状态发生改变来影响圆拱钢结构的模态频率;白浪河摩天轮结构模态频率随温度升高而降低,在监测时间内频率最大变化幅度为3.04%;该结构面内振型频率所受温度影响高于面外振型,其中结构状态改变是面内振型频率变化的主要因素;BP神经网络模型可以正确反映模态频率和环境温度之间的变化关系,利用建立的频率-温度回归模型可有效消除环境温度对结构模态频率的影响.
To investigate the time-varying characteristics of the modal frequency of circular arch steel structure under environmental temperature,the White-Wave River Ferris wheel in Weifang is taken as the research object in this study. The temperature influence of the modal frequency is studied by numerical simulation and statistical analysis of actual monitoring data. A regression model of modal frequency-temperature is also established based on the back propagation(BP)neural network technology for eliminating the temperature influence. The results show that temperature affects the modal frequency of structure by changing the mechanical properties and structural state of the structural material. For the White-Wave River Ferris wheel,the modal frequency decreases while the temperature increases,and the maximum change of frequency during the monitoring period is 3.04%. The temperature sensibility of the in-plane vibration mode frequency is higher than that of the out-plane vibration mode. The change of structural state is the main factor of the in-plane modal frequency vibration. The model established by BP neural network can accurately reflect the relationship between modal frequency and temperature. The frequency-temperature regression model can effectively eliminate the temperature influence of structure modal frequency.
To investigate the time-varying characteristics of the modal frequency of circular arch steel structure under environmental temperature,the White-Wave River Ferris wheel in Weifang is taken as the research object in this study. The temperature influence of the modal frequency is studied by numerical simulation and statistical analysis of actual monitoring data. A regression model of modal frequency-temperature is also established based on the back propagation(BP)neural network technology for eliminating the temperature influence. The results show that temperature affects the modal frequency of structure by changing the mechanical properties and structural state of the structural material. For the White-Wave River Ferris wheel,the modal frequency decreases while the temperature increases,and the maximum change of frequency during the monitoring period is 3.04%. The temperature sensibility of the in-plane vibration mode frequency is higher than that of the out-plane vibration mode. The change of structural state is the main factor of the in-plane modal frequency vibration. The model established by BP neural network can accurately reflect the relationship between modal frequency and temperature. The frequency-temperature regression model can effectively eliminate the temperature influence of structure modal frequency.
引文
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[4]Zhang Deyi,Bao Yuequan,Li Hui,et al. Investigation of temperature effects on modal parameters of the China National Aquatics Center[J]. Advances in Structural Engineering,2012,15(7):1139-1153.
[5]Zhou Huafei,Ni Yiqing,Ko J M. Eliminating temperatureeffectinvibration-basedstructuraldamagedetection[J].JournalofEngineeringMechanics, 2011,137(12):785-796.
[6]王立新,朱嘉健,姜慧.珠江黄埔大桥模态频率连续监测中的温度影响II:温度影响及建模分析[J].震灾防御技术,2016,11(2):251-260.Wang Lixin,Zhu Jiajian,Jiang Hui. Temperature influenceinmodalfrequencycontinuousmonitoringof HuangpususpensionbridgeontheZhujiangRiver[J].Technology for Earthquake Disaster Prevention,2016,11(2):251-260(in Chinese).
[7]滕军,卢云军,朱焰煌.大跨空间钢结构模态频率的温度影响监测与分析[J].工程抗震与加固改造,2010,32(3):36-41.TengJun,LuYunjun,ZhuYanhuang.Monitoringand analysisoftemperature’seffectonfrequencyoflarge spanspatialsteelstructure[J].EarthquakeResistantEngineeringandRetrofitting, 2010, 32(3):36-41(in Chinese).
[8]康婷,许金,白应,等.轴向变形对拱自振频率影响的样条有限点法[J].地震工程与工程振动,2012,32(3):41-46.Kang Ting,Xu Jin,Bai Ying,et al. Spline finite point method for analyzing effect of axial deformation on naturalfrequenciesofarch[J].JournalofEarthquakeEngineeringandEngineeringVibration,2012,32(3):41-46(in Chinese).
[9]滕兆春,李万春.变曲率平面拱的自由振动分析[J].兰州理工大学学报,2017,43(2):167-172.Teng Zhaochun,Li Wanchun. Free vibration analysis of plane arches with variable curvature[J]. Journal of LanzhouUniversityofTechnology,2017,43(2):167-172(in Chinese).
[10]张高明,马明,宋涛.潍坊摩天轮节点参数化设计及计算分析[J].建筑结构,2016,46(3):65-69.ZhangGaoming,MaMing,SongTao.Parametricdesign and analysis of the joint in the structure of the WeifangSkyWheel[J].BuildingStructure, 2016,46(3):65-69(in Chinese).
[11] XiaY.LongtermvibrationmonitoringofanRCslab temperatureandhumidityeffect[J].EngineeringStructures,2006,28(3):441-452.
[12]邓扬.基于长期监测数据的大跨桥梁结构状态预警与评估方法及其应用[D].南京:东南大学,2011.Deng Yang. The Method and Application of State Warning and Evaluation of Large Span Bridge Structure Based on Long-Term Monitoring Data[D]. Nanjing:Southeast University,2011(in Chinese).
[13]樊可清,倪一清,高赞明.大跨度桥梁模态频率识别中的温度影响研究[J].中国公路学报, 2006,19(2):68-73.FanKeqing,NiYiqing,GaoZanming.Researchon temperatureinfluencesinlong-spanbridgeeigenfrequenciesidentification[J].ChinaJournalofHighway and Transport,2006,19(2):68-73(in Chinese).