利用序贯非线性最小二乘技术识别隔震支座模型的参数
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摘要
为了研究隔震橡胶支座的力学特性,采用简化的Wen模型分析隔震支座的非线性动力行为,并用实验方法测试得到了该模型的力学相关参数。鉴于该模型具有高度的非线性,传统的参数识别方法不再适用,根据非线性系统状态参数估计理论,利用序贯非线性最小二乘方法估计该迟滞模型的非线性参数。该方法具有输入量少、计算精度高、易于实现的优点。通过进行两种地震波激励下的振动台实验,分析结果表明,这种简化的Wen模型能够模拟隔震支座的动态力学行为,而且应用该方法得到的隔震支座的模型参数与实际值比较一致,从而证明了该方法在橡胶隔震支座检测和健康状态评估中的有效性。
Due to the complex nature of the excitation and the inherent dynamics characteristics of restoring force of the base isolation system,the response of rubber bearings subject to strong earthquake are very complicate.Hence it is necessary to describe the restoring force and evaluate the condition of the rubber bearings while they are running.In this paper,the simplied Wen′s model is put forward for analyzing the properties of rubber bearing.Based on vibration data measured from sensors,a new data analysis method,referred to as the sequential non-linear least-square estimation(SNLSE),has been used.This approach has significant advantages over the extended Kalman filter(EKF) approach in terms of the stability and convergence of the solution as well as the computational efforts involved.The accuracy and effectiveness of the new approach has been demonstrated using a kind of rubber bearing(GZN110).This research results can not only be taken as a useful reference for the rubber bearings′ seismic designing, but also provide related theory for the rubber bearings′ health monitoring
Due to the complex nature of the excitation and the inherent dynamics characteristics of restoring force of the base isolation system,the response of rubber bearings subject to strong earthquake are very complicate.Hence it is necessary to describe the restoring force and evaluate the condition of the rubber bearings while they are running.In this paper,the simplied Wen′s model is put forward for analyzing the properties of rubber bearing.Based on vibration data measured from sensors,a new data analysis method,referred to as the sequential non-linear least-square estimation(SNLSE),has been used.This approach has significant advantages over the extended Kalman filter(EKF) approach in terms of the stability and convergence of the solution as well as the computational efforts involved.The accuracy and effectiveness of the new approach has been demonstrated using a kind of rubber bearing(GZN110).This research results can not only be taken as a useful reference for the rubber bearings′ seismic designing, but also provide related theory for the rubber bearings′ health monitoring
引文
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[11]Yin Q,Zhou L.Non-linear structural identificationusing a recursive model reference adaptive algorithm[A].Proceedings of the 5th International Workshopon Structural Health Monitoring[C].Stanford,CA,2005:1 007—1 016.
[12]尹强,周丽.基于模型参考自适应算法的非线性结构损伤识别[J].振动工程学报,2006,19(3):341—345.
[13]Yang J N,Huang H W,Lin S.Sequential non-linearleast-square estimation for damage identification ofstructures[J].International Journal of Non-linearMechanics,2006,41:124—140.
[14]Chen Bo-Jen,Tsai C S,Chung L L,et al.Seismicbehavior of structures isolation with a hybrid systemof rubber bearings[J].Structural Engineering andMechanics,2006,22(6):761—783.
[15]Lin J W,Raimondo B,Smyth A W,et al.On-line i-dentification of nonlinear hysteretic structural systemsusing a variable trace approach[J].J.Earthquake En-gr.Struct.Dyn.,2001,30:1 279—1 303.
[2]Furukawa T,Ito M,Izawa K,et al.System identifi-cation of base-isolation building using seismic response[J].Journal of Engineering Mechanics,ASCE,2005,131(3):268—275.
[3]Doebling S W,Farrar C R,Prime M B.A summaryreview of vibration-based damage identificationmethod[J].The Shock and Vibration Digest,1998,30(2):91—105.
[4]Chang F-K(ed.).Structural health monitoring,DEStech Publ.,Inc.,Lancaster,PA,Proceedings ofthe 4thInternational Workshop on Structural HealthMonitoring[C].Stanford,CA,2003.
[5]Loh C H,Lin C Y,Huang C C.Time domain identi-fication of frames under earthquake loadings[J].AS-CE,Journal of Engineering Mechanics,2000,126(7):693—703.
[6]Yang J N,Lin S.A tracking technique for parametricidentification of nonlinear structures[A].StructuralHealth Monitoring 2003,DEStech Publ.,Inc.,Pro-ceedings of the 4thInternational Workshop on Struc-tural Health Monitoring[C].Stanford,CA,2003:615—622.
[7]Yang J N,Lin S.On-line identification of nonlinearhysteretic structures using an adaptive tracking tech-nique[J].International Journal of Non-linear Mechan-ics,2004,39(9):1 481—1 491.
[8]Hoshiya M,Saito E.Structural identification by ex-tended Kalman filter[J].ASCE,Journal of Engineer-ing Mechanics,1984,110(12):1 757—1 771.
[9]Yang J N,Lin S L,Huang H W,et al.An adaptiveextended Kalman filter for structural damage identifi-cation[J].Journal of Structural Control and HealthMonitoring,2006,13:849—867.
[10]Sato T,Qi K.Adaptive H∞filter:its application tostructural identification[J].ASCE,Journal of Engi-neering Mechanics,1998,124(11):1 233—1 240.
[11]Yin Q,Zhou L.Non-linear structural identificationusing a recursive model reference adaptive algorithm[A].Proceedings of the 5th International Workshopon Structural Health Monitoring[C].Stanford,CA,2005:1 007—1 016.
[12]尹强,周丽.基于模型参考自适应算法的非线性结构损伤识别[J].振动工程学报,2006,19(3):341—345.
[13]Yang J N,Huang H W,Lin S.Sequential non-linearleast-square estimation for damage identification ofstructures[J].International Journal of Non-linearMechanics,2006,41:124—140.
[14]Chen Bo-Jen,Tsai C S,Chung L L,et al.Seismicbehavior of structures isolation with a hybrid systemof rubber bearings[J].Structural Engineering andMechanics,2006,22(6):761—783.
[15]Lin J W,Raimondo B,Smyth A W,et al.On-line i-dentification of nonlinear hysteretic structural systemsusing a variable trace approach[J].J.Earthquake En-gr.Struct.Dyn.,2001,30:1 279—1 303.
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