部分观测下基于子结构的大型结构损伤诊断法
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摘要
该文提出一种适用于大型结构在激励与响应部分观测情况下进行结构损伤诊断的方法。基于有限元模型,大型结构被划分成若干个子结构。相邻子结构间的作用,视为对子结构的"附加未知激励"。依次采用扩展卡尔曼估计和最小二乘估计识别扩展状态向量和未知外部激励,在子结构界面响应未观测的情况下,对各子结构的单元动力参数分别进行识别,并以追踪子结构内单元结构参数的变化,例如单元刚度的退化,对大型结构的局部损伤进行诊断。通过一个较大型的平面桁架桥的损伤识别数值算例,证实了该方法的可行性。与其他方法相比,提出的方法减少了对结构响应观测的要求。
In this paper,a damage detection algorithm is proposed for large size structures under limited input and output measurements.A large size structure is decomposed into small size substructures based on its finite element formulation.The interconnections between adjacent substructures are treated as 'additional unknown inputs' to substructures.By sequentially utilizing the extended Kalman estimator for the extended state vector and a least squares estimation for the unmeasured external inputs,the algorithm can identify element dynamic parameters in each substructure.Structural local damage in the large size structure can be detected by tracking the changes in the identified values of dynamic parameters at an element level,e.g.,the degrading of stiffness parameters.The numerical example of detecting structural damages in a relatively large size plane truss bridge validates the feasibility of the proposed algorithm.Compared with other approaches,the proposed algorithm requests fewer input and output measurements.
In this paper,a damage detection algorithm is proposed for large size structures under limited input and output measurements.A large size structure is decomposed into small size substructures based on its finite element formulation.The interconnections between adjacent substructures are treated as 'additional unknown inputs' to substructures.By sequentially utilizing the extended Kalman estimator for the extended state vector and a least squares estimation for the unmeasured external inputs,the algorithm can identify element dynamic parameters in each substructure.Structural local damage in the large size structure can be detected by tracking the changes in the identified values of dynamic parameters at an element level,e.g.,the degrading of stiffness parameters.The numerical example of detecting structural damages in a relatively large size plane truss bridge validates the feasibility of the proposed algorithm.Compared with other approaches,the proposed algorithm requests fewer input and output measurements.
引文
[1]Meier U,Havaranek B and Motavalli M.(Eds.).In:Proceedings of the 7th international conference onstructural health monitoring of intelligent infrastructures[C].Zurich,2009.
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[4]谢献忠,易伟建.结构物理参数时域识别的子结构方法[J].工程力学,2005,22(5):94―98.Xie Xianzhong,Yi Weijian.A substructure method forparameter estimation in time domain[J].EngineeringMechanics,2005,22(5):94―98.(in Chinese)
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[7]Yang J N,Huang,H W.Substructure damageidentification using a damage tracking technique[R].Proceedings of SPIE’s Conference on sensors and SmartStructures Technologies for Civil,Mechanical,andAerospace Systems,San Diego,CA,USA,2007.
[8]陈健云,王建有.部分输入未知条件下结构参数识别法研究[J].计算力学学报,2005,22(2):149―154.Chen Jianyun,Wang Jianyou.Study on identificationmethod for structural parameter with incomplete inputinformation[J].Chinese Journal of ComputationalMechanics,2005,22(2):149―154.(in Chinese)
[9]Ling X L,Haldar A.Element level system identificationwith unknown input with rayleigh damping[J].Journalof Engineering Mechanics,2004,130(8):877―885.
[10]Kathuda H,Martinez R,Hladar A.Health assessment atlocal level with unknown input excitation[J].StructuralEngineering(ASCE),2005,131(6):956―965.
[11]Yang J N,Pan S W,Huang H W.An adaptive extendedkalman filter for structural damage identification II:Unknown inputs[J].Structural Control and HealthMonitoring,2007,14(3):497―521.
[12]Yang J N,Huang H W,Lin S.Sequential non-linearleast-square estimation for damage identification ofstructures[J].International Journal of NonlinearMechanics,2006,41:124―140.
[2]李杰,陈隽.子结构物理参数识别与输人地震动的复合反演研究[J].振动与冲击,1998,17(1):58―62.Li Jie,Chen Jun.Study on composite inversion of groundmotion and substructure parameter identification[J].Journal of Vibration and Shock,1998,17(1):58―62.(inChinese).
[3]李国强,陆烨.弯曲型结构层间物理参数识别的子结构法[J].世界地震工程,2000,16(1):1―9.Li Guoqiang,Lu Ye.Identification of flexural structuresthrough substructure analysis technique[J].WorldInformation on Earthquake Engineering,2000,16(1):1―9.(in Chinese)
[4]谢献忠,易伟建.结构物理参数时域识别的子结构方法[J].工程力学,2005,22(5):94―98.Xie Xianzhong,Yi Weijian.A substructure method forparameter estimation in time domain[J].EngineeringMechanics,2005,22(5):94―98.(in Chinese)
[5]Koh C G,See L M,Balendra T.Estimation of structuralparameters in time domain:A substructure approach[J].Earthquake Engineering and Structural Dynamics,1991,20(8):787―801.
[6]Koh C G,Hong B,Liaw C Y.Substructural andprogressive structural identification methods[J].Engineering Structures,2003,25:1551―1563.
[7]Yang J N,Huang,H W.Substructure damageidentification using a damage tracking technique[R].Proceedings of SPIE’s Conference on sensors and SmartStructures Technologies for Civil,Mechanical,andAerospace Systems,San Diego,CA,USA,2007.
[8]陈健云,王建有.部分输入未知条件下结构参数识别法研究[J].计算力学学报,2005,22(2):149―154.Chen Jianyun,Wang Jianyou.Study on identificationmethod for structural parameter with incomplete inputinformation[J].Chinese Journal of ComputationalMechanics,2005,22(2):149―154.(in Chinese)
[9]Ling X L,Haldar A.Element level system identificationwith unknown input with rayleigh damping[J].Journalof Engineering Mechanics,2004,130(8):877―885.
[10]Kathuda H,Martinez R,Hladar A.Health assessment atlocal level with unknown input excitation[J].StructuralEngineering(ASCE),2005,131(6):956―965.
[11]Yang J N,Pan S W,Huang H W.An adaptive extendedkalman filter for structural damage identification II:Unknown inputs[J].Structural Control and HealthMonitoring,2007,14(3):497―521.
[12]Yang J N,Huang H W,Lin S.Sequential non-linearleast-square estimation for damage identification ofstructures[J].International Journal of NonlinearMechanics,2006,41:124―140.
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