输入未知条件下基于自适应广义卡尔曼滤波的结构损伤识别
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摘要
发展一种输入未知条件下的自适应广义卡尔曼滤波(Adaptive Extended Kalman Filter with Unknown Inputs,AEKF-UI)方法,在线复合反演系统参数与未知输入,结合基于改进粒子群优化算法的自适应技术实现系统时变参数追踪,进而识别结构损伤,包括损伤发生的时间、位置和程度。建立基础隔震结构实验模型及理论模型,其中隔震层的非线性动力学特性通过Bouc-Wen模型描述。对基础隔震结构进行振动实验研究,采用刚度元件装置模拟时间、位置和程度不同的结构损伤,基于测得的加速度响应和AEKF-UI方法进行实时系统参数与未知输入的同步反演。研究结果表明:在两种典型地震波激励下,AEKF-UI方法得到的识别值与参考值相一致,验证了该方法在系统辨识中的有效性和准确性。
In order to effectively monitor structure state under the circumstance of system input unavailable,an adaptive extended Kalman filter with unknown inputs approach,which is referred to as AEKF-UI,is developed to identify the structural parameters,such as the stiffness,damping and nonlinear hysteretic parameters,as well as the unknown inputs.Further,a new adaptive technique based on improved particle swarm optimization is proposed to on-line track time-varying parameters,leading to structural damage identification,including the time,location and severity.Vibration experiment study was conducted using a base-isolated building model,nonlinear dynamic characteristics of which were described by the Bouc-Wen model.El Centro and Kobe earthquake excitations were used to drive the model by shaking table.Different damage scenarios were simulated and tested during the experiment,and then the AEFK-UI approach was used to track damages and identify unknown inputs based on the measured acceleration responses.The identification results correlate well with the referenced values.It is concluded that the proposed approach is capable of damage tracking and unknown input identification for the base-isolated structure.
In order to effectively monitor structure state under the circumstance of system input unavailable,an adaptive extended Kalman filter with unknown inputs approach,which is referred to as AEKF-UI,is developed to identify the structural parameters,such as the stiffness,damping and nonlinear hysteretic parameters,as well as the unknown inputs.Further,a new adaptive technique based on improved particle swarm optimization is proposed to on-line track time-varying parameters,leading to structural damage identification,including the time,location and severity.Vibration experiment study was conducted using a base-isolated building model,nonlinear dynamic characteristics of which were described by the Bouc-Wen model.El Centro and Kobe earthquake excitations were used to drive the model by shaking table.Different damage scenarios were simulated and tested during the experiment,and then the AEFK-UI approach was used to track damages and identify unknown inputs based on the measured acceleration responses.The identification results correlate well with the referenced values.It is concluded that the proposed approach is capable of damage tracking and unknown input identification for the base-isolated structure.
引文
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[27]Yin Q,Zhou L,Wang X.Parameter identification of hysteretic rubber-bearing based on sequential nonlinear least-square estimation[J].Journal of Earthquake Engineering and Engineering Vibration,2010,9(3):375—383.
[28]周丽,吴新亚,尹强,等.基于自适应卡尔曼滤波方法的结构损伤识别实验研[J].振动工程学报,2008,21(2):197—202.Zhou L,Wu X Y,Yin Q,et al.Experimental study of an adaptive extended kalman filter for structural damage identification[J].Journal of Vibration Engineering,2008,21(2):197—202.
[29]Ma F,Zhang H,Bockstedte A,et al.Parameter analysis of the differential model of hysteresis[J].ASCE Journal of Applied Mechanics,2004,71(3):342—349.
[30]Chen B J,Tsai C S,Chung L L,et al.Seismic behavior of structures isolation with a hybrid system of rubber bearings[J].Structural Engineering and Mechanics,2006,22(6):761—783.
[31]尹强,周丽.基于EKF方法的橡胶隔震支座参数识别实验研究[J].南京航空航天大学学报,2012,44(1):43—49.Yin Q,Zhou L.Experimental study on parameter identification of non-linear hysteretic rubber-bearing isolators using EKF method[J].Journal of Nanjing University of Aeronautics&Astronautics,2012,44(1):43—49.
[2]Chang F K.Structural health monitoring[A].Proceedings of 8th International Workshop[C].Stanford,USA,2011.
[3]Furukawa T,Ito M,Noori M N.System identification of base-isolated building using seismic response data[J].ASCE Journal of Engineering Mechanics,2005,13(3):268—273.
[4]史东锋,郑敏,申凡,等.工程结构工作模态的子空间辨识方法[J].振动工程学报,2000,13(3):406—412.Shi D F,Zheng M,Shen F,et al.Modal extraction of structure in operating conditions with subspace method[J].Journal of Vibration Engineering,2000,13(3):406—412.
[5]Ibrahim S R.Efficient random decrement computation for identification of ambient responses[A].Proceedings of 19th IMAC[C].Florida,USA,2001,4 359(1):1—6.
[6]续秀忠,华宏星,陈兆能.基于环境激励的模态参数辨识方法综述[J].振动与冲击,2003,23(3):1—5.Xu X Z,Hua H X,Chen Z N.Review of modal identification method based on ambient excitation[J].Journal of Vibration and Shock,2003,23(3):1—5.
[7]Humar J,Bagchi A,Xu H.Performance of vibrationbased techniques for the identification of structural damage[J].Structural Health Monitoring,2006,5(3):215—241.
[8]Kozin F.Estimation of parameters for system driven by white noise excitation[A].Proceedings of INTAM Symposium on Random Vibrations and Reliability[C].Frankfurt Ioder,Germany,1985:163—173.
[9]Toki K,Sato T,Kiyono J.Identification of structural parameter s and input ground motion from response time history[J].JSCE Structural Eng./Earthquake Eng.,1989,6(2):413—421.
[10]Doebling S W,Farrar C R,Prime M B.A summary review of vibration-based damage identification methods[J].The Shock and Vibration Digest,1998,30(2):91—105.
[11]朱广荣,陈国平,张方,等.基于Wilson-θ算法的动载荷识别及影响因素[J].振动、测试与诊断,2012,32(5):709—858.Zhu G R,Chen G P,Zhang F,et al.Dynamic load identification based on wilson-θmethod and influence factors[J].Journal of Vibration,Measurement and Diagnosis,2012,32(5):709—858.
[12]Ling X,Haldar A.Element level system identification with unknown input with rayleigh damping[J].Journal of Engineering Mechanics,2004,130(8):877—885.
[13]Chen J,Li J.Simultaneous identification of structural parameters and input time history from output-only measurements[J].Computational Mechanics,2004,33(5):365—374.
[14]王建有,陈健云,李宗坤,等.输入未知下非比例阻尼结构参数识别方法的研究[J].振动与冲击,2007,26(4):119—125.Wang J Y,Chen J Y,Li Z K,et al.Study on identification method for a structure with non-proportional damping and unknown input[J].Journal of Vibration and Shock,2007,26(4):119—125.
[15]张坤,罗绍湘,段忠东.有限测点下结构参数与基底激励的同步反演[J].振动工程学报,2010,23(1):52—59.Zhang K,Law S S,Duan Z D.Simultaneous identification of structural parameters and support excitation from responses on limited degrees of freedom[J].Journal of Vibration Engineering,2010,23(1):52—59.
[16]李杰,陈隽.未知输入条件下的结构物理参数识别研究[J].计算力学学报,1997,16(1):32—40.Li J,Chen J.Study on identification of structural dynamic parameters with unknown input information[J].Journal of Computational Mechanics,1997,16(1):32—40.
[17]Yang J N,Pan S,Lin S.Least-squares estimation with unknown excitations for damage identification of structures[J].Journal of Engineering Mechanics,2007,133(1):12—21.
[18]Yang J N,Pan S,Huang H.An adaptive extended kalman filter for structural damage identifications II:unknown inputs[J].Structural Control and Health Monitoring,2007,14(3):497—521.
[19]尹强,周丽.基于遗传优化最小二乘算法的结构损伤识别[J].振动与冲击,2010,29(8):155—160.Yin Q,Zhou L.Structural damage identification based on GA optimized least square estimation[J].Journal of Vibration and Shock,2010,29(8):155—160.
[20]Zhou Y,Pei S.An effective adaptive multi-objective particle swarm for multimodal constrained function optimization[J].Journal of Computers,2010,5(8):1144—1 151.
[21]张铃,张钹.佳点集遗传算法[J].计算机学报,2001,24(9):917—922.Zhang L,Zhang B.Good point set based genetic algorithm[J].Chinese Journal of Computer,2001,24(9):917—922.
[22]He Q,Wang L.An effective co-evolutionary particle swarm optimization for constrained engineering design problems[J].Engineering Applications of Artificial Intelligence,2007,20(1):89—99.
[23]李妮,欧阳艾嘉,李肯立.求解约束优化的改进粒子群优化算法[J].计算机应用,2012,32(12):3 319—3 325.Li N,Ouyang A J,Li K L.Improved particle swarm optimization for constrained optimization functions[J].Journal of Computer Applications,2012,32(12):3 319—3 325.
[24]Xia Q,Rao M,Ying Y,et al.Adaptive fading kalman filter with an application[J].Automatica,1994,30(8):1 333—1 338.
[25]Yang J N,Lin S,Huang H,et al.An adaptive extended kalman filter for structural damage identification[J].Structural Control and Health Monitoring,2006,13(4):849—867.
[26]汪新明,周丽.基于振动响应的隔震支座的非线性建模及参数估计[J].振动与冲击,2008,27(1):146—150.Wang X M,Zhou L.Modeling of a rubber bearing and its parameters estimation based of its dynamic response[J].Journal of Vibration and Shock,2008,27(1):146—150.
[27]Yin Q,Zhou L,Wang X.Parameter identification of hysteretic rubber-bearing based on sequential nonlinear least-square estimation[J].Journal of Earthquake Engineering and Engineering Vibration,2010,9(3):375—383.
[28]周丽,吴新亚,尹强,等.基于自适应卡尔曼滤波方法的结构损伤识别实验研[J].振动工程学报,2008,21(2):197—202.Zhou L,Wu X Y,Yin Q,et al.Experimental study of an adaptive extended kalman filter for structural damage identification[J].Journal of Vibration Engineering,2008,21(2):197—202.
[29]Ma F,Zhang H,Bockstedte A,et al.Parameter analysis of the differential model of hysteresis[J].ASCE Journal of Applied Mechanics,2004,71(3):342—349.
[30]Chen B J,Tsai C S,Chung L L,et al.Seismic behavior of structures isolation with a hybrid system of rubber bearings[J].Structural Engineering and Mechanics,2006,22(6):761—783.
[31]尹强,周丽.基于EKF方法的橡胶隔震支座参数识别实验研究[J].南京航空航天大学学报,2012,44(1):43—49.Yin Q,Zhou L.Experimental study on parameter identification of non-linear hysteretic rubber-bearing isolators using EKF method[J].Journal of Nanjing University of Aeronautics&Astronautics,2012,44(1):43—49.
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