A sensitivity-based structural damage identification method with unknown input excitation using transmissibility concept

Zhu, Hongping; Mao, Ling; Weng, Shun

doi:10.1016/j.jsv.2014.08.022

Cited by 58 publications

(26 citation statements)

References 41 publications

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“…Modal parameters including natural frequency, damping ratio, and mode shape are the basic dynamic characteristics of structures that can reflect structural changes . Although these parameters can be obtained by numerical analysis or scaled laboratory experiments, errors from measurement, modeling, and numerical calculation always exist .…”

Section: Introductionmentioning

confidence: 99%

Structural health monitoring of a 250‐m super‐tall building and operational modal analysis using the fast Bayesian FFT method

Zhang

Yang

Xiong

et al. 2019

Struct Control Health Monit

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This paper presents the work on the structural health monitoring design and operational modal analysis of a 250-m super-tall building situated in Shanghai, China. The building is a steel-concrete composite structure with a steel composite frame-concrete core tube system. At the 21st and 36th-38th floors, outrigger trusses and ring-shaped trusses are set to strengthen this structure.Because the height of this structure is overlimited and its lateral stiffness in the vertical direction is nonuniform, a SHM system was designed to monitor the structural condition and evaluate its safety. The SHM system is presented in this paper, and the instrumented equipment includes accelerometers and tilt sensors. The locations of sensors were well arranged so that SHM could be conducted using the least amount of sensors. On the basis of the system, an ambient vibration test was carried out to perform the analysis with four setups designed to investigate the modal parameters in the X and Y directions. The Fast Bayesian FFT method was employed to perform the operational modal analysis. The first 10 modes were identified. The modal parameters obtained by the Bayesian method are studied and discussed, and they are compared with the results obtained by other methods. Long-term monitoring of this super-tall building was also carried out to investigate the change of modal parameters in different stages. The results of this study are expected to provide a reference for model updating, damage detection, and SHM of this high-rise building.

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Section: Introductionmentioning

confidence: 99%

Structural health monitoring of a 250‐m super‐tall building and operational modal analysis using the fast Bayesian FFT method

Zhang

Yang

Xiong

et al. 2019

Struct Control Health Monit

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show abstract

“…The drift is caused by acceleration's insensitivity to any quasi-static component in the input force [21,22]. Although some regularization methods or postsignal processing schemes can be adopted to deal with the drift in the identified results [33][34][35][36], they are not suitable for the real-time identification of coupled state/input/parameter. In [38], a method dealing with joint state and parameter identification was presented.…”

Section: Data Fusion Of Acceleration and Displacement In Egdfmentioning

confidence: 99%

“…However, it has been demonstrated that the conventional GDF approach based on limited number of acceleration measurements is inherently unstable which leads to the so-called spurious low-frequency drift in the estimates of the force and the structural displacement [22]. Although some regularization methods or postsignal processing schemes can be adopted to deal with the drift in the identified results [33][34][35][36], they prohibit the real-time identification of coupled state/input/parameter.…”

Section: Introductionmentioning

confidence: 99%

A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

Wan

Wang

et al. 2018

Shock and Vibration

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In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s). Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

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“…It is often difficult to directly measure external excitations, so it is necessary to study methodologies for the identification of structures under unknown excitations 27 . So far, KF‐UI based approaches have been developed to identify structural states and unknown excitations 28–30 .…”

Section: Introductionmentioning

confidence: 99%

Identification of model‐free hysteretic forces of magnetorheological dampers embedded in buildings under unknown excitations using incomplete structural responses

Lei

Yang

Huang

et al. 2021

Struct Control Health Monit

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Summary Magnetorheological (MR) damper is efficient to mitigate vibration of the structure subject to severe excitations. The identification of nonlinear characteristics of MR damper has attracted increasing attention. However, it is still challenging to identify model‐free hysteresis of MR dampers embedded in structures using only incomplete measurements of structural responses under unknown excitations. In this paper, an identification technique is proposed for this tough task, namely, nonparametric identification of MR nonlinear restoring forces in building structures under unknown excitations. The proposed technique involves identifications in two stages. In the first stage, the identification of linear parameters of bare structure and MR dampers under low‐level unknown excitations is conducted based on the generalized extended Kalman filter with unknown input (GEKF‐UI) by the authors. In the second stage, the hysteretic forces of MR dampers are proposed to be treated as “unknown fictitious forces” to the corresponding linear bare structure identified in the first stage. The generalized Kalman filter with unknown inputs (GKF‐UI) by the authors is adopted to identify all unknown inputs including the “unknown fictitious forces” originated from MR dampers. To demonstrate the proposed technique, some numerical examples are used to identify model‐free hysteresis of single or multi MR dampers with different nonlinear restoring force models in shear frames under unknown external force excitations or unknown seismic excitations, respectively. Furthermore, experimental testing of the identification of model‐free MR damper in a multi‐story shear frame under unknown external excitation is conducted.

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A sensitivity-based structural damage identification method with unknown input excitation using transmissibility concept

Cited by 58 publications

References 41 publications

Structural health monitoring of a 250‐m super‐tall building and operational modal analysis using the fast Bayesian FFT method

Structural health monitoring of a 250‐m super‐tall building and operational modal analysis using the fast Bayesian FFT method

A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

Identification of model‐free hysteretic forces of magnetorheological dampers embedded in buildings under unknown excitations using incomplete structural responses

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