Average acceleration discrete algorithm for force identification in state space

Ding, Yuehua; Law, S.S.; Wu, Biao; Xu, Guoshan; Lin, Qiang; Jiang, Huaiyuan; Qian, Miao

doi:10.1016/j.engstruct.2013.08.004

Cited by 54 publications

(25 citation statements)

References 16 publications

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“…Al‐Hussein and Haldar proposed a novel unscented KF with unknown input to assess the health of structural systems. Other scholars used a variety of methods to identify external loads, but in each time step, iterations were required, leading to high computational cost …”

Section: Introductionmentioning

confidence: 99%

“…Other scholars used a variety of methods to identify external loads, but in each time step, iterations were required, leading to high computational cost. [27][28][29][30][31][32] The abovementioned approaches are very suitable for load identification when the ground is motionless, such as wind load identification. However, when an earthquake occurs, the ground motions together with the structures and the data measured by SHM system are absolute responses, which mean that the above algorithms are not applicable for this situation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of earthquake ground motion based on limited acceleration measurements of structure using Kalman filtering technique

Luo

Wan

et al. 2019

Struct Control Health Monit

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Summary Identification of earthquake ground motion from structural health monitoring (SHM) data provides a good means to reconstruct seismic loads that are essential for postearthquake safety assessments and disaster simulations of structures. Because the data measured by an SHM system are structural absolute response, they cannot be directly applied to the structural motion equation, which is established in relative coordinate system. As such, this paper originally derives the motion equation in absolute coordinate system and then expands the equation into modal space. In addition, the proposed method allows for identifying earthquake ground motion using incomplete modal information and limited measurements through the standard Kalman filter. Subsequently, a numerical two‐dimensional frame is used to validate the feasibility of the proposed method, and the influences of modal parameters and measurement noise on the identification accuracy are also fully investigated. The results show that the proposed method is sensitive to frequency and measurement noise but insensitive to modal shape and damping ratio. It is also found that the identified ground motion subjected to certain measure noise can still be reliably employed for postseismic response calculations of medium‐ and long‐period structures. Finally, a shaking table test performing on a five‐floor frame further demonstrates the effectiveness and accuracy of the proposed identification algorithm for practical application.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of earthquake ground motion based on limited acceleration measurements of structure using Kalman filtering technique

Luo

Wan

et al. 2019

Struct Control Health Monit

View full text Add to dashboard Cite

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“…However, instead of using the conventional zero‐order holder discretization, in which the unknown input force vector in a sampling period is assumed to be constant, in the existing EKF‐UI approaches, the first‐order holder discretization is used in the proposed GEKF‐UI, i.e., it is assumed that unknown input force vector varies linearly in a sampling period. Then, Equation can be discretized as

Z_{k + 1} = A_{k} Z_{k} + B_{k} f_{k}^{u} + B_{k + 1} f_{k + 1}^{u} + B_{k}^{c} U_{k} + g_{k ∣ k} + w_{k},

in which

A_{k} = e^{G_{k ∣ k} normalΔ t}; g_{k ∣ k} = ((), A_{k} - monospaceI) {({bold-italicG}_{k ∣ k} Δ t)}^{- 1} ([], \overset{g}{true} ((), {\overset{Z}{true}}_{k ∣ k}) - G_{k ∣ k} {\overset{false^}{bold-italicZ}}_{k ∣ k}) normalΔ t,

…”

Section: The Proposed Synthesis Algorithmmentioning

confidence: 99%

Synthesize identification and control for smart structures with time‐varying parameters under unknown earthquake excitation

Lei

Huang

2020

Struct Control Health Monit

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Summary The synthesis of structural identification with vibration control is cost‐effective and beneficial for developing smart building structures. In the past several decades, techniques have been put forward for the combination of structural identification and vibration control. However, it is still a challenging task to synthesize identification and vibration control of time‐varying structures under unknown earthquake excitation. First, structural dynamic responses collected by a structural health monitoring (SHM) system are absolute responses under unknown earthquake excitation, so existing identification approaches for unknown external excitations are not applicable for this situation. Moreover, it is essential to have an efficient algorithm for accurately tracking the various scenarios of time‐varying structural physical parameters with inexpensive computation to ensure the real‐time performance requested by structural vibration control. In this paper, an algorithm is put forward to tackle this challenging problem. It is proposed to treat structural time‐varying effect as “virtual unknown inputs” to the corresponding time‐invariant structure. A generalized extended Kalman filtering with unknown input (GEKF‐UI) is proposed to circumvent the limitations of the existing EKF‐UI approaches. The proposed GEKF‐UI can simultaneously identify structural system, unknown earthquake excitation, and the “virtual unknown inputs” using only partially measured structural absolute responses. Then, the identified structural state is synthesized in real time with the instantaneous optimal control strategy for optimal semiactive control provided by magnetorheological dampers. Therefore, the proposed algorithm can track various structural time‐varying with much less computation, which is more suitable for synthesis with structural control compared with other existing approaches. Some numerical cases of synthesizing identification and vibration control of various type time‐varying structures under unknown earthquake motion are adopted to investigate the feasibilities of the proposed algorithm.

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“…Law and Yong [20] used the state space method to identify the interface forces and the external forces for structural condition assessment. Recently, a novel approach of force identification based on average acceleration discrete algorithm was presented in the state space [21]. Although the state space method is not sensitive to the initial values and have no cumulative errors produced by the previous time step compared with many other time domain force identification method, it still has an obvious disadvantage.…”

Section: Introductionmentioning

confidence: 99%

A novel state space method for force identification based on the Galerkin weak formulation

Wang

Wan

Wang

et al. 2015

Computers & Structures

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Average acceleration discrete algorithm for force identification in state space

Cited by 54 publications

References 16 publications

Identification of earthquake ground motion based on limited acceleration measurements of structure using Kalman filtering technique

Identification of earthquake ground motion based on limited acceleration measurements of structure using Kalman filtering technique

Synthesize identification and control for smart structures with time‐varying parameters under unknown earthquake excitation

A novel state space method for force identification based on the Galerkin weak formulation

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