Search

Summary: Knowledge of the camera motion is important in the applications of structural dynamic response measurement using a vision‐based approach because in most of the field measurements, such motion can be non‐trivial and the accuracy of dynamic response measurements is strongly affected by the camera motion. This paper presents a new framework for camera motion estimation and vision‐based displacement measurement, which greatly lowers the barriers to the application of generally positioned cameras from strictly stationary cameras. The contributions in this paper are twofold. First, camera motion as well as reconstructed structural displacement are calculated based on reference planar structures visible in a given scene. In this case, a homography is more effective at describing view changes and planar geometric constraints can be incorporated early in the reconstruction process, thereby improving the quality and effectiveness of the estimates. The second contribution is that the homography of the planar structure is estimated by a newly proposed tracking algorithm that combines RANSAC algorithm and Efficient Second‐order Minimization (ESM) technique, which refines the final estimates to sub‐pixel accuracy and avoids tracking drift and non‐smoothness effectively. Experimental results indicate that the quality of the camera motion estimation and displacement reconstruction can be significantly improved by the judgmatical use of the proposed algorithm for planar structure homography estimation. Furthermore, nonlinear structural system identification is carried out to additionally verify the proposed algorithm using unscented Kalman filter. [ABSTRACT FROM AUTHOR]

• A new hysteretic loop identification framework is developed upon restoring force reconstruction and the Kalman filter. • It does not require the a priori knowledge on hysteretic models. • It transforms nonlinear hysteretic identification into more efficient linear system estimation problem. • Augmentation of the restoring forces as state variables is shown to act as the role of Tikhonov regularization. Identifying the local nonlinear hysteretic behaviors in structures arises as an important issue in structural health monitoring. This paper develops a new hysteresis identification framework where rather than identifying the hysteretic parameters, the restoring forces are reconstructed so as to identify the hysteretic loops. Under this new framework, there is no need to get a priori knowledge on the hysteretic models, enabling a wider range of applications, and the involved system equation is linear with unknown restoring forces, tending to be more efficient. Then, the Kalman filter is adopted for real-time restoring force reconstruction because the Kalman filter is celebrated for its efficiency, effectiveness and reliability in linear system estimation with noisy measured data. In doing so, the restoring forces are additionally augmented as state variables and such augmentation is shown to act as the role of Tikhonov regularization, by which the proper covariance of the augmentation as the regularization parameter is selected via the L-curve method. Numerical examples are presented and an experimental test is conducted to verify the effectiveness and robustness of the proposed real-time hysteresis identification method. [ABSTRACT FROM AUTHOR]

A series of impulse-type inputs has been extensively used to evaluate the critical response of an elastoplastic structure subjected to diverse types of pulse-type inputs, including a near-fault ground motion. In this paper, we consider the critical double-impulse input for a single-degree-of-freedom elastic–perfectly plastic structure, and study effects of structural uncertainties. When the natural frequency (or, equivalently, the stiffness) is fixed, the critical response of the structure does not necessarily decrease as the yield deformation (or, equivalently, the yield force) increases. As the first contribution, we give through investigation of this non-monotonicity property. Moreover, we present a systematic method for finding the worst-case scenario when the yield deformation and the stiffness of a structure assumed to be uncertain simultaneously. Numerical examples are presented to illustrate that the robustness of a structure does not necessarily improve when the yield deformation and/or the yield force is increased. [ABSTRACT FROM AUTHOR]

In this paper, a systematic technique is proposed for the optimal placement and design of nonlinear dampers for building structures. The concept of Output Frequency Response Function (OFRF) is applied to analytically represent the output frequency response of a building frame where nonlinear viscous dampers are fitted for suppression of vibration during earthquakes. An effective algorithm is derived using the analytical representation to optimally determine the locations and parameters of the nonlinear dampers. Various numerical examples are provided to verify the effectiveness of the optimal designs. A comparison of the vibration suppression performance with that of the frame structure under a random or uniform damping allocation is also made to demonstrate the advantages of the new designs over traditional solutions. [ABSTRACT FROM AUTHOR]

• Guidance for the application of power spectrum density data based on minimum constitutive relation error principle has been provided. • Only measurement power spectrum density data from few limited sensors are needed for damage identification. • Sparse regularization has demonstrated a pronounced effect on the accuracy and robustness for the identification results. This paper proposes a novel model-based damage identification strategy based on minimum constitutive relation error and sparse regularization using the power spectrum density data. Firstly, the stationary random vibration problem is transformed into a series of harmonic vibrations by the pseudo excitation method and the error in constitutive relation is established by the admissible stress field and admissible displacement field. A much more general and simpler strategy so as to build the admissible stress field is addressed by requiring only an extra decomposition of the stiffness matrix. Then, the sparse regularization is added to the original constitutive relation error objective function to circumvent the ill-posedness of the inverse problem. Finally, the solution of this nonlinear optimization problem is solved by the alternating minimization method. The proposed method has the advantage that only measurement power spectrum density data from few limited sensors are needed in the inverse analysis. Numerical and experimental results show the effectiveness and robustness of this approach. [ABSTRACT FROM AUTHOR]

• A vision-based measurement framework using the camera system for damage identification is proposed, which is composed of four procedures: camera calibration, image processing, system identification and sensitivity analysis. • Less number of modes is required for modal-based damage identification problems and more physical parameters could be extracted, taking advantage of the plentiful experimental data. • Suitable strategies to circumvent the major drawback that the camera system suffers high levels of noise in small vibration responses at higher frequencies are developed. Extracting physical parameters for damage identification problems from full-field measurements is a promising research because of the recent spread of vision-based measurement techniques in the experimental mechanics. This paper presents a vision-based measurement framework using the camera system for damage identification. The framework is composed of four procedures: camera calibration, image processing, system identification and sensitivity analysis. In contrast to traditional finite-point measurements, the camera system allows considerably greater non-contact measurement flexibility. Such flexibility has two important benefits: first, less number of modes is required for modal-based damage identification problems; and second, more physical parameters could be extracted, taking advantage of the plentiful experimental data. A laboratory test comparing the camera system to traditional accelerometer measurement is conducted to confirm the above advantages. Further statistic analysis shows that the major drawback of this technique is that the camera system presents high levels of noise in small vibration responses at higher frequencies. Suitable strategies to circumvent this disadvantage are developed. Moreover, a technique for practical camera calibration without the requirement that the objective plane should be strictly perpendicular to the camera axis is also demonstrated and verified by the proposed laboratory test. [ABSTRACT FROM AUTHOR]

Multi impulse with constant time interval is used as a representative of a long-duration earthquake ground motion. An analytical expression is derived for the elastic-plastic response of a single-degree-of-freedom (SDOF) model with nonlinear viscous damping subjected to the "critical multi impulse" which maximizes the response. The fact that only free vibration appears under such multi impulse enables the smart application of an energy approach in deriving the analytical expression for a complicated elastic-plastic response with nonlinear viscous damping. The nonlinear viscous damping characteristic for deformation is approximated in terms of a quadratic or elliptical function. The critical timing of the impulses is found to correspond to the zero restoring-force timing or the maximum velocity timing depending on the input level. It is shown that the nonlinearity in viscous damping causes a remarkable influence on the earthquake response in some cases. The reliability and accuracy of the proposed theory are investigated through the comparison with the results by the time-history response analysis to the tuned sine wave as a representative of the long-duration earthquake ground motion.