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In order to identify the hysteretic behavior in the form of nonlinear restoring force (NRF) and the unknown dynamic excitation when the acceleration measurement at the degree of freedom (DOF) of the excitation is unknown, and considering the fact that it is difficult to establish a general parametric mathematical model in advance to describe the real hysteretic behavior of an engineering structure, in this paper, a nonparametric identification approach for both NRF and dynamic loading is presented using an updated general extended Kalman filter with unknown input (UGEKF‐UI) algorithm with limited acceleration measurements excluding that at the DOF of the dynamic excitation. The NRF is expressed with a Legendre polynomial model, and no assumption on the parametric model of structure nonlinearity is required for the identification. Numerical studies on lumped mass multi‐DOFs numerical models equipped with different numbers of magnetorheological (MR) dampers modeled with different parametric mathematical models are carried out to verify the effectiveness of the proposed approach. Furthermore, experimental study is conducted on a four‐story shear frame structure with an MR damper under unknown external dynamic excitation. The unknown dynamic responses including the acceleration at the location where the excitation is applied, damping force provided by the MR damper, and the dynamic excitation are identified and compared with the test measurements. Both numerical and experimental results demonstrate the proposed approach is capable of identifying the NRF and the unknown dynamic excitation in a nonparametric way even the acceleration response at the DOF where the excitation is applied is unknown. [ABSTRACT FROM AUTHOR]

The safety of inclined cables is fundamental to the integrity of cable-stayed bridges. The vibrational frequencies of these cables form the foundation for assessing the cable force. Traditional contact measurement methods necessitate the installation of sensors on each cable, incurring substantial costs. In scenarios where camera placement adjacent to an inclined cable is impractical, noncontact approaches such as video capture via unmanned aerial vehicles prove effective. However, unmanned aerial vehicle-captured videos present a challenge due to their complex background, impeding cable feature recognition. In our study, we initially utilized the Region Growing algorithm for background subtraction. To enhance this method, we integrated it with the unique structural characteristics of cables, leading to the creation of the RGv2 algorithm. This novel algorithm offers increased processing speed and improved accuracy. Furthermore, we combined our method with empirical mode decomposition for effective detection of cable frequency characteristics. We also implemented a hybrid method, combining the K-Means and line segment detector algorithms with empirical mode decomposition. Compared to deep learning techniques for background subtraction, our proposed method demonstrates superior computational efficiency and promising potential for measuring vibrational frequencies of inclined cables. [ABSTRACT FROM AUTHOR]

Adaptive control methods have been widely adopted to handle the variable time delay in real-time hybrid simulation (RTHS). Nevertheless, the initial parameter settings in adaptive control law, the parameter estimation method, and the testing system nonlinearity will affect RTHS's accuracy and stability at different levels. To this end, this study proposes a novel model-based adaptive feedforward-feedback control method that considers an additive error model. In the proposed method, the time delay and amplitude discrepancy are roughly compensated by a feedforward controller and then finely reduced by an adaptive controller, and an outer-loop control formed by the feedback controller is introduced to improve the ability and robustness furthermore. What's more, the testing system, composed of the transfer system and physical specimen, is divided into the nominal and additive error models. The feedforward controller is devised using the inverse nominal model, whose parameters are constant. The adaptive controller is designed to adopt a discrete-time additive error model, in which the parameters are identified online by the Kalman filter. Numerical simulations, parametric studies, and actual experiments were carried out to inspect the feasibility and effectiveness of this method thoroughly. Results indicate that the proposed method can effectively improve the accuracy and stability of RTHS and significantly reduce the dependence on the adaptive control law. Moreover, the proposed method exhibits strong robustness and is, therefore, useful in RTHS. [ABSTRACT FROM AUTHOR]

Summary: Global Navigation Satellite System (GNSS) positioning technology has had widespread applications in the structural health monitoring as its overall performance has improved significantly in the last two decades. It is capable of providing timely and accurate structural vibration information such as dynamic displacements and modal frequencies at higher performance than traditional accelerometers. The studies summarized in this paper focus on the improvement of the multi‐sensors and multi‐constellation data acquisition techniques, the improvement of multiple approaches for erroneous noise mitigation, and innovative modal parameter identification methods. We also detailed the applications of GNSS on the deformation monitoring for towers, chimneys, tall buildings, and bridges. With continuous enhancements in the algorithm and hardware of GNSS, it is expected that the application of GNSS technology can be expanded to other fields such as bridge cable‐force measurements and bridge weight‐in‐motion as well as structural deformation monitoring. [ABSTRACT FROM AUTHOR]

Summary: With the increase of the span and height of modern engineering structures, the design length and complexity of the cable structure are constantly increasing, whose dynamic problem has become the key to structural design, performance monitoring and maintenance, and vibration control. Therefore, it is necessary to study and develop a unified dynamic analysis theory for complex cable system to meet the requirements of calculation accuracy and efficiency. In view of this, a unified dynamic analysis method for dynamic analysis of complex cable system is proposed in this paper on the basis of the classical dynamic stiffness method. In this paper, the dynamic stiffness method has been enhanced in multiple aspects, which not only retains the advantages of high computational efficiency and wide application range but also overcomes its technical bottlenecks in analysis of shallow‐sag cable system considering the damping effect, composite cable systems, and multisegment cable systems. The proposed method can not only be used to the structural design of the complex cable system but also be extended to the vibration control of the system during the service period. [ABSTRACT FROM AUTHOR]