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Reliability evaluation is a key factor in serviceability and safety analysis of air vehicles. Structural health monitoring methods have grown to a degree of maturity in many industries. However, there is a challenging interest to tie in SHM with reliability assessment. In this respect, consideration of stochastic structural dynamics with SHM data and random loadings opens a new chapter in failure prevention. The current study focuses on the stochastic behavior of structures as a way to relate SHM data with reliability. In this respect, uncertain factors such as atmospheric turbulence, structural parameters, and sensor outputs are considered in the process of reliability assessment. Firstly, an experimental evaluation is conducted using a simple cantilevered beam. Subsequently, system identification is weaved in with a probability density evolution equation for calculating the reliability of a wing structural component. Numerical simulations demonstrate that structural reliability of a typical WSC can be effectively evaluated. The proposed scheme paves the way for new SHM research topics such as online life prediction and reliability based failure prevention. [ABSTRACT FROM AUTHOR]

In this study, active vibration control of a cantilevered flexible beam structure equipped with bonded piezoelectric sensor/actuators is investigated. The linear quadratic regulator technique together with an observer is adopted to design the controller as well as to provide the full-state feedback. Two different approaches are subsequently used for simultaneously integrated optimization of the controller and observer parameters. In the first approach, a linear experimental model of the system is obtained using identification techniques, and the optimization is then performed based on a computer simulation of the system. However, in the second approach, a hardware-in-the-loop optimization scheme is proposed and applied to automatically tune the parameters. In both cases, a hybrid metaheuristic algorithm called tabu continuous ant colony system is utilized to find the optimal controller and observer. The integrated performance is experimentally evaluated to demonstrate effectiveness of the proposed hardware-in-the-loop optimization method. Finally, a comparison is made between the frequency response of the current controller with a pole placement controller from the literature in order to assess the improvement achieved through hardware-in-the-loop optimization. [ABSTRACT FROM PUBLISHER]

Experimental system identification of a flexible beam based on sweep square excitation is studied. For the purpose of nonparametric identification, an excitation signal is conducted to evaluate the frequency response of the system. The experiment is designed to excite the beam using a piezo actuator, in a way to raise the chance of exciting first three natural modes. In order to find the best linear representation of the real system, two different identification methods are applied. First, autoregressive moving average eXogenous method is employed to identify the transfer function of the beam. Then, the identification is carried out using the subspace identification method to obtain the state space model. A comparison is made between different orders of prediction and the best chosen models of the two identification methods are compared with each other to select the most accurate linear system. Furthermore, as the identified model has to fulfill the controllability and observability conditions, the amenable system is achieved after some order reductions. Two reduction methods called minimum truncation and maximum DC gains matching are utilized to find the most effective reduced order. The outcome of this study will bring in the best linear representation of the beam coupled with piezoelectric sensors/actuators. [ABSTRACT FROM AUTHOR]