نوع مقاله : پژوهشی
نویسندگان
دانشکده ی مهندسی عمران، دانشگاه صنعتی شریف
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Rapid assessment of structural safety and performance following the occurrence
of important events such as moderate to severe earthquakes is so significant
and vital and reveals the need for developing online and pseudo-online health
monitoring methods. Online monitoring methods can be implemented without the
need for in-situ testing and expert staff to analyze the recorded data. In other words, these methods provide comprehensive information on the condition
of the structure only by using the vibration data recorded by embedded sensors
as well as the preset health monitoring algorithms. On the other hand, most
civil structures exhibit a nonlinear response after severe incidents like
earthquakes. In many cases, this nonlinear hysteretic behavior is along with
stiffness deterioration, strength degradation, pinching effect, permanent
plastic deformation, or a combination of them. Therefore, considering a
comprehensive definition of damage that takes into account the nonlinear
behavior of structures according to their type is one of the most important
steps in the process of structural identification and evaluation. Various methods have been introduced in the literature for online estimation of states and parameters of nonlinear structures. However, the challenging part in most
of these methods is the determination of parameters noise covariance matrix
which becomes particularly important due to the increasing number of structural
floors, thus increasing the number of unknown parameters. In this study, an
effective method for online jointly estimation of state and parameters of
nonlinear hysteretic structures with consideration of degradation and pinching
phenomena is proposed. Simultaneous estimation of states and parameters is
conducted using a combination of Unscented Kalman Filter as an effective
estimator and Robbins-Monroe stochastic approximation technique as the
parameters noise covariance matrix regulator. The abovementioned method was
applied to two one-story and one three-story shear buildings and the results of
the identification process were presented with emphasis on the effects of
measurement noise, modeling error, and use of the Monte-Carlo random simulation method. Simulation results demonstrated the accuracy and efficiency of the proposed method in online jointly estimation applications as well as the
desirable capability to track hysteretic curves of each structural floor.
کلیدواژهها [English]
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