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- 2017
基于自适应技术的结构参数与输入同步反演
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Abstract:
发展一种基于遗传优化算法的自适应追踪技术,结合输入未知条件下的二次误差平方和方法,利用事件中的加速度响应数据实现结构参数与输入的同步反演,判断并追踪结构损伤,包括损伤发生的时间、位置和程度。三自由度迟滞非线性系统数值仿真结果表明,该方法能够精确有效地追踪结构参数的变化,并同步反演结构的未知输入。此外,对三自由度基础隔振结构模型进行了多工况实验研究。结果表明,所发展方法能够实时有效地追踪结构时变物理参数、反演结构未知基底激励,进而精准地获取结构的损伤信息。
A new data analysis technique, referred to the quadratic sum-squares error with unknown inputs (QSSE-UI) method along with adaptive tracking technique using genetic optimization algorithm, has been developed to simultaneously identify structural time-varying parameters and inputs based on real-time acceleration responses, leading to the detection and tracking of damages, including the time, location and severity of damages. The simulation results of 3-DOFs hysteretic nonlinear structure demonstrate that the proposed technique is capable of tracking the structural time-varying parameters and identifying the unknown inputs. Further, experimental study using a small-scale 3-story base-isolated structure model is conducted based on the proposed technique. During the tests, two typical excitations are applied to the base of the base-isolated structure model by shaking table, and different damage scenarios are simulated based on the stiffness element devices. Experimental results demonstrate that the proposed technique is capable of tracking the variation of structural parameters and simultaneous identifying the unknown support ex citations, leading to the accurate damage identification and tracking.