Identification of gradually varying physical parameters based on discrete cosine transform using partial measurements

Ning Yang, Ying Lei, Jun Li, Hong Hao
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Abstract

Structural physical parameters often vary gradually due to the degradation of material properties or effects of environment. In this paper, two novel approaches are proposed to identify the gradually varying physical parameters based on the discrete cosine transform (DCT) using partial measurements of structural responses. Approach I is proposed for the circumstance of known excitations. The gradually varying physical parameters are first located by the fading‐factor extended Kalman filter (FEKF) and then identified by the proposed DCT integrated with Kalman filter (KF) method. Approach II is proposed for the identification of gradually varying physical parameters under unknown excitations. The gradually varying physical parameters are first localized by the proposed fading‐factor extended Kalman filter under unknown input (FEKF‐UI) and then identified by the proposed DCT integrated with Kalman filter under unknown input (KF‐UI). Numerical examples demonstrate that the proposed approaches can identify the gradually varying physical parameters accurately with incomplete measurement data. Moreover, the identification of time‐varying cable force in cable‐stayed bridge is also discussed as a case study of the proposed approach I. Experimental verification shows that it provides a new path to identify the time‐varying cable force by only using one acceleration response measurement of the cable.
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基于局部测量的离散余弦变换识别逐渐变化的物理参数
由于材料性能的退化或环境的影响,结构物理参数往往会逐渐变化。本文提出了两种基于离散余弦变换(DCT)的新方法,利用结构响应的局部测量来识别逐渐变化的物理参数。方法一是针对已知激励的情况提出的。首先利用衰落因子扩展卡尔曼滤波(FEKF)对逐渐变化的物理参数进行定位,然后利用所提出的与卡尔曼滤波(KF)相结合的离散余弦变换(DCT)方法进行识别。方法二用于识别未知激励下逐渐变化的物理参数。首先用未知输入下衰落因子扩展卡尔曼滤波器(FEKF‐UI)对逐渐变化的物理参数进行局部化,然后用未知输入下与卡尔曼滤波器集成的离散余波变换(DCT)进行识别。数值算例表明,该方法可以在测量数据不完整的情况下准确识别出逐渐变化的物理参数。此外,本文还讨论了斜拉桥中时变索力的识别问题,并以此为例进行了研究。实验验证表明,该方法提供了一种仅使用一次斜拉桥的加速度响应测量就能识别时变索力的新途径。
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