使用自适应扩展卡尔曼滤波器识别装有电缆支撑逆变系统的结构的系统

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Rui Zhang, Songtao Xue, Xinlei Ban, Ruifu Zhang, Liyu Xie
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引用次数: 0

摘要

一种创新的缆索支撑阻尼系统(CBIS)已被提出,并证明可有效减轻动态激励下的结构响应。CBIS 由一个惯性元件、一个涡流阻尼元件和一对只受拉力的缆索组成,可将楼层漂移转移到旋转飞轮上。为进一步研究 CBIS 的特性,提出了一种基于自适应扩展卡尔曼滤波器 (AEKF) 和递归最小二乘 (RLS) 算法的系统识别方法。根据 CBIS 模型的可用性,所提出的方法采用了两种策略:当模型特定时,AEKF 识别结构和 CBIS 的参数;或者,当模型不特定时,KF 结合 RLS 算法识别 CBIS 产生的恢复力作为未知的虚构输入。此外,AEKF 还加入了一个时变衰减因子,以自适应性地跟踪目标。通过自由振动和振动台试验对所提出的方法进行了验证,证明了 CBIS 在识别结构参数和恢复力方面的准确性。识别过程包括两个阶段:首先,AEKF 识别无 CBIS 的裸结构参数,然后使用 AEKF 或 KF-RLS 双策略分别识别 CBIS 或其恢复力的参数。研究结果还验证了 CBIS 机械模型和工作原理的可行性和有效性,从而有助于 CBIS 在未来研究中的推进和应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

System Identification of a Structure Equipped with a Cable-Bracing Inerter System Using Adaptive Extended Kalman Filter

System Identification of a Structure Equipped with a Cable-Bracing Inerter System Using Adaptive Extended Kalman Filter

An innovative cable-bracing inerter system (CBIS) has been proposed and shown to be effective in mitigating the structural response under dynamic excitation. The CBIS comprises an inerter element, an eddy current damping element, and a pair of tension-only cables that can transfer the story drift to rotating flywheels. To further investigate the characteristics of the CBIS, a system identification approach based on an adaptive extended Kalman filter (AEKF) and a recursive least-squares (RLS) algorithm is proposed. Depending on the CBIS model’s availability, the proposed approach uses two strategies: the AEKF identifies the parameters of the structure and the CBIS when the model is specific; alternatively, when the model is unspecific, the KF combined with an RLS algorithm identifies the restoring force generated by the CBIS as an unknown fictitious input. In addition, the AEKF incorporates a time-variant fading factor to track the target adaptively. The proposed approach is validated through free vibration and shaking table tests, demonstrating the accuracy in identifying structural parameters and restoring force provided by the CBIS. The identification process involves two stages: initially, the AEKF identifies the parameters of the bare structure without the CBIS, followed by a dual strategy using either AEKF or KF-RLS for identifying the parameters of the CBIS or its restoring force, respectively. The findings also verify the feasibility and validity of the mechanical model and operating principle of the CBIS, thereby contributing to the advancement and application of the CBIS in future studies.

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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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