基于反力辨识的结构振动实时响应估计

IF 5.4 2区 工程技术 Structural Control & Health Monitoring Pub Date : 2023-04-06 DOI:10.1155/2023/2691476
Seungin Oh, Hanmin Lee, Jai-Kyung Lee, Hyungchul Yoon, Jin-Gyun Kim
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引用次数: 0

摘要

虚拟传感技术弥补了传统物理传感技术的局限性,是一种识别结构系统不可达状态的有效方法。近年来,它在结构振动及其相关的物理领域,如土木、机械、航空航天、热力学和声学等领域得到了广泛的应用。本研究旨在开发一种结构振动虚拟感知算法,用于实时识别未测信息。首先,利用物理传感器测量某些局部点的振动响应(如位移和加速度),并在实时计算过程中使用数值模型对数据集进行扩展,以覆盖整个空间域的未测量量。然后提出了一种改进的时间积分器,利用逆动力学实现物理传感器和数值模型的同步。特别地,利用隐式时间积分推导了一种有效的反力识别方法。采用二阶常微分公式及其基于投影的降阶建模,避免了状态空间形式中两倍大的自由度。然后,采用吉洪诺夫正则化噪声滤波算法代替卡尔曼滤波。研究了该方法在正弦和随机激励载荷条件下的数值和实验性能。在数值试验中,该系统能够在16181 S / m / S的速度下识别电机外壳结构的状态。FDE和RMSE值分别在0.1816和1503.2以下。以实验测试为例,在单板机上对梁结构进行了算法实现,包括反力识别和未测响应预测。即使在有限的计算环境下,该系统也能以2173 S / m / S的速度实时识别所施加的力。在所有的实验案例中,FDE和RMSE值都被限定在0.2925和0.1660以下。结果表明,在有限的计算环境下,虚拟感知算法可以实时准确地识别振动模型中的未测信息、力和位移。
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Real-Time Response Estimation of Structural Vibration with Inverse Force Identification
Virtual sensing is an effective method to identify the inaccessible state of the structural systems by compensating the limitations of the conventional physical sensing techniques. Recently, it becomes popular in structural vibration field and their relevant physical domains such as civil, mechanical, aerospace engineering, thermal dynamics, and acoustics. This study aimed to develop a virtual sensing algorithm of structural vibration for the real-time identification of unmeasured information. First, certain local point vibration responses (such as displacement and acceleration) are measured using physical sensors, and the data sets are extended using a numerical model to cover the unmeasured quantities through the entire spatial domain in the real-time computation process. A modified time integrator is then proposed to synchronize the physical sensors and the numerical model using inverse dynamics. In particular, an efficient inverse force identification method is derived using implicit time integration. The second-order ordinary differential formulation and its projection-based reduced-order modeling are used to avoid two times larger degrees of freedom within the state-space form. Then, the Tikhonov regularization noise-filtering algorithm is employed instead of Kalman filtering. The performance of the proposed method is investigated on both numerical and experimental testbeds under sinusoidal and random excitation loading conditions. In the numerical test, the system could identify the status of the motor housing structure in the speed of 16,181 S a m p l e s / s . The FDE and RMSE values are bounded under 0.1816 and 1503.2. In the case of the experimental test, the algorithm is implemented to the beam structure using a single-board computer, including inverse force identification and unmeasured response prediction. Even in the limited computational environment, the system could identify the applied forces in real time in the speed of 2,173 S a m p l e s / s . Through all experimental cases, FDE and RMSE values are bounded under 0.2925 and 0.1660. The results show that the virtual sensing algorithm can accurately identify unmeasured information, forces, and displacements throughout the vibration model in real time in a very limited computing environment.
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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring Engineering-Building and Construction
自引率
13.00%
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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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