Abstract
Experimental evaluation is crucial for ensuring the accuracy of real-time hybrid simulation (RTHS) results. While existing methods can calculate time delay and amplitude error, time-varying delays can destabilize RTHS, requiring a method to account for them. This paper proposes using empirical mode decomposition (EMD) to calculate instantaneous control parameters, such as instantaneous amplitude and time delay. Intrinsic mode functions (IMF) from EMD capture the signal's local characteristics at different time scales, and the Hilbert transform is applied to compute these parameters. After EMD, a different number of IMFs may be obtained for calculated displacements than for measured displacements, and this paper gives advice on the IMFs needed to calculate instantaneous control parameters (ICP), and how they should be matched. The signals obtained from the numerical simulation of the benchmark model without and with compensation are firstly subjected to the calculation of ICP, and the results prove the effectiveness of ICP. Subsequently, the predefined displacement test with a multidegree-of-freedom structure and the RTHS with a single-degree-of-freedom structure and self-centering viscous damper were subjected to the traditional ICP method and the EMD-based ICP calculation method for ICP calculation, respectively, and the comparative results show that the effectiveness of the EMD-based ICP calculation method is increased, and that EMD effectively solves the negative-frequency issue caused by signals with multiple poles between two crossed zeros. These calculations show great potential in improving experimental evaluations.
Key Words
empirical mode decomposition; instantaneous control parameters; instantaneous frequency; real-time hybrid simulation
Address
(1) Weijie Xu, Xiangjin Meng, Tong Guo, Changle Peng:
Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, P.R. China;
(2) Cheng Chen:
School of Engineering, San Francisco State University, USA.
Abstract
Global monitoring of structures is vital for assessing their structural integrity, especially with the impact of moving vehicles on railroad bridges. This necessitates simultaneous monitoring of both systems to understand interaction dynamics comprehensively. In vibration-based Structural Health Monitoring fields, demands for directly obtaining displacement responses increase, leading to non-contact sensing adoption. Computer Vision (CV)-based methods, using feature tracking techniques for displacement measurements, have become practical alternatives. The proposed approach utilizes Poor Feature Points, offering a global view and overcoming spatial resolution limitations. Addressing challenges related to camera ego-motion in large-scale monitoring, strategies for re-assigning regions of interest based on feature quality are introduced, and camera ego-motion is compensated by calibrating feature points. The You Only Look Once algorithm is used for vehicle wheel detection, localizing contact points to examine Vehicle-Bridge Interaction dynamics. A laboratory-scale experiment validation confirms the feasibility of global monitoring with vision sensors, especially in interpreting VBI dynamics.
Key Words
KLT (Kanade Lucas Tomasi) algorithm; MST (Modified S-Transform); poor-feature points; vehicle track bridge interaction dynamics; yolo
Address
(1) Jae Hun Lee:
Department of Civil and Environmental Engineering, Hanyang University, Seoul, Republic of Korea;
(2) Sang Bin Lee, Robin Eunju Kim:
Department of Architecture and Architectural Engineering, Seoul National University, 1, Gwanak-gu, Seoul 08826, Republic of Korea;
(3) Jae Hun Lee:
Infrastructure Bridge Engineering Division, Hyundai Engineering & Construction, 75, Yulgok-ro, Jongno-gu, Seoul 03058, Republic of Korea.
