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Author:

Liu, H. (Liu, H..) | Tang, Z. (Tang, Z..) | Enokida, R. (Enokida, R..)

Indexed by:

EI Scopus SCIE

Abstract:

In recent years, real-time hybrid testing (RTHT) has been applied for the dynamic testing of high-speed trains running on bridges. A guarantee of stability for the RTHT system is essential to achieve a safe and reliable result. However, the inherent time-varying characteristics of the vehicle-bridge coupled system pose challenges to RTHT stability prediction. This study aims to develop a stability prediction method specifically tailored for time-varying RTHT system. Firstly, the vehicle-bridge coupled RTHT was modelled using a discrete state–space representation with a comprehensive consideration of the time-varying vehicle-bridge interaction and the dynamics of the shaking table. Subsequently, a time-varying stability criterion was derived from the periodic time-varying state matrix, forming the basis for a relative stability prediction method. The validity of the proposed method was confirmed through simulations and experiments employing a single-axle interaction within the vehicle-bridge coupled RTHT system. The coupled system consisted of a quarter-car model and simply supported beams were used as an example to evaluate the stability and accuracy of the time-varying RTHT. The results showed that the stability increased with increasing vehicle speed. Reducing the pure time delay of the shaking table improved both stability and accuracy. Increasing the effective frequency of the shaking table improved the accuracy but may reduce the stability of the RTHT. © 2024 Elsevier Ltd

Keyword:

Stability Vehicle–bridge coupled system Accuracy Time-varying system Real-time hybrid testing

Author Community:

  • [ 1 ] [Liu H.]The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Tang Z.]The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Tang Z.]Chongqing Research Institute of Beijing University of Technology, Chongqing, 401120, China
  • [ 4 ] [Enokida R.]International Research Institute of Disaster Science, Tohoku University, Sendai, 980-0845, Japan

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Source :

Mechanical Systems and Signal Processing

ISSN: 0888-3270

Year: 2024

Volume: 216

8 . 4 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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