The Tunnel Structural Mode Frequency Characteristics Identification and Analysis Based on a Modified Stochastic Subspace Identification Method
Auteur(s): |
Biao Zhou
Xiongyao Xie Xiaojian Wang |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Shock and Vibration, 2018, v. 2018 |
Page(s): | 1-12 |
DOI: | 10.1155/2018/6595841 |
Abstrait: |
With the rapid development of underground engineering in China, the heavy structural maintenance work followed is expected to be a great challenge in the future. The development also provides a promising application prospect for the newly developed vibration-based health assessment and monitoring methods. However, the fact that tunnels are embedded in soil makes collecting and identifying the vibration characteristics more difficult, especially for the online monitoring. In this paper, a new identification method that combines the natural excitation technique (NExT) and stochastic subspace identification (SSI) method is developed. The new method is compared with the traditional SSI method, and mode frequency analysis is made based on a series of field tests carried out at the subway and power tunnel. It is found that both stability and efficiency of the mode frequency identification have been greatly improved, and it more suitable for online monitoring. Meanwhile, a mathematical model is used to analyze the original mode characteristics and the influence of soil coupling. The results are also compared with the field tests results by using the NExT-SSI method, and some recommendations are also made for how to choose the vibration modals for vibration-based monitoring in the tunnel. |
Copyright: | © 2018 Biao Zhou, Xiongyao Xie, Xiaojian Wang |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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02.06.2022