Assessment of vibration-based damage identification techniques using localized excitation source

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• 作者：Sherif Beskhyroun (1)
  Toshiyuki Oshima (2)
  Shuichi Mikami (2)
  Yasunori Miyamori (2)
  
• 关键词：Damage detection ; Modal parameters ; Vibration data ; Health monitoring
• 刊名：Journal of Civil Structural Health Monitoring
• 出版年：2013
• 出版时间：August 2013
• 年：2013
• 卷：3
• 期：3
• 页码：207-223
• 全文大小：1669KB
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  17. Beskhyroun S, Takeda T, Oshima T, Mikami S, Yutaka T (2005) Damage identification of steel structures based on changes in the curvature of power spectral density. In: Proceedings of the 2nd international conference on structural health monitoring of intelligent infrastructure (SHMII-2-005), China, pp 791-97
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• 作者单位：Sherif Beskhyroun (1)
  Toshiyuki Oshima (2)
  Shuichi Mikami (2)
  Yasunori Miyamori (2)
  
  1. Department of Civil and Environmental Engineering, Faculty of Engineering, The University of Auckland, 20 Symonds Street, Auckland, 1142, New Zealand
  2. Civil Engineering Department, Kitami Institute of Technology, 165 Koen Cho, Kitami, Hokkaido, 090-8507, Japan
  
• ISSN：2190-5479

文摘

The Bridge Engineering Laboratory in Kitami Institute of Technology, Japan has introduced a number of different damage identification techniques to detect structural damage and identify its location utilizing piezoelectric actuators as a localized excitation source. Several spectral functions, such as cross spectral density, power spectral density, phase angle and transfer function estimate, were used to estimate the dynamic response of the structure. Each function’s magnitude, measured in a specified frequency range, is used in the damage identification methods. The change of the spectral function magnitude between the baseline state and the current state is then used to identify the location of possible damage in the structure. It is then necessary to determine which spectral function is best able to estimate the dynamic response and which algorithm is best able to identify the damage. The first part of this paper compares the performance of different spectral functions when their magnitude is used in one damage identification algorithm using experimental data from a railway steel bridge. The second part of this paper compares the performance of different damage identification algorithms using the same data.