Two-stage damage diagnosis based on the distance between ARMA models and pre-whitening filters

H. Zheng, A. Mita

研究成果: Article査読

41 被引用数 (Scopus)

抄録

This paper presents a two-stage damage diagnosis strategy for damage detection and localization. Auto-regressive moving-average (ARMA) models are fitted to time series of vibration signals recorded by sensors. In the first stage, a novel damage indicator, which is defined as the distance between ARMA models, is applied to damage detection. This stage can determine the existence of damage in the structure. Such an algorithm uses output only and does not require operator intervention. Therefore it can be embedded in the sensor board of a monitoring network. In the second stage, a pre-whitening filter is used to minimize the cross-correlation of multiple excitations. With this technique, the damage indicator can further identify the damage location and severity when the damage has been detected in the first stage. The proposed methodology is tested using simulation and experimental data. The analysis results clearly illustrate the feasibility of the proposed two-stage damage diagnosis methodology.

本文言語English
ページ(範囲)1829-1836
ページ数8
ジャーナルSmart Materials and Structures
16
5
DOI
出版ステータスPublished - 2007 10 1

ASJC Scopus subject areas

  • 信号処理
  • 土木構造工学
  • 原子分子物理学および光学
  • 材料科学(全般)
  • 凝縮系物理学
  • 材料力学
  • 電子工学および電気工学

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