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

H. Zheng, Akira Mita

研究成果: Article

39 引用 (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.

元の言語English
ページ(範囲)1829-1836
ページ数8
ジャーナルSmart Materials and Structures
16
発行部数5
DOI
出版物ステータスPublished - 2007 10 1

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autoregressive moving average
Damage detection
damage
filters
Sensors
Mathematical operators
Time series
Monitoring
methodology
sensors
cross correlation
operators
vibration

ASJC Scopus subject areas

  • Materials Science(all)

これを引用

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