Szczegóły publikacji
Opis bibliograficzny
Cointegration and wavelet analysis based approach for Lamb wave based structural damage detection / Phong B. DAO, Wiesław J. STASZEWSKI // W: Health monitoring of structural and biological systems 2013 : 11–14 March 2013, San Diego, California, United States / ed. Tribikram Kundu. — Washington : SPIE, cop. 2013. — (Proceedings of SPIE / The International Society for Optical Engineering ; ISSN 0277-786X ; vol. 8695). — ISBN: 9780819494788. — S. 86952D-1–86952D-13. — Bibliogr. s. 86952D-12–86952D-13, Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 78915 |
|---|---|
| Data dodania do BaDAP | 2014-01-21 |
| DOI | 10.1117/12.2012175 |
| Rok publikacji | 2013 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | Conference on Health Monitoring of Structural and Biological Systems |
| Czasopismo/seria | Proceedings of SPIE / The International Society for Optical Engineering |
Abstract
The paper demonstrates how to remove the undesired temperature effect from Lamb wave data in order to detect structural damage more precisely and reliably. The method used is based on the cointegration technique and wavelet analysis. The former is built on the analysis of non-stationary behaviour whereas the latter brings the concept of multi-resolution decomposition of time series. Instead of directly using Lamb wave data for damage detection, three approaches are used: (1) analysis of the variance of wavelet coefficients of Lamb wave responses before cointegration, (2) analysis of the cointegrating residuals obtained from the cointegration process of Lamb wave responses, and (3) analysis of the variance of wavelet coefficients of Lamb wave responses after cointegration. These approaches are tested on undamaged and damaged aluminium plates that have been exposed to temperature variations. The experimental results show that the first approach still exhibits temperature variability and damage cannot be detected. In contrast the second and third approaches can isolate damage-sensitive features from temperature variations, detect the existence of damage and classify its severity.
