Abstract
In this paper, a framework for probabilistic delamination location and size detection is proposed. A delamination probability image using Lamb wave-based damage detection is constructed using the Bayesian updating technique. First, the algorithm for the probabilistic delamination detection framework using Bayesian updating (Bayesian Imaging Method-BIM) is presented. Following this, a fatigue testing setup for carbon-carbon composite coupons is introduced and the corresponding lamb wave based diagnostic signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method to detect delamination size and location, as along with corresponding uncertainty bounds. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation. Finally, some conclusions and future works are drawn based on the proposed study.
| Original language | English (US) |
|---|---|
| Title of host publication | PHM 2013 - Proceedings of the Annual Conference of the Prognostics and Health Management Society 2013 |
| Publisher | Prognostics and Health Management Society |
| Pages | 141-149 |
| Number of pages | 9 |
| ISBN (Print) | 9781936263066 |
| State | Published - 2013 |
| Event | 2013 Annual Conference of the Prognostics and Health Management Society, PHM 2013 - New Orleans, United States Duration: Oct 14 2013 → Oct 17 2013 |
Other
| Other | 2013 Annual Conference of the Prognostics and Health Management Society, PHM 2013 |
|---|---|
| Country | United States |
| City | New Orleans |
| Period | 10/14/13 → 10/17/13 |
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ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Health Information Management
- Software
Cite this
Probabilistic delamination diagnosis of composite materials using a novel Bayesian imaging method. / Peng, Tishun; Saxena, Abhinav; Goebel, Kai; Sankararaman, Shankar; Xiang, Yibing; Liu, Yongming.
PHM 2013 - Proceedings of the Annual Conference of the Prognostics and Health Management Society 2013. Prognostics and Health Management Society, 2013. p. 141-149.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Probabilistic delamination diagnosis of composite materials using a novel Bayesian imaging method
AU - Peng, Tishun
AU - Saxena, Abhinav
AU - Goebel, Kai
AU - Sankararaman, Shankar
AU - Xiang, Yibing
AU - Liu, Yongming
PY - 2013
Y1 - 2013
N2 - In this paper, a framework for probabilistic delamination location and size detection is proposed. A delamination probability image using Lamb wave-based damage detection is constructed using the Bayesian updating technique. First, the algorithm for the probabilistic delamination detection framework using Bayesian updating (Bayesian Imaging Method-BIM) is presented. Following this, a fatigue testing setup for carbon-carbon composite coupons is introduced and the corresponding lamb wave based diagnostic signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method to detect delamination size and location, as along with corresponding uncertainty bounds. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation. Finally, some conclusions and future works are drawn based on the proposed study.
AB - In this paper, a framework for probabilistic delamination location and size detection is proposed. A delamination probability image using Lamb wave-based damage detection is constructed using the Bayesian updating technique. First, the algorithm for the probabilistic delamination detection framework using Bayesian updating (Bayesian Imaging Method-BIM) is presented. Following this, a fatigue testing setup for carbon-carbon composite coupons is introduced and the corresponding lamb wave based diagnostic signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method to detect delamination size and location, as along with corresponding uncertainty bounds. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation. Finally, some conclusions and future works are drawn based on the proposed study.
UR - http://www.scopus.com/inward/record.url?scp=84920508111&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920508111&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84920508111
SN - 9781936263066
SP - 141
EP - 149
BT - PHM 2013 - Proceedings of the Annual Conference of the Prognostics and Health Management Society 2013
PB - Prognostics and Health Management Society
ER -