Probabilistic delamination diagnosis of composite materials using a novel Bayesian Imaging Method



Published Oct 14, 2013
Tishun Peng Abhinav Saxena Kai Goebel Shankar Sankararaman Yibing Xiang Yongming Liu


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.

How to Cite

Peng, T. ., Saxena, A. ., Goebel, K. ., Sankararaman, S., Xiang, Y. ., & Liu, Y. . (2013). Probabilistic delamination diagnosis of composite materials using a novel Bayesian Imaging Method. Annual Conference of the PHM Society, 5(1).
Abstract 554 | PDF Downloads 124



diagnosis, composite materials, Bayesian Imaging Method

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