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Data · dataset · 2025

Probabilistic Delamination Diagnosis of Composite Materials Using a Novel Bayesian Imaging Method

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In this paper, a probabilistic delamination location and size detection framework is proposed.

Description

The 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 proposed.

Following this, the composite coupon fatigue testing setup is introduced and the corresponding lamb wave diagnosis signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method to detect delamination size and location, as well as their confidence bounds. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation.

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Finally, some conclusions and future works are drawn based on the proposed study.

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Inferred from text
Image 75% · Imaging 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
NASA Data Portal3fcb88ae-bfea-4554-af5a-dd7806df045f10 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[modality].local:modality:imagingenrichment · data nasa govkeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data nasa govconnector:data_nasa_gov@1.0.0
descriptionsource · data nasa govconnector:data_nasa_gov@1.0.0/notes
license_textsource · data nasa govconnector:data_nasa_gov@1.0.0
publication_datesource · data nasa govconnector:data_nasa_gov@1.0.0
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updated_datesource · data nasa govconnector:data_nasa_gov@1.0.0