Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling
Abstract The structural integrity and longevity of aluminum alloy components in lightweight engineering require accurate and efficient damage detection and prognosis methods. Traditional supervised machine learning (ML) techniques often face limitations due to dependency on large datasets, risk of o...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-13189-8 |
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