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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Kim, Namhun | - |
| dc.contributor.author | Lee, Jinwoo | - |
| dc.date.accessioned | 2024-01-29T14:47:13Z | - |
| dc.date.available | 2024-01-29T14:47:13Z | - |
| dc.date.issued | 2022-02 | - |
| dc.description.degree | Doctor | - |
| dc.description | Department of Mechanical Engineering | - |
| dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/73563 | - |
| dc.identifier.uri | http://unist.dcollection.net/common/orgView/200000606069 | - |
| dc.language | eng | - |
| dc.publisher | Ulsan National Institute of Science and Technology (UNIST) | - |
| dc.rights.embargoReleaseTerms | 9999-12-31 | - |
| dc.subject | In-situ monitoring, Deep learning, Operational stress condition, Direct energy deposition, Diagnosis | - |
| dc.title | An In-situ Machine Health Monitoring Method Against Operational Stress Conditions toward Deep Learning-Based Diagnosis: A Case Study of Direct-Energy Deposition | - |
| dc.type | Thesis | - |
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