A.11: DFDD: Difference between revisions
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• '''Application in relevant Projects/Initiatives''': | • '''Application in relevant Projects/Initiatives''': | ||
• '''Type''': ML Model | • '''Asset Type''': ML Model | ||
• '''AI Breadth''': | • '''AI Breadth''': | ||
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• '''Applicable Business Category''': | • '''Applicable Business Category''': | ||
• '''License Information''': GNU General Public License version 3 | • '''License Information''': GNU General Public License version 3 | ||
Revision as of 09:34, 20 December 2024
• Short Description: A two-phase, digital-twin-assisted fault diagnosis method which is using deep transfer learning fault diagnosis both in the development and maintenance phases.
• Reference, URL: https://ieeexplore.ieee.org/document/8598879
• Relevant Domain/Industry: Manufacturing
• Application in relevant Projects/Initiatives:
• Asset Type: ML Model
• AI Breadth:
• Learning Ability: Deep Transfer Learning
• Related technologies:
• Applicable Research Area:
• Applicable Technical Category:
• Applicable Business Category:
• License Information: GNU General Public License version 3
• Related to circularity and sustainability: Yes_Fault Diagnosis/Eco-Design
• Audience: Developers
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