Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387221437> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4387221437 endingPage "19" @default.
- W4387221437 startingPage "1" @default.
- W4387221437 abstract "Abstract Operating under harsh conditions and exposed to fluctuating loads for extended periods, wind turbines experience a heightened vulnerability in their key components. Early fault detection is crucial to enhance the reliability of wind turbines, minimize downtime, and optimize power generation efficiency. Although deep learning techniques have been widely applied to fault diagnosis tasks, yielding remarkable performance, practical implementations frequently confront the obstacle of acquiring a substantial quantity of labeled data to train an effective deep learning model. Consequently, this paper introduces an unsupervised Global and Local Domain Adaptation Network (GLDAN) for fault diagnosis across wind turbines, enabling the model to efficiently transfer acquired knowledge to the target domain in the absence of labeled data. This feature renders it an appropriate solution for situations with limited labeled data availability. Employing adversarial training, GLDAN aligns global domain distributions, diminishing the overall discrepancy between source and target domains, and local domain distributions within a single fault category for both domains, capturing more intricate and specific fault features. The proposed approach is corroborated using actual wind farm data, and comprehensive experimental results demonstrate that GLDAN surpasses deep global domain adaptation methods in cross-wind turbine fault diagnosis, underlining its practical value in the field." @default.
- W4387221437 created "2023-10-01" @default.
- W4387221437 creator A5008028075 @default.
- W4387221437 creator A5034947641 @default.
- W4387221437 creator A5064722162 @default.
- W4387221437 date "2023-09-30" @default.
- W4387221437 modified "2023-10-01" @default.
- W4387221437 title "Gldan: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis" @default.
- W4387221437 doi "https://doi.org/10.1115/1.4063578" @default.
- W4387221437 hasPublicationYear "2023" @default.
- W4387221437 type Work @default.
- W4387221437 citedByCount "0" @default.
- W4387221437 crossrefType "journal-article" @default.
- W4387221437 hasAuthorship W4387221437A5008028075 @default.
- W4387221437 hasAuthorship W4387221437A5034947641 @default.
- W4387221437 hasAuthorship W4387221437A5064722162 @default.
- W4387221437 hasConcept C108583219 @default.
- W4387221437 hasConcept C111919701 @default.
- W4387221437 hasConcept C119599485 @default.
- W4387221437 hasConcept C119857082 @default.
- W4387221437 hasConcept C121332964 @default.
- W4387221437 hasConcept C127313418 @default.
- W4387221437 hasConcept C127413603 @default.
- W4387221437 hasConcept C138885662 @default.
- W4387221437 hasConcept C154945302 @default.
- W4387221437 hasConcept C163258240 @default.
- W4387221437 hasConcept C165205528 @default.
- W4387221437 hasConcept C175551986 @default.
- W4387221437 hasConcept C180591934 @default.
- W4387221437 hasConcept C200601418 @default.
- W4387221437 hasConcept C2776401178 @default.
- W4387221437 hasConcept C2778449969 @default.
- W4387221437 hasConcept C41008148 @default.
- W4387221437 hasConcept C41895202 @default.
- W4387221437 hasConcept C43214815 @default.
- W4387221437 hasConcept C62520636 @default.
- W4387221437 hasConcept C78519656 @default.
- W4387221437 hasConcept C78600449 @default.
- W4387221437 hasConceptScore W4387221437C108583219 @default.
- W4387221437 hasConceptScore W4387221437C111919701 @default.
- W4387221437 hasConceptScore W4387221437C119599485 @default.
- W4387221437 hasConceptScore W4387221437C119857082 @default.
- W4387221437 hasConceptScore W4387221437C121332964 @default.
- W4387221437 hasConceptScore W4387221437C127313418 @default.
- W4387221437 hasConceptScore W4387221437C127413603 @default.
- W4387221437 hasConceptScore W4387221437C138885662 @default.
- W4387221437 hasConceptScore W4387221437C154945302 @default.
- W4387221437 hasConceptScore W4387221437C163258240 @default.
- W4387221437 hasConceptScore W4387221437C165205528 @default.
- W4387221437 hasConceptScore W4387221437C175551986 @default.
- W4387221437 hasConceptScore W4387221437C180591934 @default.
- W4387221437 hasConceptScore W4387221437C200601418 @default.
- W4387221437 hasConceptScore W4387221437C2776401178 @default.
- W4387221437 hasConceptScore W4387221437C2778449969 @default.
- W4387221437 hasConceptScore W4387221437C41008148 @default.
- W4387221437 hasConceptScore W4387221437C41895202 @default.
- W4387221437 hasConceptScore W4387221437C43214815 @default.
- W4387221437 hasConceptScore W4387221437C62520636 @default.
- W4387221437 hasConceptScore W4387221437C78519656 @default.
- W4387221437 hasConceptScore W4387221437C78600449 @default.
- W4387221437 hasLocation W43872214371 @default.
- W4387221437 hasOpenAccess W4387221437 @default.
- W4387221437 hasPrimaryLocation W43872214371 @default.
- W4387221437 hasRelatedWork W1568390478 @default.
- W4387221437 hasRelatedWork W1995197451 @default.
- W4387221437 hasRelatedWork W2005809146 @default.
- W4387221437 hasRelatedWork W2057658601 @default.
- W4387221437 hasRelatedWork W2062658440 @default.
- W4387221437 hasRelatedWork W2396014605 @default.
- W4387221437 hasRelatedWork W2613298738 @default.
- W4387221437 hasRelatedWork W2804944700 @default.
- W4387221437 hasRelatedWork W2908122050 @default.
- W4387221437 hasRelatedWork W3149885144 @default.
- W4387221437 isParatext "false" @default.
- W4387221437 isRetracted "false" @default.
- W4387221437 workType "article" @default.