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Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention
Research article (Actuators, 2024) · cited 10× · AI/ML
Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention
Summary
Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention is a scholarly article[1].
Key Facts
Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention. Retrieved May 24, 2026, from https://4ort.xyz/entity/wind-turbine-bearing-failure-diagnosis-using-multi-scale-feature-extraction-and-residual-neural-networks-with-block-atte
MLA“Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/wind-turbine-bearing-failure-diagnosis-using-multi-scale-feature-extraction-and-residual-neural-networks-with-block-atte.
BibTeX@misc{4ortxyz_wind-turbine-bearing-failure-diagnosis-using-multi-scale-feature-extraction-and-residual-neural-networks-with-block-atte_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention}}, year = {2026}, url = {https://4ort.xyz/entity/wind-turbine-bearing-failure-diagnosis-using-multi-scale-feature-extraction-and-residual-neural-networks-with-block-atte}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Wind Turbine Bearing Failure Diagnosis Using Multi-Scale Feature Extraction and Residual Neural Networks with Block Attention — https://4ort.xyz/entity/wind-turbine-bearing-failure-diagnosis-using-multi-scale-feature-extraction-and-residual-neural-networks-with-block-atte (retrieved 2026-05-24)
