Research on Defect Classification of Electric Power Equipment Based on Knowledge Graph
Author:
Affiliation:
1. Heyuan Power Supply Bureau, Guangdong Power Grid Co., Ltd.,Heyuan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512718.pdf?arnumber=10512718
Reference16 articles.
1. Automatic representation and detection of fault bearings in in-wheel motors under variable load conditions
2. Online Equivalent Degradation Indicator Calculation for Remaining Charging-Discharging Cycle Determination of Lithium-Ion Batteries
3. A classification model of power operation inspection defect texts based on graph convolutional network
4. IoT-Enabled Few-Shot Image Generation for Power Scene Defect Detection Based on Self-Attention and Global–Local Fusion
5. Novel Particle Swarm Optimization-Based Variational Mode Decomposition Method for the Fault Diagnosis of Complex Rotating Machinery
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