A Lightweight Method for Detecting Bearing Surface Defects Based on Deep Learning and Ontological Reasoning
Bearing as a critical component of machinery and equipment, its state of health directly affects the operating efficiency and security of the equipment. Therefore, the quality control of bearings must be very strict. Aiming at the different sizes and textures of the defect types on the surface of th...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11072476/ |
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