Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis
This study proposed a novel machine learning–driven methodology for detecting potential defects in computer numerical control (CNC) spindle manufacturing. The methodology, which analyzes 13 real-world built-in spindles, employs t-distributed stochastic neighbor embedding (t-SNE) for data visualizati...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/vib/7434412 |
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