Noise robust classification of carbide tool wear in machining mild steel using texture extraction based transfer learning approach for predictive maintenance

Noise robust classification of carbide tool wear in machining mild steel using texture extraction based transfer learning approach for predictive maintenance

Acoustics based smart condition monitoring is a viable alternative to mechanical vibrations or image-capture based predictive maintenance methods. In this study, a texture analysis based transfer learning methodology was applied to classify tool wear based on the noise generated during mild steel ma...

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Bibliographic Details
Main Authors: Ravi Sekhar, Sharnil Pandya, Pritesh Shah, Hemant Ghayvat, Deepak Sharma, Matthias Renz, Deep Shah, Adeeth Jagdale, Devansh Hukmani, Santosh Saxena, Neeraj Kumar
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Results in Control and Optimization
Subjects:
Smart manufacturing
Acoustics
Sound classification
Predictive maintenance
Deep learning
Transfer learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2666720724001218
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