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

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