Monitoring of machining process anomalies in diamond turning of Ti6Al4V alloy using transfer learning-based algorithms

•Challenges associated with the in-process monitoring diamond turning are discussed.•If process drifts are not detected timely can cause an impact on substrate and tool.•Time frequency-based spectrogram analysis is carried out to detect the anomalies.•Use of transfer learning to overcome challenges...

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Veröffentlicht in:	Computers & industrial engineering Jg. 182; S. 109359
Hauptverfasser:	Manjunath, K, Tewary, Suman, Khatri, Neha, Cheng, Kai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2023
Schlagworte:	In-process monitoring Spectrogram Transfer learning-based algorithms Ultra-precision machining Vibrational Signal In-process monitoring Transfer learning-based algorithms Vibrational Signal Ultra-precision machining Spectrogram
ISSN:	0360-8352, 1879-0550
Online-Zugang:	Volltext
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