Tool Wear Condition Monitoring Using Emitted Sound Signals By Simple Machine Learning Technique

Authors: , ,

Abstract: As a continuous enhancement to the tool wear monitoring using non-disturbing method of sound wave analysis, a simple machine learning technique enhances the prediction to better levels and reduces the procedures. A simple linear regression Algorithm was used to train and predict the trends of various degrees of tool wear to distinguish them from each other. The results based on this simple linear regression were successful in showing the difference of sound patterns and are reported.

Design, Construction, Maintenance, ISSN / E-ISSN: 2944-912X / 2732-9984, Volume 2, 2022, Art. #22

PDF
DOI
XML
Cite
×
Citation Tools
WSEAS AMA
C. Logesh Perumal, S. B. Bhadrinathan, Andrews Samraj, "Tool Wear Condition Monitoring Using Emitted Sound Signals By Simple Machine Learning Technique," Design, Construction, Maintenance, vol. 2, pp. 168-172, 2022, DOI:10.37394/232022.2022.2.22
C. Logesh Perumal, S. B. Bhadrinathan, Andrews Samraj. Tool Wear Condition Monitoring Using Emitted Sound Signals By Simple Machine Learning Technique. Design, Construction, Maintenance. 2022;2:168-172. 10.37394/232022.2022.2.22
Copy to Clipboard
Citation copied to Clipboard

Certification

---