Development of Image-Based Drill Bit Wear Detection System for Drilling Application

Author:

Ibrahim M. F.,Mahmod M. F.ORCID,Bakar E. A.ORCID

Publisher

Springer Nature Singapore

Reference13 articles.

1. Jie, X.: Drilling process monitoring drill wear prediction and drilling conditions recognition with newly generated features, Doctoral Dissertation, Hiroshima University, Japan (2014)

2. Jantunen, E.: A summary of methods applied to tool condition monitoring in drilling. Int. J. Mach. Tools Manuf. 42(9), 997–1010 (2002)

3. Lauro, C.H., Brandão, L.C., Baldo, D., Reis, R.A., Davim, J.P.: Monitoring and processing signal applied in machining processes - a review. Meas. J. Int. Meas. Confed. 58, 73–86 (2014)

4. Teti, R., Jemielniak, K., O’Donnell, G., Dornfeld, D.: Advanced monitoring of machining operations, CIRP Ann. Manuf. Technol., 59, 717–739 (2010)

5. Haghighi, H.S.: Study on the effect of tool nose wear on surface roughness and dimensional deviation of workspiece in finish turning using machine vision, Thesis book, Universiti Sains Malaysia, Malaysia (2008)

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