Open Access
Issue
MATEC Web Conf.
Volume 249, 2018
2018 5th International Conference on Mechanical, Materials and Manufacturing (ICMMM 2018)
Article Number 02002
Number of page(s) 5
Section Mechanical System Modeling and Analysis
DOI https://doi.org/10.1051/matecconf/201824902002
Published online 10 December 2018
  1. F. A. Alexandre, W. N. Lopes, F. R. L. Dotto, F. I. Ferreira, P. R. Aguiar, E. C. E. C. Bianchi, and J. C. Lopes, “Tool condition monitoring of aluminum oxide grinding wheel using AE and fuzzy model,” Int. J. Adv. Manuf. Technol., vol. 1, pp. 1–13, Jan. 2018. [Google Scholar]
  2. V. Gopan, S. Ragavanantham, and S. Sampathkumar, “Condition Monitoring of Grinding Process Through Machine Vision system,” pp. 177–180, 2012. [Google Scholar]
  3. D. M. D’Addona, D. Matarazzo, P. R. De Aguiar, E. C. Bianchi, and C. H. R. Martins, “Neural Networks Tool Condition Monitoring in Single-point Dressing Operations,” Procedia CIRP, vol. 41, pp. 431–436, 2016. [CrossRef] [Google Scholar]
  4. W. N. Lopes, F. I. Ferreira, F. Alexandre, E. Bianchi, and P. R. Ribeiro, Danilo Santos; Junior, Pedro Conceição; Aguiar, “Digital Signal Processing of Acoustic Emission Signals Using Power Spectral Density and Counts Statistic Applied to Single-Point Dressing Operation,” IET Sci. Meas. Technol., p. 15, 2017. [Google Scholar]
  5. H. K. Tönshoff, T. Friemuth, and J. C. Becker, “Process Monitoring in Grinding,” CIRP Ann. - Manuf. Technol., vol. 51, pp. 551–571, 2002. [CrossRef] [Google Scholar]
  6. R. Teti, K. Jemielniak, G. O’Donnell, and D. Dornfeld, “Advanced monitoring of machining operations,” CIRP Ann. - Manuf. Technol., vol. 59, no. 2, pp. 717–739, 2010. [CrossRef] [Google Scholar]
  7. D. M. S. Ribeiro, P. R. Aguiar, L. F. G. Fabiano, D. M. D’Addona, F. G. Baptista, and E. C. Bianchi, “Spectra Measurements Using Piezoelectric Diaphragms to Detect Burn in Grinding Process,” IEEE Trans. Instrum. Meas., vol. 66, no. 11, pp. 3052–3063, Nov. 2017. [CrossRef] [Google Scholar]
  8. P. R. de Aguiar, E. Carlos, and R. Chinali, “Monitoring of Grinding Burn by Acoustic Emission,” in Acoustic Emission, W. Sikorski, Ed. InTech, 2012, pp. 341–364. [Google Scholar]
  9. M. Marchi, F. G. Baptista, P. R. de Aguiar, and E. C. Bianchi, “Grinding process monitoring based on electromechanical impedance measurements,” Meas. Sci. Technol., vol. 26, no. 4, p. 45601, 2015. [CrossRef] [Google Scholar]
  10. Q. Liu, X. Chen, and N. Gindy, “Fuzzy pattern recognition of AE signals for grinding burn,” Int. J. Mach. Tools Manuf., vol. 45, no. 7–8, pp. 811–818, 2005. [CrossRef] [Google Scholar]
  11. F. R. L. Dotto, P. R. De Aguiar, E. C. Bianchi, P. J. A. Serni, and R. Thomazella, “Automatic system for thermal damage detection in manufacturing process with internet monitoring,” J. Brazilian Soc. Mech. Sci. Eng., vol. 28, no. 2, pp. 153–160, 2006. [CrossRef] [Google Scholar]
  12. R. Deiva Nathan, L. Vijayaraghavan, and R. Krishnamurthy, “In-process monitoring of grinding burn in the cylindrical grinding of steel,” J. Mater. Process. Technol., vol. 91, no. 1, pp. 37–42, Jun. 1999. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.