Monitoring the cutting condition of structurally distinct aluminum oxide grinding wheels using acoustic emission signals and the Hinkley criterion
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00170-024-13139-0.pdf
Reference28 articles.
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3. Sutowski P, Plichta S (2006) An investigation of the grinding wheel wear with the use of root-mean-square value of acoustic emission. Arch Civ Mech Eng 6(1):87–98
4. Nakai ME, Aguiar PR, Guillardi H, Bianchi EC, Spatti DH, D’Addona DM (2015) Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics. Expert Syst Appl 42(20):7026–7035. https://doi.org/10.1016/j.eswa.2015.05.008
5. Moia DFG, Thomazella IH, Aguiar PR, Bianchi EC, Martins CHR, Marchi M (2015) Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks. J Braz Soc Mech Sci Eng 63(3):627–640. https://doi.org/10.1007/s40430-014-0191-6
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