dc.contributorUniv Naples Federico II
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-11T22:20:23Z
dc.date.accessioned2022-12-19T20:34:12Z
dc.date.available2020-12-11T22:20:23Z
dc.date.available2022-12-19T20:34:12Z
dc.date.created2020-12-11T22:20:23Z
dc.date.issued2018-01-01
dc.identifier11th Cirp Conference On Intelligent Computation In Manufacturing Engineering. Amsterdam: Elsevier Science Bv, v. 67, p. 307-312, 2018.
dc.identifier2212-8271
dc.identifierhttp://hdl.handle.net/11449/197859
dc.identifier10.1016/j.procir.2017.12.218
dc.identifierWOS:000552395600054
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5378493
dc.description.abstractThis work aims at determining the right moment to stop single-point dressing the grinding wheel in order to optimize the grinding process as a whole. Acoustic emission signals and signal processing tools are used as primary approach. An acoustic emission (AE) sensor was connected to a signal processing module. The AE sensor was attached to the dresser holder, which was specifically built to perform dressing tests. In this work there were three types of test where the edit parameters of each dressing test are: the passes number, the dressing speed, the width of action of the dresser, the dressing time and the sharpness. Artificial Neural Networks (ANNs) technique is employed to classify and predict the best moment for stopping the dressing operation. During the ANNs use, the results from Supervised Neural Networks and Unsupervised Neural Networks are compared. (C) 2017 The Authors. Published by Elsevier B.V.
dc.languageeng
dc.publisherElsevier B.V.
dc.relation11th Cirp Conference On Intelligent Computation In Manufacturing Engineering
dc.sourceWeb of Science
dc.subjectDressing
dc.subjectAcustic emission signal
dc.subjectVibration signal
dc.subjectTool wear
dc.subjectArtificial neural networks
dc.titleTool condition monitoring of single-point dressing operation by digital signal processing of AE and AI
dc.typeActas de congresos


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