Lopes, Wenderson Nascimento [UNESP]Ferreira, Fabio Isaac [UNESP]Alexandre, Felipe Aparecido [UNESP]Santos Ribeiro, Danilo Marcus [UNESP]Conceicao Junior, Pedro de Oliveira [UNESP]Aguiar, Paulo Roberto de [UNESP]Bianchi, Eduardo Carlos [UNESP]2018-11-262018-11-262017-08-01Iet Science Measurement & Technology. Hertford: Inst Engineering Technology-iet, v. 11, n. 5, p. 631-636, 2017.1751-8822http://hdl.handle.net/11449/163043Dressing is an important operation for the grinding process. Its goal is to recondition the wheel tool to re-establish its cutting characteristics, owing to the wear produced after successive passes. Monitoring systems that use acoustic emission (AE) have been studied to correlate the signals with several tool conditions. This study brings a new approach of processing AE signals with the purpose of identifying the correct moment to stop the dressing, which is essential in an automatic control system. From the AE signals collected in dressing tests with aluminium oxide grinding wheel and single-point dresser, spectral analysis was made through power spectral density, selecting frequencies bands that best characterise the process. The statistical parameter counts' was applied to the raw signal unfiltered and filtered in the selected bands in order to identify the tool condition and, in turn, towards a monitoring system implementation. Results showed an expressive relation between tool cutting conditions and processed signals in the selected bands. There was a great disparity of the filtered signals in the selected bands and signals unfiltered, reflecting that the filtered ones were more efficient in terms of process automation.631-636enggrindingacoustic emissionsignal processingproduction engineering computingstatistical analysiswheelsgrinding machinescuttingwearcorrelation methodsproduction testingspectral analysisfiltering theorycutting toolsdigital signal processingacoustic emission signal processingpower spectral densitysingle-point dressing operationgrinding processwheel tool reconditioningAE monitoring systemAE signal processingautomatic control systemaluminium oxide grinding wheelsingle-point dressertool cutting conditionprocess automationArtigo10.1049/iet-smt.2016.0317WOS:000406147400013Acesso abertoWOS000406147400013.pdf14554003096600810000-0002-9934-4465