Investigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Milling

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dc.contributor.authorDado, Miroslavcs
dc.contributor.authorKoleda, Petercs
dc.contributor.authorVlašic, Františekcs
dc.contributor.authorSalva, Jozefcs
dc.coverage.issue12cs
dc.coverage.volume15cs
dc.date.accessioned2025-07-17T06:56:54Z
dc.date.available2025-07-17T06:56:54Z
dc.date.issued2025-06-13cs
dc.description.abstractThe integration of acoustic emission (AE) signals into adaptive control systems for CNC wood milling represents a promising advancement in intelligent manufacturing. This study investigated the feasibility of using AE signals for the real-time monitoring and control of CNC milling processes, focusing on medium-density fiberboard (MDF) as the workpiece material. AE signals were captured using dual-channel sensors during side milling on a five-axis CNC machine, and their characteristics were analyzed across varying spindle speeds and feed rates. The results showed that AE signals were sensitive to changes in machining parameters, with higher spindle speeds and feed rates producing increased signal amplitudes and distinct frequency peaks, indicating enhanced cutting efficiency. The statistical analysis confirmed a significant relationship between AE signal magnitude and cutting conditions. However, limitations related to material variability, sensor configuration, and the narrow range of process parameters restrict the broader applicability of the findings. Despite these constraints, the results support the use of AE signals for adaptive control in wood milling, offering potential benefits such as improved machining efficiency, extended tool life, and predictive maintenance capabilities. Future research should address signal variability, tool wear, and sensor integration to enhance the reliability of AE-based control systems in industrial applications.en
dc.formattextcs
dc.format.extent1-18cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationApplied Sciences - Basel. 2025, vol. 15, issue 12, p. 1-18.en
dc.identifier.doi10.3390/app15126659cs
dc.identifier.issn2076-3417cs
dc.identifier.orcid0000-0002-5283-2461cs
dc.identifier.other198162cs
dc.identifier.researcheridE-9838-2012cs
dc.identifier.scopus55607120100cs
dc.identifier.urihttps://hdl.handle.net/11012/255173
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofApplied Sciences - Baselcs
dc.relation.urihttps://www.mdpi.com/2076-3417/15/12/6659cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2076-3417/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectacoustic emissionen
dc.subjectadaptive controlen
dc.subjectCNCen
dc.subjectmillingen
dc.subjectwooden
dc.titleInvestigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Millingen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-198162en
sync.item.dbtypeVAVen
sync.item.insts2025.07.17 08:56:54en
sync.item.modts2025.07.17 08:33:50en
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. ÚK-odbor technické diagnostikycs
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