Investigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Milling
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Date
2025-06-13
Authors
Dado, Miroslav
Koleda, Peter
Vlašic, František
Salva, Jozef
ORCID
0000-0002-5283-2461Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
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Abstract
The 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.
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Citation
Applied Sciences - Basel. 2025, vol. 15, issue 12, p. 1-18.
https://www.mdpi.com/2076-3417/15/12/6659
https://www.mdpi.com/2076-3417/15/12/6659
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en