Investigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Milling
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced machining processes and optimization · Manufacturing Process and Optimization · Engineering Technology and Methodologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Manufacturing Technology and Quality Management, Faculty of Technology, Technical University in Zvolen, Študentská 26, 960 01 Zvolen, Slovakia
Department of Manufacturing and Automation Technology, Faculty of Technology, Technical University in Zvolen, Študentská 26, 960 01 Zvolen, Slovakia
Institute of Machine and Industrial Design, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 61669 Brno, Czech Republic
Department of Environmental Engineering, Faculty of Ecology and Environmental Sciences, Technical University in Zvolen, T. G. Masaryka 24, 960 01 Zvolen, Slovakia
Funding
Slovak Research and Development Agency
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