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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F26%3A0198162" target="_blank" >RIV/00216305:26210/26:0198162 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2076-3417/15/12/6659" target="_blank" >https://www.mdpi.com/2076-3417/15/12/6659</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app15126659" target="_blank" >10.3390/app15126659</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20302 - Applied mechanics

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Applied Sciences-Basel

ISSN

—

e-ISSN

2076-3417

Volume of the periodical

15

Issue of the periodical within the volume

12

Country of publishing house

CH - SWITZERLAND

Number of pages

18

Pages from-to

1-18

UT code for WoS article

001515119300001

EID of the result in the Scopus database

2-s2.0-105008960242