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Sound Detection Monitoring Tool in CNC Milling Sounds by K-Means Clustering Algorithm.

Authors
  • Peng, Cheng-Yu1
  • Raihany, Ully1
  • Kuo, Shu-Wei2
  • Chen, Yen-Zuo1
  • 1 Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan. , (Taiwan)
  • 2 Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan. , (Taiwan)
Type
Published Article
Journal
Sensors
Publisher
MDPI AG
Publication Date
Jun 23, 2021
Volume
21
Issue
13
Identifiers
DOI: 10.3390/s21134288
PMID: 34201656
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Computer numerical control (CNC) is a machine used in the manufacturing industry to produce components quickly for the engineering field or the desired shape. In the milling process carried out by CNC machines, sometimes vibrations occur that cause unwanted cracks or damage, which if left unchecked, will cause more severe damage. For this reason, this study describes how to monitor and analyze the sound produced by CNC during the milling process. This study uses six sound sample videos from YouTube, and there are two modes: (1) the operating mode is three different shapes with XY, XZ, and XYZ axes, and the second (2) is based on material differences. Namely, wood, Styrofoam, and plastic. The sound generated from all samples of the CNC milling processes will be detected using a sound detection program that has been designed in the LabVIEW using a simple microphone. The resulting sound frequency will be analyzed using the fast Fourier transform (FFT) process in spectral measurements, which will produce the amplitude and frequency of the detected sound in real time in the form of a graph. All frequency results that have been obtained from the sound detection monitoring tool in the CNC milling machine will be imported into the K-means clustering algorithm where the different frequencies between the resonant frequency and noise will be classified. Based on the experiments conducted, the sound detection program can detect sounds with a significant level of sensitivity.

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