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基于 K-Means 聚类算法的数控机床铣削声音的声音检测监测工具。

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

机构信息

Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan.

Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.

出版信息

Sensors (Basel). 2021 Jun 23;21(13):4288. doi: 10.3390/s21134288.

DOI:10.3390/s21134288
PMID:34201656
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8296841/
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 , , and 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.

摘要

计算机数控（CNC）是制造业中用于快速生产工程领域所需组件或所需形状的机器。在 CNC 机床进行的铣削过程中，有时会发生振动，导致产生不需要的裂缝或损坏，如果不加以检查，将导致更严重的损坏。出于这个原因，本研究描述了如何监控和分析 CNC 在铣削过程中产生的声音。本研究使用了来自 YouTube 的六个声音样本视频，有两种模式：（1）操作模式是三个不同的形状，包括 、 和 轴，第二种（2）基于材料差异。即木材、泡沫塑料和塑料。使用已在 LabVIEW 中设计的声音检测程序，通过简单的麦克风来检测来自 CNC 铣削过程的所有样本产生的声音。所产生的声音频率将使用频谱测量中的快速傅里叶变换（FFT）过程进行分析，该过程将以图形的形式实时显示检测到的声音的幅度和频率。已从 CNC 铣床中的声音检测监控工具获得的所有频率结果都将导入到 K-均值聚类算法中，该算法将对共振频率和噪声之间的不同频率进行分类。根据进行的实验，声音检测程序可以检测到具有显著灵敏度的声音。

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