Method of controlling cutting tool wear based on signal analysis of acoustic emission for milling

被引：26
|
作者：
Pechenin, Vadim A. [1 ]
Khaimovich, Alexander I. [1 ]
Kondratiev, Alexsandr I. [1 ]
Bolotov, Michael A. [1 ]
机构：
[1] Samara Natl Res Univ, Moskovskoe Shosse 34, Samara 443086, Russia
来源：
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON DYNAMICS AND VIBROACOUSTICS OF MACHINES (DVM2016) | 2017年 / 176卷
关键词：
acoustic emission; tool wear; nonstationary system; adaptive system; wavelet transform; CWT; WAVELET-BASED APPROACH; SOUND SIGNALS; IDENTIFICATION; SYSTEMS;
D O I：
10.1016/j.proeng.2017.02.294
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this paper, a tool wear diagnostic system based on the information contained in the signal of acoustic emission (AE) is considered. In the process, experiments on milling of steel billets 1035 were carried out, with the reference values of cutting force being dynamically monitored with the help of a Kistler 9257B multi-component dynamometer. Registration of the AE signal is performed by an LTR22 modular data acquisition system equipped with an OKTAFON 110 sensor. The method of useful signal filtering from the entire spectrum of AE is carried out using wavelet decomposition. Detection of necessary time periods from the decomposed milling AE signal is suggested for further analysis based on Fourier analysis. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：246 / 252
页数：7
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