Study on accurate tool wear monitoring based on acoustic emission signal

被引：0

作者：

Cui Yinhu ^{[1
]}

Wang Guofeng ^{[1
]}

Peng Dongbiao ^{[1
]}

Feng Xiaoliang ^{[1
]}

Zhang Lu ^{[1
]}

Liu Chang ^{[1
]}

机构：

[1] Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China

来源：

FOURTH INTERNATIONAL SEMINAR ON MODERN CUTTING AND MEASUREMENT ENGINEERING | 2011年 / 7997卷

关键词：

acoustic emission; wavelet packet decomposition; tool wear monitoring;

D O I：

10.1117/12.888609

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper presents an experimental study of the application of acoustic emission (AE) signal for tool wear monitoring in the milling of Ti-6Al-4V alloy. Experiments were conducted and the corresponding AE signals were captured under different tool wear status. Initial analysis reveals that the AE signal contains useful information about the mechanism of the tool wear and can reflect the changing of the cutting parameters as well which show that the AE signal can be used as a reliable means for accurate tool wear monitoring. The comparison with other kinds of sensor signals also shows that the AE signal is more suitable for online tool wear monitoring in industrial environment. Based on these conclusions, AE signal can be used as a reliable signal for accurate tool wear monitoring.

引用

页数：7

共 50 条

[1] ACOUSTIC EMISSION AS TOOL WEAR MONITORING
Duspara, Miroslav
Sabo, Kristian
Stoic, Antun
TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2014, 21 (05): : 1097 - 1101
[2] CLASSIFIER FUSION FOR ACOUSTIC EMISSION BASED TOOL WEAR MONITORING
Yum, Juil
Kim, Tae Hyuhg
Kannatey-Asibu, Elijah, Jr.
PROCEEDINGS OF THE ASME INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2012, 2012, : 805 - 812
[3] Tool wear monitoring based on the combination of machine vision and acoustic emission
Chen, Meiliang
Li, Mengdan
Zhao, Linfeng
Liu, Jiachen
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2023, 125 (7-8): : 3881 - 3897
[4] Tool wear monitoring based on the combination of machine vision and acoustic emission
Meiliang Chen
Mengdan Li
Linfeng Zhao
Jiachen Liu
The International Journal of Advanced Manufacturing Technology, 2023, 125 : 3881 - 3897
[5] Acoustic signal based tool wear monitoring system for belt grinding of superalloys
Chen, Junqi
Wang, Junwei
Zhang, Xiaoqiang
Cao, Feng
Chen, Xiaoqi
PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2017, : 1281 - 1286
[6] Chaotic characteristic analysis of tool wear acoustic emission signal
Guan, Shan
Peng, Chang
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2015, 31 (11): : 60 - 65
[7] Method of controlling cutting tool wear based on signal analysis of acoustic emission for milling
Pechenin, Vadim A.
Khaimovich, Alexander I.
Kondratiev, Alexsandr I.
Bolotov, Michael A.
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON DYNAMICS AND VIBROACOUSTICS OF MACHINES (DVM2016), 2017, 176 : 246 - 252
[8] Monitoring the tool wear in the turning process using acoustic emission
Diniz, Anselmo Eduardo
Pigari, Almir
1996, Braz Soc Mech Sci, Rio de Janeiro, Brazil (18):
[9] Acoustic emission analysis for tool wear monitoring in face milling
Pai, PS
Rao, PKR
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2002, 40 (05) : 1081 - 1093
[10] Study of sensitivity of acoustic emission technique with other techniques and sensitivities of acoustic emission parameters bn monitoring tool wear
Sampathkumar, S
Kandasami, GS
Venkataraman, NS
TRENDS IN NDE SCIENCE AND TECHNOLOGY - PROCEEDINGS OF THE 14TH WORLD CONFERENCE ON NDT (14TH WCNDT), VOLS 1-5, 1996, : 1921 - 1924

← 1 2 3 4 5 →