An automatic system based on vibratory analysis for cutting tool wear monitoring

被引:92
作者
Rmili, Wafaa [1 ]
Ouahabi, Abdeljalil [2 ]
Serra, Roger [3 ]
Leroy, Rene [1 ]
机构
[1] Univ Tours, PolytechTours, Lab Mecan & Rheol, EA 2640, F-37200 Tours, France
[2] Univ Tours, PolytechTours, Signal & Image Grp, F-37200 Tours, France
[3] INSA Ctr Val de Loire, Lab Mecan & Rheol, EA 2640, F-41034 Blois, France
关键词
Cutting tool wear measurement; Vibratory measurement; Wear indicator; Automatic detection system; TURNING OPERATIONS; ACOUSTIC-EMISSION;
D O I
10.1016/j.measurement.2015.09.010
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The aim of this work is to develop a new, simple to use and reliable automatic method for detection and monitoring wear on the cutting tool. To achieve this purpose, the vibratory signatures produced during a turning process were measured by using a three-axis accelerometer. Then, the mean power analysis was proposed to extract an indicator parameter from the vibratory responses, to be able to describe the state of the cutting tool over its lifespan. Finally, an automatic detector was proposed to evaluate and monitor tool wear in real time. This detector is efficient, simple to operate in an industrial environment and does not require any protracted computing time. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:117 / 123
页数:7
相关论文
共 19 条
[11]   An overview of approaches to end milling tool monitoring [J].
Prickett, PW ;
Johns, C .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 1999, 39 (01) :105-122
[12]   Acoustic emission for tool condition monitoring in metal cutting [J].
Ravindra, HV ;
Srinivasa, YG ;
Krishnamurthy, R .
WEAR, 1997, 212 (01) :78-84
[13]  
Rmili W, 2009, INT J ACOUST VIB, V14, P4
[14]   Wear monitoring in turning operations using vibration and strain measurements [J].
Scheffer, C ;
Heyns, PS .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2001, 15 (06) :1185-1202
[15]   A cutting power model for tool wear monitoring in milling [J].
Shao, H ;
Wang, HL ;
Zhao, XM .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2004, 44 (14) :1503-1509
[16]   On-line and indirect tool wear monitoring in turning with artificial neural networks: A review of more than a decade of research [J].
Sick, B .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2002, 16 (04) :487-546
[17]   Tool wear monitoring of turning operations by neural network and expert system classification of a feature set generated from multiple sensors [J].
Silva, RG ;
Reuben, RL ;
Baker, KJ ;
Wilcox, SJ .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1998, 12 (02) :319-332
[18]   On-line tool breakage monitoring in turning [J].
Wang, HL ;
Shao, H ;
Chen, M ;
Hu, DJ .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2003, 139 (1-3) :237-242
[19]  
Zieba S., 1995, THESIS