DocumentCode
2428308
Title
Monitoring of tool wear using artificial neural networks
Author
Venkatesh, Kurapati ; Zhou, MengChu ; Caudill, Reggie
Author_Institution
Center for Manuf. Syst., New Jersey Inst. of Technol., Newark, NJ, USA
Volume
3
fYear
1994
fDate
29 June-1 July 1994
Firstpage
2565
Abstract
An online scheme for tool wear monitoring using artificial neural networks (ANNs) has been proposed. Motivated by the fact that the tool wear at a given instance of time depends on the tool wear value at previous instance of time, memory was included in ANN. With this aim, an ANN without memory, an ANN with one phase memory, and an ANN with two are investigated in this study. The advantages and unique characteristics of the proposed tool wear modeling scheme with earlier methods of tool wear estimation are discussed.
Keywords
computerised monitoring; machine tools; manufacturing data processing; neural nets; real-time systems; wear; machine tools; neural networks; online scheme; tool wear monitoring; Adaptive control; Artificial neural networks; Condition monitoring; Machine tools; Machining; Manufacturing systems; Surface finishing; Switches; Training data; Wearable sensors;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1994
Print_ISBN
0-7803-1783-1
Type
conf
DOI
10.1109/ACC.1994.735022
Filename
735022
Link To Document