Prediction of tool wear in high speed machining using acoustic emission technique and neural network

Indian Journal of Engineering and Materials Sciences

Volumn 13, Issue 4, 2006, Pages 275-280

  Giriraj, B ^a   Prabhu Raja, V ^a   Gandhinadhan, R ^a   Ganeshkumar, R ^a  

^a PSG COLLEGE OF TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC EMISSION TECHNIQUES; CUTTING PARAMETERS; FULLY AUTOMATED; HIGH SPEED MACHINING; QUICK RESPONSE TIME; SURFACE FINISHES; TAGUCHI'S DESIGN OF EXPERIMENTS; TOOL WEAR MONITORING;

ACOUSTIC EMISSIONS; DESIGN OF EXPERIMENTS; EXPERIMENTS; FORECASTING; NEURAL NETWORKS;

WEAR OF MATERIALS;

EID: 33751055848     PISSN: 09714588     EISSN: 09751017     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Schultz H & Moriwaki T. CIRP, 41 (1992) 637.
2. Lopez de Lucalle L N, Lamikiz A. Sanehez J A & Cabnes I. PROL Instn Mech Eng, 215 (2001) 1257.
3. Cook N H, Subramanian K & Basile S A. Survey of the state of art of tool wear sensing techniques, MIT report prepared under NSF Grant No. GI-43861, 1975.
4. Michcletti, G F, Koenig W & Victor H R, CIRP, 25 (1976) 483.
5. Elijah Kannatey- Asibu, Jr, Acoustic Emission Signal Analysis - A New Technique for Sensing Tool Wea, Ohis Valley Tool & Manufacturing Engineering Conference, 1981. 20-22.
6. Physical Acoustics Corporation. PCI-2 based AE system User's Manual, Revla, AMISTRAS Holding Company, 2003.
7. Xiaoli Li, Machine Tools Manuf, 42 (2002) 157.
8. Chungchoo C & Saini D. Machine Tools Manuf, 42 (2002) 29.
9. IS: 8688-2-1989(E). Tool wear in end Milling Cutter.