DSpace@nitr >
National Institue of Technology- Rourkela >
Conference Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/548

Title: Prediction of Drill Flank Wear Using Radial Basis Function Neural Network
Authors: Panda, S S
Charkraborty, D
Pal, S K
Keywords: Neuron
Centre Vector
sensor signal
Flank Wear
Issue Date: 2006
Publisher: NITR, Rourkela
Citation: Proceedings of the National Conference on Soft computing Techniques for Engineering Applications, SCT-2006, 24-26 March 2006, NIT, Rourkela
Abstract: In the present work, different type of artificial neural network (ANN) architectures have been used in an attempt to predict flank wear in drill bits. Flank wear in drill bit depends upon speed, federate, drill diameter and hence these parameters along with other derived parameters such as thrust force and torque have been used to predict flank wear using ANN. The results obtained from different ANN architectures have been compared and some useful conclusions have been made.
Description: Copyright for the published Version belongs to NITR
URI: http://hdl.handle.net/2080/548
Appears in Collections:Conference Papers

Files in This Item:

File Description SizeFormat
sspanda-NITR-1.pdf1187KbAdobe PDFView/Open

Show full item record

All items in DSpace are protected by copyright, with all rights reserved.


Powered by DSpace Feedback