Faculty Publications

Title

Neural networks-based in-process surface roughness adaptive control system in turning operations

Document Type

Conference

Journal/Book/Conference Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

3973 LNCS

First Page

970

Last Page

975

Abstract

Using a back-propagation neural networks algorithm and accelerometer sensor technique, this research developed an in-process surface roughness adaptive control (IPSRAC) system in turning operations. This system not only can predict surface roughness in real time, but can also provide an adaptive feed rate change in finishing turning to ensure the surface roughness can meet requirements. © Springer-Verlag Berlin Heidelberg 2006.

Original Publication Date

1-1-2006

DOI of published version

10.1007/11760191_142

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