期刊
COMPUTERS & INDUSTRIAL ENGINEERING
卷 53, 期 1, 页码 30-42出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2006.06.018
关键词
fuzzy-nets; surface roughness prediction; turning
This paper discusses the development of a surface roughness prediction system for a turning operation, using a fuzzy-nets modeling technique. The goal is to develop and train a fuzzy-nets-based surface roughness prediction (FN-SRP) system that will predict the surface roughness of a turned workpiece using accelerometer measurements of turning parameters and vibration data. The FN-SRP system has been developed using a computer numerical control (CNC) slant-bed lathe with a carbide cutting tool. The system was trained using feed rate, spindle speed, and tangential vibration data collected during experimental runs. A series of validation runs indicate that this system has a mean accuracy of 95%. (c) 2007 Elsevier Ltd. All rights reserved.
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