کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
384531 660848 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM
چکیده انگلیسی

A wire electrical discharge machined (WEDM) surface is characterized by its roughness and metallographic properties. Surface roughness and white layer thickness (WLT) are the main indicators of quality of a component for WEDM. In this paper an adaptive neuro-fuzzy inference system (ANFIS) model has been developed for the prediction of the white layer thickness (WLT) and the average surface roughness achieved as a function of the process parameters. Pulse duration, open circuit voltage, dielectric flushing pressure and wire feed rate were taken as model’s input features. The model combined modeling function of fuzzy inference with the learning ability of artificial neural network; and a set of rules has been generated directly from the experimental data. The model’s predictions were compared with experimental results for verifying the approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 3, Part 2, April 2009, Pages 6135–6139
نویسندگان
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