The Study of EDG GH3536 Surface Roughness Base on the Artificial Neural Network Modeling

Ji Gao; Di Wang; Yao Sun

doi:10.4028/www.scientific.net/AMR.690-693.3175

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 690-693The Study of EDG GH3536 Surface Roughness Base on...

The Study of EDG GH3536 Surface Roughness Base on the Artificial Neural Network Modeling

Abstract:

The process parameters of electrical discharge grinding,such as workpiece polarity, pulse width, pulse interval, peak current, peak voltage, all have influence on GH3536’s surface roughness.General method is difficult to determine the relationship between the process parameters and the process indicators. This article established a artificial neural network model of EDG GH3536 surface roughness which can forecast. Neural network algorithm use BP algorithm, the network structure is the 2-4-1.

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Periodical:

Advanced Materials Research (Volumes 690-693)

Pages:

3175-3179

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.690-693.3175

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Online since:

May 2013

Authors:

Ji Gao, Di Wang, Yao Sun

Keywords:

Artificial Neural Network Model, Back Propagation (BP), Electrical Discharge Grinding (EDG), Surface Roughness (SR)

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