|Table of Contents|

Intelligent Prediction of E4303 Electrode Mechanical Properties Based on Fuzzy Neural Network

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2011年02期
Page:
218-223
Research Field:
Publishing date:

Info

Title:
Intelligent Prediction of E4303 Electrode Mechanical Properties Based on Fuzzy Neural Network
Author(s):
HUANG JunXU Yue-lan
School of Materials Science and Engineering,NUST,Nanjing 210094,China
Keywords:
carbon steel electrodes fuzzy neural network mechanical properties intelligent prediction
PACS:
TG422.1;TP183
DOI:
-
Abstract:
To acquire a prediction model reflecting the relationship between primary materials formula and the deposited metal mechanical properties of electrodes,formula design and resurfacing welding experiments are made on E4303 carbon steel electrode.Mechanical properties indexes of deposited metal including tensile strength,yield strength,elongation percentage,impacting works are also measured.Using the method of adaptive fuzzy neural network,a model for predicting electrode mechanical properties directly from primary material components is built.The model is used to predict the experiment data except training samples.Results show that the prediction average relative errors of tensile strength and yield strength are all below 5%,the prediction average absolute error of elongation percentage is only 0.021,the predicting effect of impacting works is improved compared with that using the BP network.This fuzzy neural network prediction model can accurately predict the deposited metal mechanical properties directly from primary material components.

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Last Update: 2012-04-30