Hybrid models for aluminium alloy properties prediction

被引：5

作者：

Abbod, MF

Zhu, Q

Linkens, DA

Sellars, CM

Mahfouf, M

机构：

[1] Univ Sheffield, Dept Automat Control & Syst Engn, Inst Microstruct & Mech Properties Engn, Sheffield S1 3JD, S Yorkshire, England

[2] Univ Sheffield, Dept Mech Engn, Inst Microstruct & Mech Properties Engn, Sheffield S1 3JD, S Yorkshire, England

[3] Univ Sheffield, Dept Mat Engn, Inst Microstruct & Mech Properties Engn, Sheffield S1 3JD, S Yorkshire, England

来源：

CONTROL ENGINEERING PRACTICE | 2006年 / 14卷 / 05期

基金：

英国工程与自然科学研究理事会;

关键词：

aluminium alloys; hybrid modelling; model validation; neuro-fuzzy models; prediction;

D O I：

10.1016/j.conengprac.2004.08.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a novel modelling approach based on a hybrid structure developed for predicting the material properties of aluminium alloys for different deformation conditions. The model is based on physical equations and neuro-fuzzy models. The paper describes the methodology for developing the hybrid model and the validation process which covers a wide range of alloys, treatment temperatures and deformation conditions (e.g. plane strain compression (PSC) tests, strain rate). (c) 2004 Elsevier Ltd. All rights reserved.

引用

页码：537 / 546

页数：10

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