Prediction of weight loss of various polyaryletherketones and their composites in three-body abrasive wear situation using artificial neural networks

被引：11

作者：

Harsha, A. P. ^{[1
]}

机构：

[1] Banaras Hindu Univ, Inst Technol, Dept Engn Mech, Varanasi 221005, Uttar Pradesh, India

[2] Delhi Coll Engn, Dept Engn Mech, Delhi 110042, India

来源：

JOURNAL OF REINFORCED PLASTICS AND COMPOSITES | 2007年 / 26卷 / 13期

关键词：

artificial neural networks; three-body abrasive wear; polymer composites; wear model;

D O I：

10.1177/0731684407079736

中图分类号：

TB33 [复合材料];

学科分类号：

摘要：

The objective of the present paper is to investigate the potential of an artificial neural network technique to predict the weight loss of various polyaryletherketones (PAEKs) and their composites in a three-body abrasive wear situation. Back-propagation neural networks have been used to predict the weight loss based on an experimental database in a three-body abrasive wear situation. The results show that the predicted data are perfectly acceptable when compared to the actual experimental test results. Hence a well-trained artificial neural networks (ANNs) system is expected to be very helpful for estimating the weight loss in the complex three-body abrasive wear situation of polymer composites.

引用

页码：1367 / 1377

页数：11

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