Fuzzy-Bayesian network for refrigeration compressor performance prediction and test time reduction

被引：21

作者：

Penz, Cesar A. ^{[1
]}

Flesch, Carlos A. ^{[1
]}

Nassar, Silvia M. ^{[2
]}

Flesch, Rodolfo C. C. ^{[3
]}

de Oliveira, Marco A. ^{[4
]}

机构：

[1] Univ Fed Santa Catarina, Dep Engn Mecanica, BR-88040970 Florianopolis, SC, Brazil

[2] Univ Fed Santa Catarina, Dep Informat & Estat, BR-88040900 Florianopolis, SC, Brazil

[3] Univ Fed Santa Catarina, Dep Automacao & Sistemas, BR-88040900 Florianopolis, SC, Brazil

[4] Unidade EMBRACO, Whirlpool SA, BR-89219901 Joinville, SC, Brazil

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 04期

关键词：

Fuzzy-Bayesian networks; Refrigeration compressor; Performance test; Time reduction; Test prediction;

D O I：

10.1016/j.eswa.2011.09.107

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A typical characteristic of refrigeration compressor performance tests is their long duration. A reduction in the time periods related to this activity can be achieved using unsteady-state data analysis. This paper presents an original approach to predicting compressor performance using Bayesian networks and a hybrid Fuzzy-Bayesian network. All analysis was performed using real test data. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：4268 / 4273

页数：6

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