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
收藏
页码：4268 / 4273
页数：6
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