A Predictive Preference Model for Maintenance of a Heating Ventilating and Air Conditioning System

被引：7

作者：

Tehrani, Mandi Mohammadi ^{[1
]}

Beauregard, Yvan ^{[1
]}

Rioux, Michel ^{[2
]}

Kenne, Jean Pierre ^{[1
]}

Ouellet, Rejean ^{[3
]}

机构：

[1] ETS Univ, Dept Mech Engn, 1100 Ave Yotre Dame West, Montreal, PQ H3C 1K3, Canada

[2] ETS Univ, Engn Dept Automated Prod, 1100 Ave Yotre Dame West, Montreal, PQ H3C 1K3, Canada

[3] Matricis Informat Inc, Integrat Dept, 1425 Blvd Rene Levesque O, Montreal, PQ H3G 1T7, Canada

来源：

IFAC PAPERSONLINE | 2015年 / 48卷 / 03期

关键词：

Linear Regression; Neural Network; Predictive; Maintenance; HVAC system; NEURAL-NETWORKS; CLASSIFICATION; REGRESSION;

D O I：

10.1016/j.ifacol.2015.06.070

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Predicting next failure of the filler's differential pressure of heating ventilating and air conditioning (HVAC) system provides for a higher performance of the system. There exist various fluctuating parameters that contribute in this paramount prediction. In the current study, the traditional method of linear regression and artificial neural network are applied as means of prediction, and it is shown that the performance is improved shen supplemented with a decision tree approach. The outcome reveals which one can more effectively predict trends and behavioral patterns as well as maintenance requirement of such systems with limited considered attributes. Hence, the empirical data is retrieved and a new method for predictive maintenance illustrated using HVAC system of Ecole de technologie superieure (ETS). (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：130 / 135

页数：6

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