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Titolo:
Development of parameter based fault detection and diagnosis technique forenergy efficient building management system
Autore:
Kumar, S; Sinha, S; Kojima, T; Yoshida, H;
Indirizzi:
Seikei Univ, Fac Engn, Dept Ind Chem, Musashino, Tokyo 1808633, Japan Seikei Univ Musashino Tokyo Japan 1808633 Musashino, Tokyo 1808633, Japan Kyoto Univ, Dept Global Environm Engn, Sakyo Ku, Kyoto 60601, Japan Kyoto Univ Kyoto Japan 60601 Environm Engn, Sakyo Ku, Kyoto 60601, Japan
Titolo Testata:
ENERGY CONVERSION AND MANAGEMENT
fascicolo: 7, volume: 42, anno: 2001,
pagine: 833 - 854
SICI:
0196-8904(200105)42:7<833:DOPBFD>2.0.ZU;2-#
Fonte:
ISI
Lingua:
ENG
Keywords:
fault detection and diagnosis; autoregressive exogenous model; variable air volume faults; air handling unit;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
--discip_BC--
Citazioni:
8
Recensione:
Indirizzi per estratti:
Indirizzo: Kojima, T Seikei Univ, Fac Engn, Dept Ind Chem, 3-3-1 Kichijoji,Kitamachi,Musashino, Tokyo 1808633, Japan Seikei Univ 3-3-1 Kichijoji,Kitamachi Musashino Tokyo Japan 1808633
Citazione:
S. Kumar et al., "Development of parameter based fault detection and diagnosis technique forenergy efficient building management system", ENERG CONV, 42(7), 2001, pp. 833-854

Abstract

This paper presents a complete methodology for detection and diagnosis of faults in variable air volume air handling units, Three cases are considered: (a) an off-line fault detection technique for existing buildings, (b) anautomatic on-line fault detection technique for integration in building management systems (BMSs) of upcoming not very complex buildings and (c) an automatic on-line fault detection as well as diagnosis technique for BMSs ofupcoming complex automated buildings. The method is based upon the auto regressive exogenous model and recursive parameter estimation algorithm. The proposed model and methodology have been trained by using several days of normal real time operational data and validated on data obtained by introducing faults artificially under normal operating conditions, It is concluded that the method is robust and can detect faults in dampers, sensors and PIDcontrol. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Documento generato il 05/04/20 alle ore 00:37:07