Fault detection and diagnosis system for air-conditioning units using recurrent type neural network

Herath K U Samarasinghe; Shuji Hashimoto

Fault detection and diagnosis system for air-conditioning units using recurrent type neural network

Herath K U Samarasinghe^*, Shuji Hashimoto

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the system has been increased. At the same time, stability in the system and the low-running cost are demanded. To solve these problems, various researches have been done. The development of the energy load prediction systems and the faults detection and diagnosis systems have received greater attention. In this paper, we propose a real time fault diagnosis system for air conditioning units (the heating unit, the cooling unit, the air intake unit, and the air-recycling unit) using a recurrent type neural network.

Original language	English
Title of host publication	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publisher	IEEE
Pages	2637-2642
Number of pages	6
Volume	4
Publication status	Published - 2000
Event	2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA Duration: 2000 Oct 8 → 2000 Oct 11

Other

Other	2000 IEEE International Conference on Systems, Man and Cybernetics
City	Nashville, TN, USA
Period	00/10/8 → 00/10/11

ASJC Scopus subject areas

Hardware and Architecture
Control and Systems Engineering

Cite this

@inproceedings{7966afc8c8b54f92a4aff73e2aad4282,

title = "Fault detection and diagnosis system for air-conditioning units using recurrent type neural network",

abstract = "The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the system has been increased. At the same time, stability in the system and the low-running cost are demanded. To solve these problems, various researches have been done. The development of the energy load prediction systems and the faults detection and diagnosis systems have received greater attention. In this paper, we propose a real time fault diagnosis system for air conditioning units (the heating unit, the cooling unit, the air intake unit, and the air-recycling unit) using a recurrent type neural network.",

author = "Samarasinghe, {Herath K U} and Shuji Hashimoto",

year = "2000",

language = "English",

volume = "4",

pages = "2637--2642",

booktitle = "Proceedings of the IEEE International Conference on Systems, Man and Cybernetics",

publisher = "IEEE",

note = "2000 IEEE International Conference on Systems, Man and Cybernetics ; Conference date: 08-10-2000 Through 11-10-2000",

}

TY - GEN

T1 - Fault detection and diagnosis system for air-conditioning units using recurrent type neural network

AU - Samarasinghe, Herath K U

AU - Hashimoto, Shuji

PY - 2000

Y1 - 2000

N2 - The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the system has been increased. At the same time, stability in the system and the low-running cost are demanded. To solve these problems, various researches have been done. The development of the energy load prediction systems and the faults detection and diagnosis systems have received greater attention. In this paper, we propose a real time fault diagnosis system for air conditioning units (the heating unit, the cooling unit, the air intake unit, and the air-recycling unit) using a recurrent type neural network.

AB - The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the system has been increased. At the same time, stability in the system and the low-running cost are demanded. To solve these problems, various researches have been done. The development of the energy load prediction systems and the faults detection and diagnosis systems have received greater attention. In this paper, we propose a real time fault diagnosis system for air conditioning units (the heating unit, the cooling unit, the air intake unit, and the air-recycling unit) using a recurrent type neural network.

UR - http://www.scopus.com/inward/record.url?scp=0034511069&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034511069&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0034511069

VL - 4

SP - 2637

EP - 2642

BT - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

PB - IEEE

T2 - 2000 IEEE International Conference on Systems, Man and Cybernetics

Y2 - 8 October 2000 through 11 October 2000

ER -

Fault detection and diagnosis system for air-conditioning units using recurrent type neural network

Abstract

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this