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

Herath K U Samarasinghe, Shuji Hashimoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 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 languageEnglish
    Title of host publicationProceedings of the IEEE International Conference on Systems, Man and Cybernetics
    PublisherIEEE
    Pages2637-2642
    Number of pages6
    Volume4
    Publication statusPublished - 2000
    Event2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA
    Duration: 2000 Oct 82000 Oct 11

    Other

    Other2000 IEEE International Conference on Systems, Man and Cybernetics
    CityNashville, TN, USA
    Period00/10/800/10/11

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Control and Systems Engineering

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  • Cite this

    Samarasinghe, H. K. U., & Hashimoto, S. (2000). Fault detection and diagnosis system for air-conditioning units using recurrent type neural network. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (Vol. 4, pp. 2637-2642). IEEE.