• DocumentCode
    3763347
  • Title

    Intelligent online sensor monitoring and fault alarm system in heating ventilation and air conditioning systems

  • Author

    Ying Guo;Josh Wall;Jiaming Li;Sam West

  • Author_Institution
    Digital Productivity Flagship, The Commonwealth Scientific and Industrial Research Organisation, Marsfield, NSW 2122, Australia
  • fYear
    2015
  • Firstpage
    789
  • Lastpage
    794
  • Abstract
    The heating, ventilation, and air conditioning (HVAC) system is designed to provide thermal comfort and acceptable indoor air quality. A variety of sensing devices (such as temperature, humidity, velocity, or pressure sensors) are installed in the HVAC systems. In a realistic situation, the HVAC system can fail to satisfy performance expectations envisioned because of a variety of problems. This paper presents online sensor monitoring and fault detection techniques, as well as the key sensor sets selection approach to optimise the fault detection results. The methodology presented is also implemented in commercial buildings and experimental results show that different types of faults are detected successfully.
  • Keywords
    "Monitoring","Buildings","Fault detection","Hidden Markov models","Temperature sensors","Training"
  • Publisher
    ieee
  • Conference_Titel
    Sensing Technology (ICST), 2015 9th International Conference on
  • Electronic_ISBN
    2156-8073
  • Type

    conf

  • DOI
    10.1109/ICSensT.2015.7438504
  • Filename
    7438504