• DocumentCode
    3583472
  • Title

    Research on air-conditioning fault diagnosis method based on SVM

  • Author

    Li Yang ; Fang Qiansheng ; Wang Xiaolong ; Zhang Zhenya ; Xie Chenlei

  • Author_Institution
    Anhui Key Lab. of Intell. Building, Anhui Univ. of Archit., Hefei, China
  • Volume
    7
  • fYear
    2010
  • Firstpage
    3397
  • Lastpage
    3400
  • Abstract
    Air-conditioning system is an important component of the building equipment, but also a large energy consumption item of building. The accurate and timely air-conditioning fault diagnosis will guarantee the stable operation of the air-conditioning, which fulfils key functions in construction energy conservation, but now the bottleneck of fault diagnosis technology of air-conditioning is lack of fault samples, therefore, this paper puts forward an air-conditioning fault diagnosis method based on SVM , which can realize the SVM Multi-fault classifier through diagnosis of the typical faults in air conditioning system, it shows that the designed system has good classification accuracy and generalization ability.
  • Keywords
    air conditioning; energy conservation; fault diagnosis; support vector machines; SVM multi-fault classifier; air-conditioning fault diagnosis; energy conservation; support vector machines; Accuracy; Atmospheric modeling; Buildings; Fault diagnosis; Kernel; Support vector machines; Training; Air-conditioning system; Fault diagnosis; Multi-fault classifier; SVM (support vector machine);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583693
  • Filename
    5583693