• DocumentCode
    2975787
  • Title

    Research on Fault Diagnosis Method of Pressurization System of Water-Jet Cutting Machine Based on Support Vector Machine

  • Author

    Zhang, Haixia ; Zhao, De-An ; Ji, Wei ; Kong, Deyuan ; Chen, Bo

  • Author_Institution
    Sch. of Electr. & Inf., Jiangsu Univ., Zhenjiang, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    1680
  • Lastpage
    1683
  • Abstract
    Water-jet cutting machine is one of the high-tech products setting of ultra-high pressure technology, numerical control technology, computer application technology as a whole, make use of the kinetic energy of abrasive water-jet cutting of various materials to achieve the purpose of cutting. It has advantages such as no chemical changes, no heat distortion, thin cutting gap, high accuracy, aspect bright and clean and clean pollution-free. Aiming at the problem of many kinds of fault and so difficult to obtain a large number of fault data samples on pressurization system of water-jet cutting machine. A new method of fault diagnose is proposed for pressurization system of water-jet cutting machine based on SVM-one to one classification, this method was used for building a multi-fault classifier on the training set. Then it is applied to fault diagnosis of pressurization system of four-axe linkage water-jet cutting machine, and the results show that it has high efficiency. And do not need to preprocess of the original signal to satisfy the need of on line diagnosis.
  • Keywords
    fault diagnosis; pattern classification; pressure; support vector machines; water jet cutting; computer application technology; fault data sample; fault diagnosis method; four axe linkage water jet cutting machine; heat distortion; high tech product; kinetic energy; multifault classifier; numerical control technology; pressurization system; support vector machine; thin cutting gap; ultra high pressure technology; water jet cutting machine; Circuit faults; Classification algorithms; Expert systems; Fault diagnosis; Feature extraction; Support vector machines; Training; Fault Diagnosis; Pressurization system of water-jet cutting machine; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.414
  • Filename
    5629652