• DocumentCode
    3478586
  • Title

    Fault Diagnosis of Electro-hydraulic Position Servo Closed-loop System Based on Support Vector Regression

  • Author

    Cao, Keqiang ; Zhang, Jianbang ; Hu, Liangmou

  • Author_Institution
    Univ. of Air Force Eng., Xian
  • fYear
    2007
  • fDate
    18-21 Aug. 2007
  • Firstpage
    3044
  • Lastpage
    3049
  • Abstract
    A fault diagnosis method is proposed for electro-hydraulic position closed-loop system based on support vector regression (SVR), a new class of kernel based techniques introduced within statistical learning theory and structural risk minimization. This new fault diagnosis approach leads to solving convex optimization problems and also the model complexity follows from this solution. By using the measurable parameters, the total fault diagnosis model and the partial fault diagnosis model of SVR for electro-hydraulic position closed-loop system are established. The simulation results show that this method can effectively detect the fault of electro-hydraulic position closed-loop system.
  • Keywords
    closed loop systems; electrohydraulic control equipment; fault diagnosis; optimisation; position control; regression analysis; servomechanisms; support vector machines; convex optimization problems; electro-hydraulic position servo closed-loop system; fault diagnosis; model complexity; statistical learning theory; structural risk minimization; support vector regression; Aerospace engineering; Aircraft propulsion; Control systems; Fault diagnosis; Mathematical model; Neural networks; Risk management; Servomechanisms; Support vector machine classification; Support vector machines; Closed-loop control system; Electro-hydraulic position servo system; Fault diagnosis; Support vector regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2007 IEEE International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-1531-1
  • Type

    conf

  • DOI
    10.1109/ICAL.2007.4339104
  • Filename
    4339104