Volume 37 Issue 11
Nov.  2011
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Ge Wei, Wang Shaoping. Wear condition prediction of hydraulic pump[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(11): 1410-1414. (in Chinese)
Citation: Ge Wei, Wang Shaoping. Wear condition prediction of hydraulic pump[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(11): 1410-1414. (in Chinese)

Wear condition prediction of hydraulic pump

  • Received Date: 20 Jul 2010
  • Publish Date: 30 Nov 2011
  • Wear is a typical progressive failure of aero hydraulic pump. It is difficult to measure wear loss. To solve precision wear condition prediction problem, multi-dimensional support vector machine (SVM) prediction method was proposed, based on theoretical basis of SVM applied to time series prediction, multi-dimensional data decomposition and phase space reconstruction. The inner relationship of time series can be mined and reflected more effectively by this method. Oil-return flow was chosen to reflect the wear condition of hydraulic pump and was decomposed into trend data and random data. Multi-dimensional SVM was applied to predict oil-return flow of the aero hydraulic pump one-step ahead and multi-step ahead with grid search optimization method. The results show that multi-dimensional SVM model has higher prediction precision and is very suitable for long-term forecasting compared with the predicted results of traditional SVM.

     

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