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�������պ����ѧѧ�� 2011, Vol. 37 Issue (11) :1410-1414    DOI:
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��ޱ, ����Ƽ*
�������պ����ѧ �Զ�����ѧ���������ѧԺ, ���� 100191
Wear condition prediction of hydraulic pump
Ge Wei, Wang Shaoping*
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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Abstract�� 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.
Keywords�� aero hydraulic pump   wear prediction   multi-dimensional support vector machine   data decomposition   phase space reconstruction     
Received 2010-07-20;

����863�ƻ�������Ŀ(2009AA04Z412); ���մ��»���������Ŀ(08D51010); 111�ƻ�������Ŀ

About author: �� ޱ(1985-),Ů,�ӱ�ʯ��ׯ��,˶ʿ��,gewei.buaa@gmail.com.
��ޱ, ����Ƽ.����Һѹ��ĥ��״��Ԥ��[J]  �������պ����ѧѧ��, 2011,V37(11): 1410-1414
Ge Wei, Wang Shaoping.Wear condition prediction of hydraulic pump[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2011,V37(11): 1410-1414
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2011/V37/I11/1410
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