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   Fault Diagnosis of a Hydraulic Power System Using an Artificial Neural Network  
   
نویسنده El-Betar Ahemd ,Abdelhamed Magdy M. ,El-Assal Ahmed ,Abdelsatar Roubi
منبع journal of king abdulaziz university : engineering sciences - 2006 - دوره : 17 - شماره : 1 - صفحه:113 -117
چکیده    This paper deals with the problem of fault detection, isolation and identification of a hydraulic power system. a proposed fault diagnostic scheme (fds) using an artificial neural network (ann) is investigated. a feedforward neural network is employed to diagnose two commonly occurring faults of the hydraulic power system: actuator internal leakage and valve spool blockage. the characterizing model of each fault is derived. the fault diagnostic scheme is applied to a hydraulic power test rig to diagnose real encountered faults. the ann based fds has been trained with sufficient data of the faults. extensive experiments have been carried out and their results are presented and discussed. the experimental results have showed that the trained network has the capability to detect and identify various severity magnitudes of the faults of interest. furthermore, the trained ann based fds has the ability to identify fault levels of untrained fault cases accurately. therefore, the validity of the proposed fds as a diagnostic tool for the hydraulic actuator internal leakage and the valve blockage has been assured. finally, the proposed fault diagnostic scheme can be practically implemented.
کلیدواژه Fault diagnostic technique ,artificial neural network ,hydraulic actuator ,oil leakage and valve spool blockage
آدرس Benha High Institute of Technology, Egypt, Ain Shams University, Design &ProductionEngineering Department, Egypt, Benha High Institute of Technology, Egypt, Benha High Institute of Technology, Egypt
 
     
   
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