A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

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Xiangyu He; Shanghong He;
  • Publisher: IFSA Publishing, S.L.
  • Journal: Sensors & Transducers (issn: 2306-8515, eissn: 1726-5479)
  • Publisher copyright policies & self-archiving
  • Subject: Technology (General) | Hydraulic system | Fault diagnosis | Artificial neural networks (ANNs) | General regression neural network (GRNN). | Nonlinear system | T1-995

Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then se... View more
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