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논문검색

A Hybrid Fault Diagnosis Approach for Hydraulic Systems by using Radial basis Function Networks

초록

영어

To improve the reliability of hydraulic systems, a fault diagnosis approach based on radial basis function (RBF) networks was proposed in this paper. According to the target fault features extracted from a fuzzy auto-regressive with extra outputs (FARX) model, RBF networks serve as a fault classifier and the output of the RBF networks is the result of fault diagnosis. Several typical faults of hydraulic systems were used to test the fault diagnosis approach. Experiment results showed that the fault diagnosis approach is feasible and effective for improving the reliability of hydraulic systems.

목차

Abstract
 1. Introduction
 2. RBF Networks
 3. FARX Model
  3.1. Structure of ARX
  3.2. Fault Feature Extraction Approach
 4. Fault Diagnosis
 5. Experiment
 6. Summary
 Acknowledgements
 References

저자정보

  • Xiang-yu He State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, 310027, China, Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle of Education Department of Hunan Province, Changsha University of Science and Technology, Changsha, Hunan, 410004 China
  • Yijiao Yang Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle of Education Department of Hunan Province, Changsha University of Science and Technology, Changsha, Hunan, 410004 China
  • Shanghong He Shanghong He2. Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle of Education Department of Hunan Province, Changsha University of Science and Technology, Changsha, Hunan, 410004 China

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