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Fault Diagnosis and Analysis of Hydraulic System Based on Partial Least Squares Method

  • Xiaoming Wang*
  • , Rui Xiong
  • , Jiashan Gao
  • , Xingjian Wang
  • *Corresponding author for this work
  • Beijing Institute of Aerospace Systems Engineering
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The hydraulic system is widely used as power mechanism and actuation system in large-scale industrial equipment. The strong coupling between system circuits and different fault mechanisms make fault diagnosis difficult. In order to address these issues, a fault diagnosis method based on partial least squares is proposed for hydraulic system. The AMESim simulation platform is used to simulate the fault status of hydraulic components, generate fault data, and combine partial least squares to establish a regression equation between process variables and fault types for discriminative analysis of hydraulic system fault types. The simulation results indicate that the partial least squares method can achieve process variable data fusion, extract fault features, and complete the detection, separation, and recognition of fault types.

Original languageEnglish
Title of host publication2023 3rd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages374-379
Number of pages6
ISBN (Electronic)9798350303698
DOIs
StatePublished - 2023
Event3rd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023 - Hybrid, Nanjing, China
Duration: 21 Jul 202323 Jul 2023

Publication series

Name2023 3rd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023

Conference

Conference3rd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023
Country/TerritoryChina
CityHybrid, Nanjing
Period21/07/2323/07/23

Keywords

  • AMESim simulation modeling
  • Fault diagnosis
  • Hydraulic system
  • Partial least squares method
  • Process variables
  • component

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