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A Fault-Diagnosis Algorithm-Embedded Controller Design for Hydraulic Solenoid Valves in Industrial Applications
  • Yoo, Seungjin ;
  • Jung, Joon Ha ;
  • Lee, Jai Kyung ;
  • Shin, Sang Woo ;
  • Jang, Dal Sik
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Publication Year
2024-01-01
Publisher
SpringerOpen
Citation
International Journal of Precision Engineering and Manufacturing
Keyword
ControllerFault diagnosisHydraulic solenoid valveMicroprocessorSoftware and hardware design
Mesh Keyword
Controller designsDiagnosis algorithmsEmbedded controllersFaults diagnosisFluid controlHardware designHydraulic solenoid valveMechanical partsSoftware and hardware designSoftware and hardwares
All Science Classification Codes (ASJC)
Mechanical EngineeringIndustrial and Manufacturing EngineeringElectrical and Electronic Engineering
Abstract
Hydraulic solenoid valves (HSVs) are widely used for fluid control in industrial applications. Like other mechanical parts, HSVs deteriorate and faults occur during their use in industrial settings. Although several prior fault-diagnosis methods have been proposed to detect these faults, previous studies have not considered the actual implementation of the methods on the controller. Thus, to ensure reliable operation of HSVs in the field, this research paper presents an innovative HSV controller design that is able to process the proposed fault-diagnosis algorithm. In the proposed work, the hardware is designed to transmit and receive signals and data for the valve-diagnosis algorithm. For the software, an architecture is proposed to enable the fault-diagnosis algorithm to be processed in a conventional microprocessor. In this research, the proposed controller design was built and tested on an actual hydraulic system. The results show that the proposed fault-diagnosis algorithm has been successfully embedded in the microcontroller.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34419
DOI
https://doi.org/10.1007/s12541-024-01108-2
Fulltext

Type
Article
Funding
This work was supported by a project of the Industry-University-Research Institute platform cooperation R&D funded by the Korea Ministry of SMEs and Startups in 2022. (S3310924)
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Jung, Joon Ha Image
Jung, Joon Ha정준하
Department of Industrial Engineering
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