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Cited 6 time in webofscience Cited 6 time in scopus
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A Review of Hydraulic Cylinder Faults, Diagnostics, and Prognostics

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dc.contributor.authorKumar, Prashant-
dc.contributor.authorPark, Sechang-
dc.contributor.authorZhang, Yongli-
dc.contributor.authorJo, Soo-Ho-
dc.contributor.authorKim, Heung Soo-
dc.contributor.authorKim, Taejin-
dc.date.accessioned2024-08-08T12:31:38Z-
dc.date.available2024-08-08T12:31:38Z-
dc.date.issued2024-09-
dc.identifier.issn2288-6206-
dc.identifier.issn2198-0810-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/22191-
dc.description.abstractHydraulic cylinders are typical actuators that are used in many industries, including manufacturing and construction machinery. Due to the wide application of cylinders, cylinder failures could increase maintenance costs, reduce productivity, and raise safety issues. Therefore, estimating and predicting the condition of cylinders is necessary for cost reduction and safety. This paper reviews various methods that have been proposed to estimate and predict cylinder failures. The paper first investigates the types of failures that can occur in cylinders and their causes. The failures include internal leakage, external leakage, and seal wear. The sensors used to identify each type of failure are then introduced. Since the failure information of the cylinder is implicitly embedded in the measured data, different diagnostics methods for isolating the failure information have been developed for each sensor. The diagnostic methods vary from traditional feature engineering to recent artificial intelligence-based methods. The prognostics that provide the remaining useful life of the cylinder are then reviewed. Finally, the paper discusses the challenges associated with the fault prognosis of hydraulic cylinders and future prospects.-
dc.format.extent25-
dc.language영어-
dc.language.isoENG-
dc.publisher한국정밀공학회-
dc.titleA Review of Hydraulic Cylinder Faults, Diagnostics, and Prognostics-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.1007/s40684-024-00639-3-
dc.identifier.scopusid2-s2.0-85196374867-
dc.identifier.wosid001251050700001-
dc.identifier.bibliographicCitationInternational Journal of Precision Engineering and Manufacturing-Green Technology, v.11, no.5, pp 1637 - 1661-
dc.citation.titleInternational Journal of Precision Engineering and Manufacturing-Green Technology-
dc.citation.volume11-
dc.citation.number5-
dc.citation.startPage1637-
dc.citation.endPage1661-
dc.type.docTypeReview-
dc.identifier.kciidART003114136-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryGreen & Sustainable Science & Technology-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.relation.journalWebOfScienceCategoryEngineering, Mechanical-
dc.subject.keywordPlusWAVELET-BASED APPROACH-
dc.subject.keywordPlusINTERNAL LEAKAGE-
dc.subject.keywordPlusPREDICTIVE MAINTENANCE-
dc.subject.keywordPlusSIGNATURE ANALYSIS-
dc.subject.keywordPlusFEATURE-EXTRACTION-
dc.subject.keywordPlusACTUATORS-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusTRANSFORM-
dc.subject.keywordPlusFOURIER-
dc.subject.keywordPlusMODELS-
dc.subject.keywordAuthorHydraulic cylinders-
dc.subject.keywordAuthorFaut detection-
dc.subject.keywordAuthorFault prognosis-
dc.subject.keywordAuthorArtificial intelligence-
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