Detection of Gear Wear and Faults in Spur Gear Systems Using Statistical Parameters and Univariate Statistical Process Control Charts

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dc.authoridBirgoren, Burak/0000-0001-9045-6092
dc.authoridARSLAN, HAKAN/0000-0002-2019-1882
dc.authoridMARAS, SINAN/0000-0002-2651-374X
dc.contributor.authorMaras, Sinan
dc.contributor.authorArslan, Hakan
dc.contributor.authorBirgoren, Burak
dc.date.accessioned2025-01-21T16:37:23Z
dc.date.available2025-01-21T16:37:23Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn this study, the detection of wear faults in spur gears was examined using vibration analysis, statistical process control method, and statistical parameters. For this purpose, a closed-loop test rig with a power transmission system was established. Defect-free gears were attached to the test assembly, and the system was operated at a specific torsional load and number of cycles until the gears were worn. Vibration amplitudes at vertical and horizontal directions, received via sensors on the bearings, were transferred to the computer with a digital-analog converter. The control charts were plotted by sampling 30 data points per hour. Upper and lower control limits were determined by using the data obtained from the defect-free gears. The gears are worn in the process due to the effect of applied torque and the operation conditions suitable for the formation of defects. As a result, the vibration amplitudes were increased. The accuracy and convergence of the statistical process control method were verified by the statistical parameters root mean square, kurtosis value, skewness value, crest factor, and peak-to-peak values. It was emphasized that great convergence and accuracy between the statistical process control results and statistical parameters results are achieved. The present study showed that the detection of abrasion of a robust gear could be graphically demonstrated through a real-time experimental study. The statistical process control method is convenient and easily applicable, which allows constructing a real-time early warning system detecting malfunctions at the start.
dc.identifier.doi10.1007/s13369-021-05930-y
dc.identifier.endpage12234
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue12
dc.identifier.scopus2-s2.0-85109306718
dc.identifier.scopusqualityQ1
dc.identifier.startpage12221
dc.identifier.urihttps://doi.org/10.1007/s13369-021-05930-y
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24469
dc.identifier.volume46
dc.identifier.wosWOS:000669821800001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofArabian Journal For Science and Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241229
dc.subjectSpur gears; Gear fault; Wear; Vibration; (X)over-bar-S charts; Statistical parameters; Generalized variance chart
dc.titleDetection of Gear Wear and Faults in Spur Gear Systems Using Statistical Parameters and Univariate Statistical Process Control Charts
dc.typeArticle

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