Gearbox fault identification under non-Gaussian noise and time-varying operating conditions

dc.contributor.authorSchmidt, Stephan
dc.contributor.authorChaari, Fakher
dc.contributor.authorZimroz, Radoslaw
dc.contributor.authorHeyns, P.S. (Philippus Stephanus)
dc.contributor.authorHaddar, Mohamed
dc.contributor.emailstephan.schmidt@up.ac.zaen_ZA
dc.date.accessioned2022-03-25T07:19:18Z
dc.date.available2022-03-25T07:19:18Z
dc.date.issued2021-05
dc.description.abstractThe Synchronous Average of the Squared Envelope (SASE) is very useful to visualise the periodicities in the instantaneous power of the machine due to damage. However, the SASE is sensitive to impulsive noise and the presence of non-synchronous damaged components and therefore provide unreliable representations of the condition of the gearbox under these conditions. Also, the instantaneous power is adversely affected by time-varying operating conditions. Impulsive noise and/or time-varying operating conditions can be encountered in the power generation (e.g. wind turbines) and mining industries (e.g. bucket wheel excavators). Hence, a method is proposed for impulsive data that were acquired under time-varying operating conditions. This method firstly estimates and removes the instantaneous power changes caused by the time-varying operating conditions, whereafter the Synchronous Geometric Average of the Squared Envelope (SGASE) is applied. A more numerically stable calculation of the SGASE is performed, which also provides further insights into its suitability for impulsive noise environments. The methodology is investigated on a bevel gearbox model that was simulated under time-varying operating conditions and an experimental dataset also acquired under time-varying conditions. The results indicate that the SGASE is to be preferred to the SASE for performing fault diagnosis in the presence of non-Gaussian noise.en_ZA
dc.description.departmentMechanical and Aeronautical Engineeringen_ZA
dc.description.librarianhj2022en_ZA
dc.description.sponsorshipThe South African and Tunisian authors acknowledge the South African and Tunisia Research Cooperation Programme 2019.en_ZA
dc.description.urihttps://www.springer.com/series/13418en_ZA
dc.identifier.citationSchmidt S., Chaari F., Zimroz R., Heyns P.S., Haddar M. (2021) Gearbox Fault Identification Under Non-Gaussian Noise and Time-Varying Operating Conditions. In: Feki N., Abbes M.S., Taktak M., Amine Ben Souf M., Chaari F., Haddar M. (eds) Advances in Acoustics and Vibration III. ICAV 2021. Applied Condition Monitoring, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-76517-0_1.en_ZA
dc.identifier.isbn978-3-030-76516-3 (print)
dc.identifier.isbn978-3-030-76517-0 (online)
dc.identifier.issn2363-6998 (online)
dc.identifier.issn2363-698X (print)
dc.identifier.other10.1007/978-3-030-76517-0_1
dc.identifier.urihttp://hdl.handle.net/2263/84646
dc.language.isoenen_ZA
dc.publisherSpringeren_ZA
dc.rights© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. The original publication is available at https://www.springer.com/series/13418.en_ZA
dc.subjectGearbox fault diagnosisen_ZA
dc.subjectSynchronous average of the squared envelope (SASE)en_ZA
dc.subjectSynchronous geometric average of the squared envelope (SGASE)en_ZA
dc.subject.otherEngineering, built environment and information technology articles SDG-04
dc.subject.otherSDG-04: Quality education
dc.subject.otherEngineering, built environment and information technology articles SDG-08
dc.subject.otherSDG-08: Decent work and economic growth
dc.subject.otherEngineering, built environment and information technology articles SDG-09
dc.subject.otherSDG-09: Industry, innovation and infrastructure
dc.subject.otherEngineering, built environment and information technology articles SDG-11
dc.subject.otherSDG-11: Sustainable cities and communities
dc.subject.otherEngineering, built environment and information technology articles SDG-12
dc.subject.otherSDG-12: Responsible consumption and production
dc.subject.otherEngineering, built environment and information technology articles SDG-13
dc.subject.otherSDG-13: Climate action
dc.titleGearbox fault identification under non-Gaussian noise and time-varying operating conditionsen_ZA
dc.typePostprint Articleen_ZA

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