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Journal bearing lubrication monitoring based on spectrum cluster analysis of vibration signals

Hassin, Osama, Wei, Nasha, Towsyfyan, Hossein, Gu, Fengshou and Ball, Andrew (2015) Journal bearing lubrication monitoring based on spectrum cluster analysis of vibration signals. In: 28th International Congress of Condition Monitoring and Diagnostic Engineering Management (COMADEM 2015), 1st - 4th December 2015, Buenos Aires, Argentina.

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Journal bearings are critical components for many important machines. Lubrication analysis techniques are often not timely and cost effective for monitoring journal bearings. This research investigates into vibration responses of such bearings using a clustering technique for identifying different lubrication regimes, and consequently for assessing bearing lubrication conditions. It firstly understands that the vibration sources are mainly due to the nonlinear effects including micro asperity collisions and fluid shearing interactions. These excitations together with complicated vibration paths are difficult to be characterized in a linear way for the purpose of condition monitoring. Therefore, a clustering analysis technique is adopted to classify the vibration spectrum in high frequency ranges around 10kHz into different representative responses that corresponds to different bearing modulus values and lubrication characteristics. In particular, the analysis allows sensitive signal components and sensor positions to be determined for monitoring the journal bearing effectively. Test results from self-aligning spherical journal bearings show that it allows different lubricant oils and different lubrication regimes to be identified appropriately, providing feasible ways to online monitoring bearing conditions.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
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Depositing User: Cherry Edmunds
Date Deposited: 10 Dec 2015 12:19
Last Modified: 28 Aug 2021 17:33


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