Search:
Computing and Library Services - delivering an inspiring information environment

Vibro-Acoustic Characteristic of A Self Aligning Spherical Journal Bearing due to Eccentric Bore Fault

Raharjo, Parno, Abdusslam, S.A., Gu, Fengshou and Ball, Andrew (2012) Vibro-Acoustic Characteristic of A Self Aligning Spherical Journal Bearing due to Eccentric Bore Fault. In: CM 2012 and MFPT 2012: The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies , 12th - 14th June 2012, London, UK. (Unpublished)

[img]
Preview
PDF
23_Vibro-acoustic_Characteristic_of_a_self-aligning_spherical_journal_bearing_due_to_eccentric_bore_fault.pdf - Accepted Version

Download (645kB) | Preview

Abstract

Self aligning spherical journal bearing is a type of plain bearings which has spherical surface contact. This type of bearing can accommodate a misalignment problem. The journal bearing faults degrade machine performance, decrease life time service and unexpected failure which are dangerous for safety issues. Surface vibration (SV), airborne sound (AS) and acoustic emission (AE) measurements are appropriate monitoring methods for early stage journal bearing fault in low, medium and high frequency.
This paper focuses on the performance comparison between SV, AS and AE measurements in the self aligning spherical journal bearing with normal and eccentric bore faults. The dynamics of the bearing is studied to gain the generation and characteristics of SV, AS and AE, which allow the extraction of useful information for diagnosis. The results of SV, AS and AE experiments especially for self-aligning spherical journal bearing due to eccentric bore fault indicate that the spectrum can detect significantly distinct between normal and faulty bearing. The statistic parameters show that RMS value and Peak value for fault bearing is higher than normal bearing. Spectrum of SV, AS and SE showed significant differences between normal bearing and eccentric bore bearing.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Cherry Edmunds
Date Deposited: 11 Jul 2012 11:38
Last Modified: 11 Jul 2012 11:38
URI: http://eprints.hud.ac.uk/id/eprint/14202

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©