Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums

Simple item page
dc.contributor.authorKhan, Muhammad Ali
dc.contributor.authorShahid, Muhammad Atayyab
dc.contributor.authorAhmed, Syed Adil
dc.contributor.authorKhan, Sohaib Zia
dc.contributor.authorKhan, Kamran Ahmed
dc.contributor.authorAli, Syed Asad
dc.contributor.authorTariq, Muhammad
dc.date.accessioned2019-09-19T13:24:55Z
dc.date.available2019-09-19T13:24:55Z
dc.date.issued2019-05-31
dc.description.abstractFailure in gears, transmission shafts and drivetrains is very critical in machineries such as aircrafts and helicopters. Real time condition monitoring of these components, using predictive maintenance techniques is hence a proactive task. For effective power transmission and maximum service life, gears are required to remain in prefect alignment but this task is just beyond the bounds of possibility. These components are flexible, thus even if perfect alignment is achieved, random dynamic forces can cause shafts to bend causing gear misalignments. This paper investigates the change in energy levels and statistical parameters including Kurtosis and Skewness of gear mesh vibration and airborne sound signals when subjected to lateral and angular shaft misalignments. Novel regression models are proposed after validation that can be used to predict the degree and type of shaft misalignment, provided the relative change in signal RMS from an aligned condition to any misaligned condition is known.en_UK
dc.identifier.citationKhan M, Shahid M, Ahmed S, et al., (2019) Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums. Measurement. Volume 145, October 2019, pp. 419-435en_UK
dc.identifier.issn0263-2241
dc.identifier.urihttps://doi.org/10.1016/j.measurement.2019.05.088
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/14545
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGearboxen_UK
dc.subjectMisalignmenten_UK
dc.subjectPredictionen_UK
dc.subjectVibrationen_UK
dc.subjectAcousticen_UK
dc.titleGear misalignment diagnosis using statistical features of vibration and airborne sound spectrumsen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Gear_misalignment_diagnosis_using_statistical-2019.pdf
Size:
3.44 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)