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Parametric spectral estimation to detect and diagnose faults in low speed rolling element bearings: Preliminary investigations

โœ Scribed by C.K. Mechefske; J. Mathew

Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
655 KB
Volume
7
Category
Article
ISSN
0888-3270

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โœฆ Synopsis

The monitoring of low speed bearings (~<100 rpm) is fraught with difficulties, not the least of which is the impracticality of recording sufficiently long periods of data for appropriate data analysis to be performed. Based on current fast Fourier transform (FFT) techniques, it would be normal to analyse data for several minutes if low frequency bandwidths are being investigated. A parametric model based approach could reduce the data acquisition period to a fraction of the time taken by the FFT technique. This paper presents a brief review of the parametric spectral estimation method, as well as report on some preliminary Work that compares the two methods when applied to low speed rolling element bearings.

๐Ÿ“œ SIMILAR VOLUMES

Fault detection and diagnosis in low spe
Fault detection and diagnosis in low speed rolling element bearings using inductive inference classification
โœ C.K. Mechefske; J. Mathew ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 516 KB

An effective procedure for the early detection and objective diagnosis of faults in rolling element bearings is described. The procedure involves the use of an inductive inference theory based classification program called 'Snob'. The program objectively divides frequency spectra into classes repres