This work seeks to study the potential effectiveness of Fourier-Bessel (FB) series expansion for gear fault diagnostics. FB series expansion is a method for cross-terms suppression in Wigner-Ville distribution (WVD). In particular, FB series expansion is used as a signal decomposition technique in order to subdivide the signal into its components before WVD evaluation. The pros and cons of this method are highlighted by the analysis of experimental results. In particular two case studies are taken into account: a fatigue crack at the tooth root and spalls of different sizes. The presented results highlight the conditions in which FB decomposition technique is effective in WVD cross-term suppression, the limitations, as well as the advantages in terms of fault identification.
On the Use of Fourier-Bessel Series Expansion for Gear Diagnostics / D'Elia, Gianluca; Delvecchio, Simone; Dalpiaz, Giorgio. - (2012), pp. 267-275. (Intervento presentato al convegno Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations" CMMNO’2012 tenutosi a Hammamet, Tunisia nel 26-28 March 2012) [10.1007/978-3-642-28768-8].
On the Use of Fourier-Bessel Series Expansion for Gear Diagnostics
D'ELIA, Gianluca;DELVECCHIO, Simone;DALPIAZ, Giorgio
2012
Abstract
This work seeks to study the potential effectiveness of Fourier-Bessel (FB) series expansion for gear fault diagnostics. FB series expansion is a method for cross-terms suppression in Wigner-Ville distribution (WVD). In particular, FB series expansion is used as a signal decomposition technique in order to subdivide the signal into its components before WVD evaluation. The pros and cons of this method are highlighted by the analysis of experimental results. In particular two case studies are taken into account: a fatigue crack at the tooth root and spalls of different sizes. The presented results highlight the conditions in which FB decomposition technique is effective in WVD cross-term suppression, the limitations, as well as the advantages in terms of fault identification.
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