scispace - formally typeset
M

M. El Badaoui

Researcher at University of Lyon

Publications -  52
Citations -  1989

M. El Badaoui is an academic researcher from University of Lyon. The author has contributed to research in topics: Cyclostationary process & Signal. The author has an hindex of 18, co-authored 48 publications receiving 1761 citations. Previous affiliations of M. El Badaoui include Jean Monnet University.

Papers
More filters
Journal ArticleDOI

Cyclostationary modelling of rotating machine vibration signals

TL;DR: In this article, it is shown that vibration signals exhibit cyclostationarity if and only if the random speed fluctuation of the machine is periodic, stationary or cyclostatary.
Journal ArticleDOI

Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation)

TL;DR: In this article, the authors propose a method to resample the signal against the angle by using the acceleration signal of a gearbox, where the gear tooth pairs produce contact shocks during rotation and these shocks are processed in order to retrieve the position of the gear against the time.
Journal ArticleDOI

Dynamic modelling of spur gear pair and application of empirical mode decomposition-based statistical analysis for early detection of localized tooth defect

TL;DR: In this paper, a 6-degree-of-freedom gear dynamic model including localized tooth defect has been developed, which consists of a spur gear pair, two shafts, two inertias representing load and prime mover and bearings.
Journal ArticleDOI

Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft

TL;DR: In this paper, a 20-cylinder diesel engine with crankshaft torsional modes in the low frequency range is modeled with a phenomenological model and an automated diagnosis based on an artificially intelligent system is proposed.
Journal ArticleDOI

Cyclostationarity approach for monitoring chatter and tool wear in high speed milling

TL;DR: In this article, a cyclostationary method was used to process the vibrations signals acquired from high-speed milling to detect chatter and tool wear in high speed machining.