Détection d'arcs électriques séries par analyse temps-fréquence et traitement morphologique

- Les arcs électriques séries peuvent endommager gravement les installations électriques, voire provoquer des incendies. Cet article décrit une méthode de détection des arcs séries basée sur l'analyse de la dérivée du courant. Une Représentation Temps-Fréquence (RTF) de ce signal (spectrogramme glissant) permet de mettre en évidence des motifs caractéristiques des arcs séries. Un traitement morphologique simple permet d'extraire les motifs d'arcs de la RTF et de quantifier l'importance du phénomène sous la forme d'un « degré de présence d'arc série »

Tracking of spectral lines in an ARCAP time-frequency representation

International audienceARCAP time-frequency representation of narrow-band signals are madde of instantaneous characteristics (frequencies and amplitudes), without any time li,ks. In order to extract the frequency modulations (or spectral trajectoeries), we propose to re-create them on the basis of ballistic integrator models. The analytic expression of the corresponding asymptotic Kalman filter gains allows a very simple implementation of asociation procedures including trajectory birth or death. The points being associated, a Fraser filtering leads to the smoothed spectral trajectories

Tracking of spectral lines in an ARCAP time-frequency representation

International audienceARCAP time-frequency representation of narrow-band signals are madde of instantaneous characteristics (frequencies and amplitudes), without any time li,ks. In order to extract the frequency modulations (or spectral trajectoeries), we propose to re-create them on the basis of ballistic integrator models. The analytic expression of the corresponding asymptotic Kalman filter gains allows a very simple implementation of asociation procedures including trajectory birth or death. The points being associated, a Fraser filtering leads to the smoothed spectral trajectories

Bearings fault diagnosis in asynchrounous machine based on current analysis using high resolution technique

In this Chapter, we propose to perform early fault diagnosis using spectral analysis based on high resolution MUSIC algorithm to detect bearings faults in electrical asynchronous machine. While most research works focus on mechanical vibration signals analysis. The originality of our work relies on the use of high-resolution method to stator current. We present the results obtained for real data of electrical signals to detect inner raceway and outer raceway bearings defects made articially as well as bearing defects obtained through element aging. The results shows that the proposed method yields better detection than classical spectum analysi