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Paper Detail

Paper:	ITT-P3.8
Session:	Multimedia, Automotive, Printing and Networking Applications
Time:	Friday, May 19, 16:30 - 18:30
Presentation:	Poster
Topic:	Industry Technology Track: Other ITT Topics
Title:	GEAR SIGNAL SEPARATION BY EXPLOITING THE SPECTRAL DIVERSITY AND CYCLOSTATIONARITY
Authors:	Khalid Sabri, GSCM, Faculté des Sciences Rabat / Université Jean Monnet, Morocco; Mohamed El Badaoui, François Guillet, LASPI, Université Jean Monnet, IUT de Roanne, France; Abdellah Adib, GSCM, Université Mohammed V, FSR, Morocco; Driss Aboutajdine, GSCM, Faculté des Sciences Rabat, Morocco
Abstract:	This paper deals with the problem concerning the framework of rotating machines diagnostics by using signal processing advanced tools and more precisely Blind Source Separation (BSS) methods. An application on gear box is given, the objective is to separate gear mesh signals corresponding to each reducer’s wheel. It enables us to diagnose and separate each defect in the event of degradation. The proposed method exploits the information redundancy around the meshing frequency and its harmonics resulting from cyclostationarity properties. This redundancy allows us to separate the contribution of each wheel from only one sensor, by tacking advantage of the nonuniformity of the Mechanical Structure Frequency Response (MSFR) connecting the exciting source to the sensor. Key words: Mechanical Structure Frequency Response, BSS, Cyclostationarity, Diagnostics.