A novel approach to evaluation of vibration source separation based on spatial distribution of sensors and Fourier transforms / Ali Mahvash in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 133 N° 6 (Novembre 2011)  

Public ISBD [article]  inTransactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 09 p. Titre : A novel approach to evaluation of vibration source separation based on spatial distribution of sensors and Fourier transforms Type de document : texte imprimé Auteurs : Ali Mahvash, Auteur ; Aouni A. Lakis, Auteur Année de publication : 2012 Article en page(s) : 09 p. Note générale : Dynamic systems Langues : Anglais (eng) Mots-clés : Blind source separation Condition monitoring Fourier transforms Machinery Sensors Statistical analysis Vibrations Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : An obstacle in diagnosis of multicomponent machinery using multiple sensors to acquire vibration data is firstly found in the data acquisition itself. This is due to the fact that vibration signals collected by each sensor are a mixture of vibration produced by different components and noise; it is not evident what signals are produced by each component. A number of research studies have been carried out in which this problem was considered a blind source separation (BSS) problem and different mathematical methods were used to separate the signals. One complexity with applying such mathematical methods to separate vibration sources is that no metric or standard measure exists to evaluate the quality of the separation. In this study, a method based on statistical energy analysis (SEA) is proposed using Fourier transforms and the spatial distance between sensors and components. The principle of this method is based on the fact that each sensor, with respect to its location in the system, collects a different version of the vibration produced in the system. By applying a short time Fourier transform to the signals collected by multiple sensors and making use of a priori knowledge of the spatial distribution of sensor locations with respect to the components, the source of the peaks on the frequency spectra of the signals can be identified and attributed to the components. The performance of the method was verified using a series of experimental tests on synthetic signals and real laboratory signals collected from different bearings and the results confirmed the efficacy of the method. DEWEY : 553 ISSN : 0022-0434 En ligne : http://www.asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013300 [...] [article] A novel approach to evaluation of vibration source separation based on spatial distribution of sensors and Fourier transforms [texte imprimé] / Ali Mahvash, Auteur ; Aouni A. Lakis, Auteur . - 2012 . - 09 p. Dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 09 p. Mots-clés : Blind source separation Condition monitoring Fourier transforms Machinery Sensors Statistical analysis Vibrations Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : An obstacle in diagnosis of multicomponent machinery using multiple sensors to acquire vibration data is firstly found in the data acquisition itself. This is due to the fact that vibration signals collected by each sensor are a mixture of vibration produced by different components and noise; it is not evident what signals are produced by each component. A number of research studies have been carried out in which this problem was considered a blind source separation (BSS) problem and different mathematical methods were used to separate the signals. One complexity with applying such mathematical methods to separate vibration sources is that no metric or standard measure exists to evaluate the quality of the separation. In this study, a method based on statistical energy analysis (SEA) is proposed using Fourier transforms and the spatial distance between sensors and components. The principle of this method is based on the fact that each sensor, with respect to its location in the system, collects a different version of the vibration produced in the system. By applying a short time Fourier transform to the signals collected by multiple sensors and making use of a priori knowledge of the spatial distribution of sensor locations with respect to the components, the source of the peaks on the frequency spectra of the signals can be identified and attributed to the components. The performance of the method was verified using a series of experimental tests on synthetic signals and real laboratory signals collected from different bearings and the results confirmed the efficacy of the method. DEWEY : 553 ISSN : 0022-0434 En ligne : http://www.asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013300 [...]

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité
aucun exemplaire