Early fault diagnosis can increase machinery availability and performance, reduce consequential damage, prolong machine life, and reduce spare parts inventories and breakdown maintenance. In this book, one intelligent fault diagnostic system is proposed based on feature extraction and selection techniques. Features are calculated from many domains: time domain, frequency domain, cepstrum domain and wavelet domain. In this way, the information of raw data is kept at best to meet different analysis methods in future. Principal component analysis and linear discriminant analysis, two feature extraction methods are introduced. Feature selection methods, individual feature evaluation and genetic algorithm, are compared. They are used to reduce feature dimensionality and improve system performance. The proposed system is applied to fault diagnosis of induction motors as a real application. The results show that the proposed system, combining feature extraction with feature selection, has fast training procedure, high classification rate and compact structure. It is suitable for motor condition monitoring and fault diagnosis.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Early fault diagnosis can increase machinery availability and performance, reduce consequential damage, prolong machine life, and reduce spare parts inventories and breakdown maintenance. In this book, one intelligent fault diagnostic system is proposed based on feature extraction and selection techniques. Features are calculated from many domains: time domain, frequency domain, cepstrum domain and wavelet domain. In this way, the information of raw data is kept at best to meet different analysis methods in future. Principal component analysis and linear discriminant analysis, two feature extraction methods are introduced. Feature selection methods, individual feature evaluation and genetic algorithm, are compared. They are used to reduce feature dimensionality and improve system performance. The proposed system is applied to fault diagnosis of induction motors as a real application. The results show that the proposed system, combining feature extraction with feature selection, has fast training procedure, high classification rate and compact structure. It is suitable for motor condition monitoring and fault diagnosis. 256 pp. Englisch. N° de réf. du vendeur 9783659514623
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Han TianDoctor Tian Han is working in the School of Mechanical Engineering at University of Science and Technology Beijing in China. He received his PhD degree in 2005. Dr. Han s main research fields cover machine dynamics, vibration. N° de réf. du vendeur 5161546
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 256. N° de réf. du vendeur 26128412577
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 256 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. N° de réf. du vendeur 131126398
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 256. N° de réf. du vendeur 18128412587
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Intelligent Fault Diagnostic System of Induction Motor | Based on Feature Extraction & Feature Selection | Tian Han | Taschenbuch | 256 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659514623 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 105197587
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Early fault diagnosis can increase machinery availability and performance, reduce consequential damage, prolong machine life, and reduce spare parts inventories and breakdown maintenance. In this book, one intelligent fault diagnostic system is proposed based on feature extraction and selection techniques. Features are calculated from many domains: time domain, frequency domain, cepstrum domain and wavelet domain. In this way, the information of raw data is kept at best to meet different analysis methods in future. Principal component analysis and linear discriminant analysis, two feature extraction methods are introduced. Feature selection methods, individual feature evaluation and genetic algorithm, are compared. They are used to reduce feature dimensionality and improve system performance. The proposed system is applied to fault diagnosis of induction motors as a real application. The results show that the proposed system, combining feature extraction with feature selection, has fast training procedure, high classification rate and compact structure. It is suitable for motor condition monitoring and fault diagnosis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 256 pp. Englisch. N° de réf. du vendeur 9783659514623
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Early fault diagnosis can increase machinery availability and performance, reduce consequential damage, prolong machine life, and reduce spare parts inventories and breakdown maintenance. In this book, one intelligent fault diagnostic system is proposed based on feature extraction and selection techniques. Features are calculated from many domains: time domain, frequency domain, cepstrum domain and wavelet domain. In this way, the information of raw data is kept at best to meet different analysis methods in future. Principal component analysis and linear discriminant analysis, two feature extraction methods are introduced. Feature selection methods, individual feature evaluation and genetic algorithm, are compared. They are used to reduce feature dimensionality and improve system performance. The proposed system is applied to fault diagnosis of induction motors as a real application. The results show that the proposed system, combining feature extraction with feature selection, has fast training procedure, high classification rate and compact structure. It is suitable for motor condition monitoring and fault diagnosis. N° de réf. du vendeur 9783659514623
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA82936595146246
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