In this book, we address the problem of sensor fault diagnosis in complex systems. The motivation for this work is the common problem encountered in industrial setting, i.e. sensor shift, drift and outright failure. The approach proposed in this paper is based on Auto-Associative Neural Networks but has been extended to address some intrinsic deficiencies of these types of networks in practical setting. In particular, it is shown that the proposed approach provides the basic functionality needed for sensor fault detection in a multi-sensor environment with limited additional computational burden.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
In this book, we address the problem of sensor fault diagnosis in complex systems. The motivation for this work is the common problem encountered in industrial setting, i.e. sensor shift, drift and outright failure. The approach proposed in this paper is based on Auto-Associative Neural Networks but has been extended to address some intrinsic deficiencies of these types of networks in practical setting. In particular, it is shown that the proposed approach provides the basic functionality needed for sensor fault detection in a multi-sensor environment with limited additional computational burden.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, we address the problem of sensor fault diagnosis in complex systems. The motivation for this work is the common problem encountered in industrial setting, i.e. sensor shift, drift and outright failure. The approach proposed in this paper is based on Auto-Associative Neural Networks but has been extended to address some intrinsic deficiencies of these types of networks in practical setting. In particular, it is shown that the proposed approach provides the basic functionality needed for sensor fault detection in a multi-sensor environment with limited additional computational burden. 100 pp. Englisch. N° de réf. du vendeur 9783838359144
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, we address the problem of sensor fault diagnosis in complex systems. The motivation for this work is the common problem encountered in industrial setting, i.e. sensor shift, drift and outright failure. The approach proposed in this paper is based on Auto-Associative Neural Networks but has been extended to address some intrinsic deficiencies of these types of networks in practical setting. In particular, it is shown that the proposed approach provides the basic functionality needed for sensor fault detection in a multi-sensor environment with limited additional computational burden. N° de réf. du vendeur 9783838359144
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, we address the problem of sensor fault diagnosis in complex systems. The motivation for this work is the common problem encountered in industrial setting, i.e. sensor shift, drift and outright failure. The approach proposed in this paper is based on Auto-Associative Neural Networks but has been extended to address some intrinsic deficiencies of these types of networks in practical setting. In particular, it is shown that the proposed approach provides the basic functionality needed for sensor fault detection in a multi-sensor environment with limited additional computational burden.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch. N° de réf. du vendeur 9783838359144
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Taschenbuch. Etat : Neu. Application of Auto-Associative Neural Networks for Sensor Diagnostics | An Enhancement to Auto-Associative Neural Networks for Detection and Isolation of Sensor Faults | Massieh Najafi | Taschenbuch | 100 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838359144 | 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 101167971
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