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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes: 377 (Lecture Notes in Control and Information Sciences) - Softcover
Inhaltsangabe
An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.
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Reseña del editor
This book investigates the properties of locally recurrent neural networks, developing training procedures for them and their application to the modeling and fault diagnosis of non-linear dynamic processes and plants.
Reseña del editor
An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
Verlag:
Springer Berlin Heidelberg, 2008
ISBN 10: 3540798714
ISBN 13: 9783540798712
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
Verlag:
Springer Berlin Heidelberg, 2008
ISBN 10: 3540798714
ISBN 13: 9783540798712
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Investigates the properties of locally recurrent neural networks, developing training procedures for them and their application to the modelling and fault diagnosis of non-linear dynamic processes and plantsIncludes an Introduction to fault diagno. Bestandsnummer des Verkäufers 4901352
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available. Bestandsnummer des Verkäufers 9783540798712
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
Verlag:
Springer Berlin Heidelberg Jun 2008, 2008
ISBN 10: 3540798714
ISBN 13: 9783540798712
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available. 232 pp. Englisch. Bestandsnummer des Verkäufers 9783540798712
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
ISBN 10: 3540798714
ISBN 13: 9783540798712
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Taschenbuch. Zustand: Neu. Neuware -An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch. Bestandsnummer des Verkäufers 9783540798712
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes (Lecture Notes in Control and Information Sciences, 377)
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes (Lecture Notes in Control and Information Sciences, 377)
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Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes (Lecture Notes in Control and Information Sciences)
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