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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes (Advances in Industrial Control) - Hardcover
Inhaltsangabe
Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis.
The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.
The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
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Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis.
The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.
The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
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- VerlagSpringer
- Erscheinungsdatum2013
- ISBN 10 1852332581
- ISBN 13 9781852332587
- EinbandTapa dura
- SpracheEnglisch
- Anzahl der Seiten212
- Kontakt zum HerstellerNicht verfügbar
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Data-Driven Techniques For Fault Detection and Diagnosis in Chemical Processes
Anbieter: Attic Books (ABAC, ILAB), London, ON, Kanada
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Hardcover. Zustand: Fine. Advances in Industrial Control series. xiii, 192 p. 24 cm. 49 figures and tables. Hardcover. Bestandsnummer des Verkäufers 116503
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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Zustand: New. pp. xiv + 212. Bestandsnummer des Verkäufers 18459135
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
Anbieter: Books Puddle, New York, NY, USA
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Zustand: New. pp. xiv + 212 1st Edition. Bestandsnummer des Verkäufers 26459125
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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Zustand: New. pp. xiv + 212 Illus. Bestandsnummer des Verkäufers 7388842
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
Verlag:
Springer London, Springer London Feb 2000, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
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Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis.The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 212 pp. Englisch. Bestandsnummer des Verkäufers 9781852332587
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
Print-on-DemandAnbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis.The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application. 212 pp. Englisch. Bestandsnummer des Verkäufers 9781852332587
Anzahl: 2 verfügbar
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
Verlag:
Springer London, Springer London, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis.The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application. Bestandsnummer des Verkäufers 9781852332587
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes (Advances in Industrial Control)
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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Paperback. Zustand: Brand New. 192 pages. 9.25x6.25x0.75 inches. In Stock. Bestandsnummer des Verkäufers zk1852332581
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