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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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
I. Introduction.- 1. Introduction.- II. Background.- 2. Multivariate Statistics.- 3. Pattern Classification.- III. Methods.- 4. Principal Component Analysis.- 5. Fisher Discriminant Analysis.- 6. Partial Least Squares.- 7. Canonical Variate Analysis.- IV. Application.- 8. Tennessee Eastman Process.- 9. Application Description.- 10. Results and Discussion.- V. Other Approaches.- 11. Overview of Analytical and Knowledge-based Approaches.- References.
Product Description
Book by Russell Evan L Chiang Leo H Braatz Richard D
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer
- Data di pubblicazione2013
- ISBN 10 1852332581
- ISBN 13 9781852332587
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine212
- Contatto del produttorenon disponibile
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Data-Driven Techniques For Fault Detection and Diagnosis in Chemical Processes
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Hardcover. Condizione: Fine. Advances in Industrial Control series. xiii, 192 p. 24 cm. 49 figures and tables. Hardcover. Codice articolo 116503
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Condizione: New. pp. xiv + 212 Illus. Codice articolo 7388842
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Data-Driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Springer London, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers a variety of data-driven process monitoring techniquesIncludes detailed applications in chemical plant simulationIncludes homework problems to enable deeper comprehension of the textEarly and accurate fault detection and diagnosis for mod. Codice articolo 4289444
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Springer London Feb 2000, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9781852332587
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Springer London, Springer London Feb 2000, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9781852332587
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Springer London, Springer London, 2000
ISBN 10: 1852332581
ISBN 13: 9781852332587
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9781852332587
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes (Advances in Industrial Control)
Da: Revaluation Books, Exeter, Regno Unito
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Paperback. Condizione: Brand New. 192 pages. 9.25x6.25x0.75 inches. In Stock. Codice articolo zk1852332581
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