Chemical Process Performance Evaluation

Ali Cinar

ISBN 10: 0849338069 / ISBN 13: 9780849338069

Edité par Taylor & Francis Inc Jan 2007, 2007

A propos de cet article

Neuware - Focusing on continuous, multivariate processes, Chemical Process Performance Evaluation introduces statistical methods and modeling techniques for process monitoring, process and controller performance evaluation, and fault diagnosis. The book covers empirical modeling development techniques, modeling process signals for trend analysis, sensor failure detection and diagnosis, controller performance assessment, process performance evaluation, and data analysis techniques for web and sheet processes. Balancing practice and theory, the book integrates several techniques to facilitate practical applications. Case studies illustrate the implementation of methods presented throughout.

N° de réf. du vendeur 9780849338069

Détails bibliographiques

• Titre: Chemical Process Performance Evaluation
• Éditeur: Taylor & Francis Inc Jan 2007
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 0849338069
• ISBN à 13 chiffres: 9780849338069
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 234 L x 156 H x 0 P (en millimètres) 234 millimètres de largeur par 156 millimètres de hauteur par 0 millimètres de profondeur
• Poids: 625 grammes

A propos de ce titre

Synopsis

The latest advances in process monitoring, data analysis, and control systems are increasingly useful for maintaining the safety, flexibility, and environmental compliance of industrial manufacturing operations.
Focusing on continuous, multivariate processes, Chemical Process Performance Evaluation introduces statistical methods and modeling techniques for process monitoring, performance evaluation, and fault diagnosis.

This book introduces practical multivariate statistical methods and empirical modeling development techniques, such as principal components regression, partial least squares regression, input-output modeling, state-space modeling, and modeling process signals for trend analysis. Then the authors examine fault diagnosis techniques based on episodes, hidden Markov models, contribution plots, discriminant analysis, and support vector machines. They address controller process evaluation and sensor failure detection, including methods for differentiating between sensor failures and process upset. The book concludes with an extensive discussion on the use of data analysis techniques for the special case of web and sheet processes. Case studies illustrate the implementation of methods presented throughout the book.

Emphasizing the balance between practice and theory, Chemical Process Performance Evaluation is an excellent tool for comparing alternative techniques for process monitoring, signal modeling, and process diagnosis. The unique integration of process and controller monitoring and fault diagnosis facilitates the practical implementation of unified and automated monitoring and diagnosis technologies.

À propos de l?auteur

Illinois Institute of Technology, Chicago, USA University of California, Davis, USA Integrated Engineering Technologies, Tacoma, Washington, USA