focussed on the key steps in soft sensor design: data selection; model structure selection and model validation, respectively. Extensions to the basic steps of soft sensor design, namely soft sensor performance enhancement and the modifications needed to facilitate different industrial process applications follow in Chapter 7 and 8, respectively. Widening the applications range and role of soft sensors to fault detection and sensor validation configurations is dealt with in Chapter 9. A great strength of Soft Sensors for Monitoring and Control of Industrial Processes is the use, throughout the…mehr
focussed on the key steps in soft sensor design: data selection; model structure selection and model validation, respectively. Extensions to the basic steps of soft sensor design, namely soft sensor performance enhancement and the modifications needed to facilitate different industrial process applications follow in Chapter 7 and 8, respectively. Widening the applications range and role of soft sensors to fault detection and sensor validation configurations is dealt with in Chapter 9. A great strength of Soft Sensors for Monitoring and Control of Industrial Processes is the use, throughout the text, of a set of industrial case studies to demonstrate the successes and drawbacks of the different methods used to create soft sensor models. A number of different methods may be used in each separate step of the soft sensor design process and the industrial case studies are often used to provide explicit comparisons of the performance of these methods. The industrial control and processengineer will find these comparison exercises invaluable illustrations of the sort of results that might be found in industrial applications. The monograph also highlights the importance of using knowledge from industrial experts and from the existing industrial process literature. This is an important aspect of industrial control that is not very widely acknowledged or taught in control courses. Most industrial processes have already generated a significant experimental knowledge base and the control engineer should develop ways of tapping into this valuable resource when designing industrial control schemes.
Artikelnr. des Verlages: 11605263, 978-1-84628-479-3
2007
Seitenzahl: 292
Erscheinungstermin: 7. Dezember 2006
Englisch
Abmessung: 241mm x 160mm x 21mm
Gewicht: 547g
ISBN-13: 9781846284793
ISBN-10: 1846284791
Artikelnr.: 20869378
Autorenporträt
Luigi Fortuna has been Professor of System Theory at the University of Catania since 1994. He has published more than 280 technical papers and is co-author of seven books including, for Springer, Soft Computing (1-85233-308-1, 2001, 280 pp, SC) and Microelectronics and Microsystems (1-85233-499-1, 2001, 222 pp, HC). He holds several USA patents. His scientific interests include automatic control, nonlinear science and complexity, chaos, cellular neural networks with applications in bioengineering. He has been an IEEE Fellow since 2000. Salvatore Graziani received a M.S. degree in electronic engineering and a Ph.D. in electrical engineering, both from the Università degli Studi di Catania, Italy, in 1990 and 1994, respectively. In 1990 he joined the Dipartimento di Ingegneria Elettrica, Elettrica e dei Sistemi, Università di Catania, where he is an Associate Professor of Electric and Electronic Measurement and Instrumentation. His primary research interests lie in the field of sensors and actuators, signal processing, multisensor data fusion, neural networks, and smart sensors. He has co-authored several scientific papers and one book. Maria Gabriella Xibilia holds an M.S. degree in electronic engineering and a Ph.D. in electrical engineering, both from the Università degli Studi di Catania, Italy, in 1991 and 1995, respectively. In 1998 she joined the Dipartimento di Matematica of the Università degli Studi di Messina, where she is an Assistant Professor of Automatic Control. Her primary research interests lie in the field of process control, system identification, soft computing and fault detection. She has coauthored several scientific papers and three books.
Inhaltsangabe
Soft Sensors in Industrial Applications.- Virtual Instruments and Soft Sensors.- Soft Sensor Design.- Selecting Data from Plant Database.- Choice of the Model Structure.- Model Validation.- Strategies to Improve Soft Sensor Performance.- Adapting Soft Sensors to Applications.- Fault Detection, Sensor Validation and Diagnosis.
Soft Sensors in Industrial Applications.- Virtual Instruments and Soft Sensors.- Soft Sensor Design.- Selecting Data from Plant Database.- Choice of the Model Structure.- Model Validation.- Strategies to Improve Soft Sensor Performance.- Adapting Soft Sensors to Applications.- Fault Detection, Sensor Validation and Diagnosis.
Soft Sensors in Industrial Applications.- Virtual Instruments and Soft Sensors.- Soft Sensor Design.- Selecting Data from Plant Database.- Choice of the Model Structure.- Model Validation.- Strategies to Improve Soft Sensor Performance.- Adapting Soft Sensors to Applications.- Fault Detection, Sensor Validation and Diagnosis.
Soft Sensors in Industrial Applications.- Virtual Instruments and Soft Sensors.- Soft Sensor Design.- Selecting Data from Plant Database.- Choice of the Model Structure.- Model Validation.- Strategies to Improve Soft Sensor Performance.- Adapting Soft Sensors to Applications.- Fault Detection, Sensor Validation and Diagnosis.
Rezensionen
From the reviews: "The monograph is devoted to design procedure of soft sensors and their applications for solving some industrial problems. ... The monograph highlights the importance of using knowledge from industrial experts and from the existing industrial process literature. It is full of valuable information about the veracity of different methods. The monograph will be appreciated by the industrial control engineer for its practical insights and by the academic staff for its case-study applications."(Tadeusz Kaczorek, Zentralblatt MATH, Vol. 1136 (14), 2008)
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