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{ "item_title" : "Process Imaging for Automatic Control", "item_author" : [" David M. Scott", "Hugh McCann "], "item_description" : "As industrial processes and their corresponding control models increase in complexity, the data provided by traditional point sensors is no longer adequate to ensure product quality and cost-effective operation. Process Imaging for Automatic Control demonstrates how in-process imaging technologies surpass the limitations of traditional monitoring systems by providing real-time multidimensional measurement and control data. Combined with suitable data extraction and control schemes, such systems can optimize the performance of a wide variety of industrial processes.Contributed by leading international experts, Process Imaging for Automatic Control offers authoritative, comprehensive coverage of this new area of process control technology, including:Basic goals of process modeling and their application to automatic controlDirect imaging devices and applications, such as machine vision and spatial measurement of flow velocity, pressure, shear, pH, and temperatureVarious techniques, hardware implementations, and image reconstruction methods for process tomographyImage enhancement and restorationState estimation methodsState space control system models, control strategies, and implementation issuesFive chapters devoted to case studies and advanced applicationsFrom theory to practical implementation, this book is the first to treat the entire range of imaging techniques and their application to process control. Supplying broad coverage with more than 270 illustrations and nearly 700 cited references, it presents an accessible introduction to this rapidly growing, interdisciplinary technology.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/0/82/475/920/0824759206_b.jpg", "price_data" : { "retail_price" : "305.00", "online_price" : "305.00", "our_price" : "305.00", "club_price" : "305.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Process Imaging for Automatic Control|David M. Scott

Process Imaging for Automatic Control

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Overview

As industrial processes and their corresponding control models increase in complexity, the data provided by traditional point sensors is no longer adequate to ensure product quality and cost-effective operation. Process Imaging for Automatic Control demonstrates how in-process imaging technologies surpass the limitations of traditional monitoring systems by providing real-time multidimensional measurement and control data. Combined with suitable data extraction and control schemes, such systems can optimize the performance of a wide variety of industrial processes.

Contributed by leading international experts, Process Imaging for Automatic Control offers authoritative, comprehensive coverage of this new area of process control technology, including:
  • Basic goals of process modeling and their application to automatic control
  • Direct imaging devices and applications, such as machine vision and spatial measurement of flow velocity, pressure, shear, pH, and temperature
  • Various techniques, hardware implementations, and image reconstruction methods for process tomography
  • Image enhancement and restoration
  • State estimation methods
  • State space control system models, control strategies, and implementation issues
  • Five chapters devoted to case studies and advanced applications
From theory to practical implementation, this book is the first to treat the entire range of imaging techniques and their application to process control. Supplying broad coverage with more than 270 illustrations and nearly 700 cited references, it presents an accessible introduction to this rapidly growing, interdisciplinary technology.

This item is Non-Returnable

Details

  • ISBN-13: 9780824759209
  • ISBN-10: 0824759206
  • Publisher: CRC Press
  • Publish Date: May 2005
  • Dimensions: 9.3 x 6.12 x 1.22 inches
  • Shipping Weight: 1.76 pounds
  • Page Count: 439

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