Process Imaging For Automatic Control Electrical and Computer Engineering 1st Edition by David M Scott, Hugh McCann ISBN 0824759206 9780824759209

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Product details:

ISBN 10: 0824759206 

ISBN 13: 9780824759209

Author: David M. Scott, Hugh McCann

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.

Table of contents:

1. The Challenge
1.1 Motivation
1.2 Roadmap
1.3 Vista

2. Process Modeling
2.1 Introduction
2.2 Simulation Versus Optimization
2.3 Process Models for Imaging and Analysis
2.4 Process Modeling for Design, Control, and Diagnostics
2.5 References

3. Direct Imaging Technology
3.1 Introduction
3.2 Light Sources
3.3 Sensors
3.4 Optical Components
3.5 Applications
3.6 Machine Vision
3.7 References

4. Process Tomography
4.1 Introduction
4.2 Tomographic Sensor Modalities
4.3 Image Reconstruction
4.4 Current Tomography Systems
4.5 Applications
4.6 References

5. Image Processing and Feature Extraction
5.1 Introduction
5.2 Image Enhancement
5.3 Image Restoration
5.4 Segmentation
5.5 Feature Representation
5.6 Morphological Image Processing and Analysis
5.7 References

6. State Estimation
6.1 Introduction
6.2 Real-Time Recursive Estimation: Kalman Predictors and Filters
6.3 On-Line and Transient Estimation: Smoothers
6.4 Nonlinear and Non-Gaussian State Estimation
6.5 Partially Unknown Models: Parameter Estimation
6.6 Further Topics
6.7 Observation and Evolution Models in Process Industry
6.8 Example: Convection-Diffusion Models
6.9 References

7. Control Systems
7.1 Introduction
7.2 Modeling the Process
7.3 Feedback Control
7.4 Control Design
7.5 Practicalities of Implementing Controllers
7.6 Conclusion
7.7 References

8. Imaging Diagnostics for Combustion Control
8.1 Introduction
8.2 Combustor Types
8.3 Imaging in Combustors
8.4 Results from Combustion Imaging
8.5 Conclusions
8.6 References

9. Multiphase Flow Measurements
9.1 Introduction
9.2 Flow Pattern Recognition
9.3 Flow Pattern Imaging
9.4 Solids Mass Flow Measurements
9.5 References

10. Applications in the Chemical Process Industry
10.1 Introduction
10.2 Applications Related to Process Control
10.3 Applications Related to Process/Product R&D
10.4 Conclusion
10.5 References

11. Mineral and Material Processing
11.1 Motivation for Development of Image-Based Techniques
11.2 Design of Comminution Equipment
11.3 Granular Flow and Bulk Transportation
11.4 Particle Classification in Cyclones
11.5 Performance of Flotation Cells and Columns
11.6 Solids Settling and Water Recovery
11.7 Microscale Analysis of Granules, Flocs, and Sediments
11.8 Concluding Remarks
11.9 References

12. Applications in the Metals Production Industry
12.1 Introduction
12.2 Detection of Slag Entrainment
12.3 Measurement of Furnace Refractory Wear
12.4 Flow Measurement
12.5 Imaging of Solid State Phase Change

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Tags: David M Scott, Hugh McCann, Process Imaging, Automatic Control, Electrical Engineering, Computer Engineering