Industrial Tomography

Systems and Applications

2nd Edition - May 6, 2022
Editor: Mi Wang
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 0 1 5 - 2
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 3 0 7 - 8

Industrial Tomography: Systems and Applications, Second Edition thoroughly explores the important techniques of industrial tomography, also discusses image reconstru… Read more

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Industrial Tomography: Systems and Applications, Second Edition thoroughly explores the important techniques of industrial tomography, also discusses image reconstruction, systems, and applications.

This book presents complex processes, including the way three-dimensional imaging is used to create multiple cross-sections, and how computer software helps monitor flows, filtering, mixing, drying processes, and chemical reactions inside vessels and pipelines.

This book is suitable for materials scientists and engineers and applied physicists working in the photonics and optoelectronics industry or in the applications industries.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Preface
Introduction
Understanding the basics of sensor design and reconstruction
Optimizing data collection and analysis for industrial information
Part One. Tomographic modalities
1. Electrical Capacitance Tomography
1.1. Introduction
1.2. Principle of operation
1.3. Image reconstruction algorithms
1.4. Data acquisition system
1.5. Electrical capacitance volume tomography
1.6. Illustrative examples and discussion
1.7. Flow velocimetry with ECVT
1.8. Three-phase flow decomposition by exploiting Maxwell–Wagner–Sillars effect
1.9. Displacement–current phase tomography (DCPT) and water-dominated flow velocimetry
1.10. Recent progress with AECVT
1.11. RVM for the determination of uncertainty in reconstruction
1.12. Conclusion
1.13. Future trends
1.14. Source of further information
2. Electrical impedance tomography
2.1. Introduction
2.2. Fundamentals of measurement
2.3. Principle of electrical impedance tomography sensing
2.4. Data acquisition
2.5. Image reconstruction
2.6. Imaging capability
2.7. EIT data for process application
2.8. Future trends
2.9. Sources of further information
3. Electromagnetic induction tomography
3.1. Introduction
3.2. Principle of operation and governing equations
3.3. Solution to the forward problem
3.4. Solution to the inverse problem
3.5. System hardware
3.6. Applications
3.7. Conclusions and outlook
4. Magnetic resonance imaging
4.1. Introduction to MRI and NMR
4.2. MRI: basic imaging principles
4.3. Methods: basic imaging techniques
4.4. Advanced data acquisition: fast imaging approaches
4.5. Applications in engineering
4.6. Future trends
4.7. Conclusions
4.8. Sources of further information and advice
5. Chemical Species Tomography
5.1. Introduction
5.2. Absorption spectroscopy for Chemical Species Tomography
5.3. Image reconstruction for low beam count systems
5.4. Beam array design and optimization
5.5. Design of Chemical Species Tomography systems
5.6. Case studies
5.7. Future trends
6. X-ray computed tomography
6.1. Introduction
6.2. Variants of X-ray computed tomography for process applications
6.3. X-ray sources for process tomography
6.4. X-ray detectors
6.5. Attenuation measurement with X-rays
6.6. Beam hardening and radiation scattering
6.7. Cone-beam X-ray computed tomography for gas holdup measurements
6.8. Static mixer studies with ultrafast electron beam X-ray tomography
6.9. Future trends
6.10. Sources of further information and advice
7. Radioisotope tracer techniques
7.1. Nuclear medicine imaging
7.2. Industrial applications
7.3. Particle tracking
8. Ultrasound tomography
8.1. Introduction
8.2. Ultrasound theory
8.3. Equipment and techniques
8.4. Industrial applications
8.5. Summary
8.6. Future trends
8.7. Source of further information and advice
9. Spectro-tomography
9.1. Introduction
9.2. Multidimensional process sensing
9.3. Spectroscopic sensing
9.4. Spectro-tomography principles
9.5. Spectro-tomography system implementation
9.6. Trial demonstrations
9.7. Future trends for spectro-tomography
10. Electron tomography
10.1. Introduction
10.2. Tomography in the electron microscope
10.3. Practical electron tomography
10.4. Advanced electron tomography
10.5. Off-line electron tomography
10.6. Electron tomography of dynamic processes
10.7. Future trends
10.8. Sources of further information
Part Two. Tomographic image reconstruction and data fusion
11. Mathematical concepts for image reconstruction in tomography
11.1. Introduction
11.2. Transmission tomography
11.3. Electrical tomography
11.4. Diffraction tomography
11.5. Future trends
11.6. Source of further information
12. Direct image reconstruction in electrical tomography and its applications
12.1. Introduction
12.2. Invariant property of the governing equation via conformal transformation
12.3. Typical direct algorithms for electrical tomography
12.4. Dirichlet-to-Neumann/Neumann-to-Dirichlet maps
12.5. Calculation of the scattering transforms
12.6. Applications in image reconstruction
12.7. Dynamic flame monitoring
12.8. Future trends
12.9. Further information
13. Machine learning process information from tomography data
13.1. Introduction
13.2. Machine learning methods for information needs
13.3. Artificial neural networks for IPT applications
13.4. Case study A—estimating multiphase flow parameters
13.5. Case study B—estimating inline rheology properties of product flow
13.6. Future trends
14. Advanced electrical tomography visualisation
14.1. Introduction
14.2. Background
14.3. Advanced visualization of multiphase flow
14.4. Multidimensional data fusion
14.5. Future trends
Part Three. Tomography applications
15. Applications of electrical resistance tomography to chemical engineering
15.1. Introduction
15.2. Applications of ERT
15.3. Conclusions
16. From process understanding to process control—Applications in industry
16.1. Introduction
16.2. Applications to improve process understanding
16.3. Process modeling and optimization
16.4. Process analytics
16.5. Process monitoring for process control
16.6. Conclusions and future trends
17. Applications of tomography in oil–gas industry—Part 1
17.1. Introduction
17.2. Seismic tomography in hydrocarbon exploration and reservoir characterization
17.3. Multicomponent seismic data for reservoir characterization
17.4. Simultaneous inversion of time-lapse seismic surveys for reservoir monitoring
17.5. Borehole seismic surveys
17.6. Future trends
17.7. Source of further information and advice
18. Applications of tomography in oil–gas industry—Part 2
18.1. Introduction
18.2. Cross-well electromagnetic tomography in hydrocarbon reservoir monitoring
18.3. Potential of tomography in hydrocarbon production monitoring
18.4. Future trends
18.5. Source of further information and advice
19. Applications of tomography in multiphase transportation
19.1. Introduction
19.2. Flow pattern and flow pattern identification with IPT
19.3. Multiphase transportation process measurement and monitoring with IPTs
19.4. IPT in multiphase flow measurement with multisensor fusion
19.5. Conclusions and future trends
20. Measurement and characterization of slurry flow using Electrical Resistance Tomography
20.1. Introduction
20.2. Physical mechanisms governing hydraulic transport of solid particles
20.3. Slurry flow characterization with Electrical Resistance Tomography
20.4. Limitations of ERT in slurry flow measurement and characterization
20.5. Conclusions and future trends
20.6. Sources of further information
21. Application of tomography in microreactors
21.1. Introduction
21.2. X-ray and γ-ray tomography
21.3. X-ray and γ-ray absorption/radiography tomography
21.4. Nuclear magnetic resonance imaging
21.5. Positron emission tomography
21.6. Electrical impedance tomography
21.7. Future trends
22. X-ray tomography of fluidized beds
22.1. Introduction
22.2. Imaging of fluid beds
22.3. Computational models and their experimental validation
22.4. Experimental studies
22.5. Data evaluation
22.6. Validation experiments for narrow and wide particle size distribution
22.7. Comparison between different validation approaches
22.8. Validation for reactor scale-up
22.9. Ultrafast X-ray computer tomography
22.10. Future trends
23. Applications of tomography in bubble column and fixed bed reactors
23.1. Introduction
23.2. Bubble column reactors
23.3. Fixed bed reactors
23.4. Future trends
23.5. Sources of further information
24. Applications of tomography in mixing process
24.1. Introduction
24.2. Review of tomographic techniques utilizing for different kinds of mixing processes
24.3. How to extract information about mixing from tomographic images
24.4. Application of one-plane tomography in mixing process
24.5. Mixing process monitoring by twin-plane tomographic system
24.6. Toward to improvement of process measurement
24.7. Future trends
25. Applications of electrical capacitance tomography in industrial systems
25.1. Introduction
25.2. Two-phase gas–solid systems
25.3. Two-phase air–water systems
25.4. Three-phase systems
25.5. Future trends
25.6. Source of further information
26. Applications of AI and possibilities for process control
26.1. Introduction
26.2. Artificial intelligence
26.3. Multiphase flow processes for testing AI techniques
26.4. AI techniques relevant for process control
26.5. Possibilities for AI-assisted control
26.6. Future trends
26.7. Sources of further information
27. Diverse tomography applications
27.1. Introduction
27.2. Packed column monitoring with electrical tomography
27.3. 3D Cell spheroid imaging by electrical impedance tomography
27.4. Fabrics pressure mapping using electrical impedance tomography
27.5. Hand gesture recognition using electrical impedance tomography
27.6. Temperature monitoring in the stored grain using acoustic tomography
27.7. Tree decay detection by acoustic tomography
27.8. Concrete defect detection by acoustic tomography
27.9. Temperature monitoring using single light field camera
27.10. Conclusion
Index

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Mi Wang