Industrial Tomography
Systems and Applications
- 1st Edition - April 2, 2015
- Editor: Mi Wang
- Language: English
Industrial Tomography: Systems and Applications thoroughly explores the important tomographic techniques of industrial tomography, also discussing image reconstruction, systems,… Read more
Industrial Tomography: Systems and Applications
thoroughly explores the important tomographic techniques of industrial tomography, also discussing image reconstruction, systems, and applications.The text 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.
Readers will find a comprehensive discussion on the ways tomography systems can be used to optimize the performance of a wide variety of industrial processes.
- Provides a comprehensive discussion on the different formats of tomography
- Includes an excellent overview of image reconstruction using a wide range of applications
- Presents a comprehensive discussion of tomography systems and their application in a wide variety of industrial processes
Applied physicists, materials scientists and engineers working in the photonics and optoelectronics industry or in the applications industries.
- Related titles
- List of contributors
- Woodhead Publishing Series in Electronic and Optical Materials
- Introduction – an overview of process applications of tomographic techniques
- 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. Conclusions
- 1.8. Future trends
- 2. Electrical impedance tomography
- 2.1. Introduction
- 2.2. EIT sensor
- 2.3. Electrode modelling
- 2.4. Signal sources
- 2.5. Sensing strategies
- 2.6. Sensor electronics and demodulation
- 2.7. Data acquisition systems
- 2.8. Imaging capability
- 2.9. EIT data for process application
- 2.10. Future trends
- 2.11. 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. Image contrast
- 4.4. Basic imaging techniques
- 4.5. Fast imaging approaches
- 4.6. Applications in engineering
- 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 CST 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. Gamma-ray tomography
- 7.1. Introduction
- 7.2. Radioisotope sources and gamma-ray emission
- 7.3. Gamma-ray attenuation in matter
- 7.4. Detector and read-out systems
- 7.5. System engineering and geometry
- 7.6. Case studies
- 7.7. Future trends
- 8. Radioisotope tracer techniques
- 8.1. Nuclear medicine imaging
- 8.2. Industrial applications
- 8.3. Particle tracking
- 9. Ultrasound tomography
- 9.1. Introduction
- 9.2. Ultrasound theory
- 9.3. Equipment and techniques
- 9.4. Industrial applications
- 9.5. Future trends
- 9.6. Sources of further information and advice
- 9.7. Summary
- 10. Spectro-tomography
- 10.1. Multidimensional process measurement requirements
- 10.2. Multidimensional process sensing
- 10.3. Spectral energy sensing dimension
- 10.4. Spectro-tomography principles
- 10.5. Spectro-tomography system implementation
- 10.6. Demonstration and implementation
- 10.7. Spectro-tomography application review
- 11. Tomographic imaging in sensor networks
- 11.1. Introduction
- 11.2. Seismic tomography
- 11.3. Sensor networks for volcano monitoring
- 11.4. In-network tomographic imaging
- 11.5. In-network tomography imaging applications
- 11.6. Future trends in in-network tomography imaging
- 11.7. Other sources and advice
- 1. Electrical capacitance tomography
- Part Two. Tomographic image reconstruction
- 12. Mathematical concepts for image reconstruction in tomography
- 12.1. Introduction
- 12.2. Transmission tomography
- 12.3. Electrical tomography
- 12.4. Diffraction tomography
- 12.5. Future trends
- 12.6. Further useful information
- 13. Image reconstruction for hard field tomography
- 13.1. Introduction and basic considerations
- 13.2. The forward problem: projections and the Radon space
- 13.3. The inverse problem and two-dimensional analytic image reconstruction with parallel beams
- 13.4. The central slice theorem
- 13.5. Implementation
- 13.6. Algebraic image reconstruction
- 13.7. 3D analytic image reconstruction
- 13.8. Local tomography, limited-angle tomography, and limited-data tomography
- 13.9. Future trends
- 13.10. Sources of further information and advice
- Appendix A.1: proof of rotational invariance of the 2D Fourier transform
- 14. Direct methods for image reconstruction in electrical capacitance tomography
- 14.1. Introduction
- 14.2. Three typical direct algorithms for ECT
- 14.3. Constructions of the Dirichlet-to-Neumann/Neumann-to-Dirichlet maps
- 14.4. Calculation of the scattering transforms
- 14.5. Reconstructed results and discussion
- 14.6. Conclusions
- 14.7. Future trends
- 14.8. Further information
- 15. Statistical image reconstruction
- 15.1. Introduction
- 15.2. Background
- 15.3. Bayesian paradigm
- 15.4. Data models
- 15.5. Pixel-based continuous prior models
- 15.6. Other pixel-based prior models
- 15.7. Feature-based prior models
- 15.8. Estimation methodology
- 15.9. Estimation examples
- 15.10. Discussion and future trends
- 12. Mathematical concepts for image reconstruction in tomography
- Part Three. Tomography applications
- 16. Applications of tomography in mineral transportation
- 16.1. Introduction
- 16.2. Flow pattern and flow pattern identification with industrial process tomography
- 16.3. Mineral transportation process measurement and monitoring with industrial process tomography
- 16.4. Industrial process tomography in multiphase-flow measurement with multisensory fusion
- 16.5. Conclusions
- 17. X-ray tomography of fluidized beds
- 17.1. Introduction
- 17.2. Imaging of fluid beds
- 17.3. Computational models and their experimental validation
- 17.4. Experimental studies
- 17.5. Data evaluation
- 17.6. Validation experiments for narrow and wide particle size distribution
- 17.7. Comparison between different validation approaches
- 17.8. Validation for reactor scale-up
- 17.9. Ultrafast X-ray computer tomography
- 17.10. Future trends
- 18. Applications of tomography in bubble column and trickle bed reactors
- 18.1. Introduction
- 18.2. Bubble column reactors
- 18.3. Trickle bed reactors
- 18.4. Future trends
- 18.5. Sources of further information
- 19. Applications of tomography in reaction engineering (mixing process)
- 19.1. Introduction
- 19.2. Review of tomographic techniques utilized for different kinds of mixing processes
- 19.3. How to extract information about mixing from tomographic images
- 19.4. Application of one-plane tomography in mixing processes
- 19.5. Mixing process monitoring by twin-plane tomographic system
- 19.6. Other applications of tomography for mixing processes
- 19.7. Future trends
- 20. Applications of capacitance tomography in gas–solid fluidized bed systems
- 20.1. Introduction to fluidized bed systems
- 20.2. Electrical capacitance characterization of gas–solid fluidized beds
- 20.3. Examples and discussion for electrical capacitance tomography applications in conventional fluidized beds
- 20.4. Applications of capacitance tomography in the pharmaceutical industry
- 20.5. Effective permittivities of mixtures and phase distributions
- 20.6. Future trends and conclusion
- 21. Process tomography and estimation of velocity fields
- 21.1. Introduction
- 21.2. Nonstationary inverse problems and state estimation
- 21.3. Approximate nonlinear and non-Gaussian state estimation and handling modelling errors
- 21.4. Approaches with auxiliary parameters
- 21.5. Tomographic state space estimation of velocity fields
- 21.6. Computational case studies
- 21.7. Discussion
- 21.8. Sources of further information and advice
- 22. Applications of tomography in oil-gas industry – Part 1
- 22.1. Introduction
- 22.2. Seismic tomography in hydrocarbon exploration and reservoir characterization
- 22.3. Multicomponent seismic data for reservoir characterization
- 22.4. Simultaneous inversion of time-lapse seismic surveys for reservoir monitoring
- 22.5. Borehole seismic surveys
- 22.6. Future trends
- 22.7. Sources of further information and advice
- 23. Applications of tomography in the oil-gas industry – Part 2
- 23.1. Introduction
- 23.2. Cross-well electromagnetic tomography in hydrocarbon reservoir monitoring
- 23.3. Potential of tomography in hydrocarbon production monitoring
- 23.4. Future trends
- 23.5. Sources of further information and advice
- 24. Application of tomography in microreactors
- 24.1. Introduction
- 24.2. X-ray and γ-ray tomography
- 24.3. X-ray and γ-ray absorption/radiography tomography
- 24.4. Nuclear magnetic resonance imaging
- 24.5. Positron emission tomography
- 24.6. Electrical impedance tomography
- 24.7. Future trends
- 25. Applications of tomography in food inspection
- 25.1. Introduction
- 25.2. Description of testing method used in X-ray microtomography
- 25.3. To date: food products studied
- 25.4. Case studies of food products studied to date
- 25.5. Future trends
- 25.6. Further information
- 26. Application of process tomography in nuclear waste processing
- 26.1. Introduction
- 26.2. Applications of resistance tomography
- 26.3. Applications of other tomographic modalities
- 26.4. Future trends
- 26.5. Sources of further information and advice
- 16. Applications of tomography in mineral transportation
- Index
- Edition: 1
- Published: April 2, 2015
- Language: English
MW
Mi Wang
Mi Wang has been a Professor of Process Tomography and Sensing at the University of Leeds, UK, since 2007. He is also a guest editor of Measurement Science and Technology and Flow Measurement and Instrumentation, and the editor of Petroleum and Hydrodynamics. He has previously been a guest Professor at the Institute of Mechanics of the Chinese Academy of Sciences, China, and a visiting Professor at Nihon University, Japan, where he was awarded the Outstanding Contribution Medal in 2007.
Affiliations and expertise
Professor of Process Tomography and Sensing, University of Leeds, UKRead Industrial Tomography on ScienceDirect