Industrial Tomography: Systems and Applications

743 Pages·2015·60.097 MB·English

by  Mi Wang

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Woodhead Publishing Series in Electronic and
Optical Materials: Number 71
Industrial Tomography
Systems and Applications
Edited by
Mi Wang
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List of contributors
N.AliOthman UniversitiKebangsaanMalaysia,Bangi,Selangor,Malaysia;Chiba
University, Inage, Chiba, Japan
R.G.Aykroyd University of Leeds, Leeds, UK
B. Cafarelli University ofFoggia, Foggia,Italy
Z. Cao Beihang University, Beijing, China
K. Daun University ofWaterloo,Waterloo,Ontario, Canada
M.A. Del Nobile University ofFoggia, Foggia, Italy
F. Dong Tianjin University, Tianjin, China
L.-S.Fan The Ohio State University, Columbus, OH, USA
U. Hampel Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany;
Technische Universit€atDresden, Dresden, Germany
D.J. Holland University of Canterbury,Christchurch, NewZealand
B.S. Hoyle University of Leeds, Leeds, UK
G.A.Johansen Faculty of Engineeringand BusinessAdministration, Bergen
University College, Bergen, Norway
J.P.Kaipio The University ofAuckland, Auckland, New Zealand; University of
Eastern Finland,Kuopio,Finland;Rocsole Ltd, Kuopio,Finland
G. Kamath GeorgiaState University, Atlanta, GA, USA
A. Kantzas University of Calgary, Calgary,AB, Canada
A.K.Khambampati Institutefor NuclearScience and Technology, Jeju National
University, Jeju, South Korea
S. Kim Schoolof Energy Systems Engineering,Chung-Ang University, Seoul,
South Korea
V. Lampignano University of Foggia, Foggia, Italy
J. Laverse University of Foggia, Foggia, Italy
A. Lehikoinen University of Eastern Finland, Kuopio, Finland;Rocsole Ltd,
Kuopio,Finland
A. Lipponen University of Eastern Finland, Kuopio,Finland
xiv Listofcontributors
Q. Marashdeh Tech4Imaging LLC, Columbus,OH, USA
H. McCann University ofEdinburgh, Edinburgh,Scotland, UK
V. Mosorov Institute ofAppliedComputer Science, Lodz University of
Technology,Lodz, Poland
D. Parker University of Birmingham, Birmingham, UK
A.J. Peyton University of Manchester, Manchester, UK
K. Primrose IndustrialTomography Systems plc, Manchester, UK
V. Rimpil€ainen The University ofAuckland, Auckland, NewZealand
A.J. Sederman Department of Chemical Engineering and Biotechnology,
University ofCambridge, Cambridge,UK
A. Sepp€anen University ofEastern Finland;Kuopio,Finland
W.-Z.Song Georgia State University, Atlanta, GA,USA
A. Spada University of Foggia, Foggia, Italy
M. Takei Chiba University, Inage, Chiba, Japan
C. Tan TianjinUniversity, Tianjin, China
F.L. Teixeira The Ohio State University, Columbus, OH, USA
M. Vauhkonen University ofEastern Finland,Kuopio, Finland; Rocsole Ltd,
Kuopio, Finland
A. Voutilainen Rocsole Ltd, Kuopio,Finland
A. Wang The Ohio State University, Columbus, OH, USA
M. Wang University of Leeds,Leeds,West Yorkshire,UK
N.J. Watson University ofNottingham, Nottingham, UK
R.A.Williams University ofBirmingham,Birmingham, UK
M. Wilt Schlumberger Gould Research Centre, Cambridge, UK; Schlumberger
OilfieldPetroTechnical Services, Richmond, CA,USA
P. Wright University of Manchester, Manchester UK
C.-G.Xie Singapore Well Testing Centre (SWTC), Schlumberger Oilfield (S)
Pte Ltd, Singapore; Schlumberger Gould Research Centre, Cambridge, UK;
Schlumberger OilfieldPetroTechnical Services,Richmond, CA, USA
L. Xu Beihang University, Beijing,China
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–
Introduction an overview of process
applications of tomographic techniques
1. Historical development
Since its inception the goal of process tomography has been to sense and interpret
complex data in order to extract qualitative and quantitative information of the
behaviour of fluids moving within processes. These processes may be reactors,
pipelines or measurements focused on the properties of materials being manufac-
tured. At one extreme, we have the classical physics of nondestructive testing (a
parlance reserved for testing of static products undergoing routine characterisation)
and at the other extreme are attempts to quantitate multiphase fluids under chaotic
flow regimes. In all cases, there is trade-off between spatial and component resolu-
tion and the dynamic (or temporal) resolution. The roots of the discipline lie in
medical tomography in which a static (literal) body was investigated using now
well-known medical tomographic sensors based on radiation and electromagnetic
sensing. Process tomography sought to extend the principles applied to static and
steady-state objects to industrial applications (Beck & Williams, 1995, p. 550;
Chaouki, Larachi, & Dudukovi(cid:1)c, 1997; Williams, 2010). The journey of this
book takes a sensor-perspective, introducing the capabilities of different sensors
(often called modalities) and then examining their application for specific measure-
ment tasks.
The process engineer starts at the process. The physicist and instrument engineer
may often start with the sensors. Process tomography requires integration at both
ends, but invariably the practicalities of the purpose of the measurement should
be used to drive the design of the overall process. Whilst there is a natural desire
to want to know everything about the process, in reality this is beyond reach.
The approach must focus not on the quality of an image but on the specification of
measurements from which judgments can be made for specific purposes. We see
this dilemma in the early works on Process Tomography in the World Congress
conference series commencing in 1999 (see Bibliography [B10]). Here, sensors
werenormallyevaluatedinstatictestsusingphantomobjectsagainstdifferentcondi-
tions–farremovedfromrealprocesses.Thesewerenecessarytests,buttheywerenot
sufficient for therealities ofprocess measurement.
More sophisticated computational and modeling methods were needed to extract
information of interest – and this information was often not an image. Nevertheless,
preoccupation with images has persisted for obvious reasons. Figure 1 illustrates