Imaging nylon polymerisation processes by applying electrical tomography

Dyakowski, T.; York, T.A.; Mikos, Michal; Vlaev, D.; Mann, R.; Follows, Gordon W.; Boxman, Arthur; Wilson, M. P.

doi:10.1016/s1385-8947(99)00132-1

Cited by 32 publications

(22 citation statements)

References 2 publications

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“…By measuring the capacitance between all pairs of electrodes, a set of linear equations can be obtained relating the capacitance and the distribution of permittivity. It is then possible to obtain a map of the permittivity distribution in the material contained within the electrodes by solving the inverse problem described by the set of equations (2).…”

Section: A Electrical Capacitance Tomographymentioning

confidence: 99%

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Total variation image reconstruction for electrical capacitance tomography

Chandrasekera

Dennis

et al. 2012

2012 IEEE International Conference on Imaging Systems and Techniques Proceedings

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A new iterative reconstruction technique for electrical capacitance tomography (ECT) is presented. This method applies iterative soft thresholding to penalize the total variation of the ECT image. This method is shown to allow for sharp changes between different regions of simulated ECT images, unlike conventional iterative reconstruction techniques such as ART, SIRT and the Landweber iteration. The technique is demonstrated on experimental results for a phantom with distinct regions of gas and solid. The technique is therefore appropriate for the imaging of multiphase systems.

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Section: A Electrical Capacitance Tomographymentioning

confidence: 99%

“…Electrical resistance and capacitance tomographies are established techniques for non-invasively monitoring industrial processes, e.g. settling, oil and gas flow, or fluidization [1][2][3][4]. The advantage of the electrical tomographies is that they are fast, flexible (scalable) and relatively cheap.…”

Section: Introductionmentioning

confidence: 99%

Total variation image reconstruction for electrical capacitance tomography

Chandrasekera

Dennis

et al. 2012

2012 IEEE International Conference on Imaging Systems and Techniques Proceedings

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“…high pressures and/or high temperatures) [1]. Industrial applications can be found in oil conveying and exploitation [2], production of food [3], and in the chemical industry [4], [5].…”

Section: Introductionmentioning

confidence: 99%

“…N-1 x(s) 2' + 2 ; (ax,, cos(27ns) + bx, sin(27ns)) n=l ay,u+ 1 N-1 y(s) = 2' + 2 (ay,n cos(27ns) + by,n sin(27ns)) n=l(1) (2) where a,,i, ay,j, b,,i and by,j are the system states. Taking further into account that the contour evolves over time, the state-space representation of a contour including its dynamics can be defined by Xk = f(Xk1,Vk-1) Zk = h(xk, wk),(3)(4)…”

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confidence: 99%

A Bayesian Filtering Approach to Object Tracking and Shape Recovery from Tomographic Measurement Data

Watzenig

Brandner

Steiner

et al. 2006

2006 IEEE International Symposium on Industrial Electronics

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Dynamic tomography of non-stationary objects from sparse tomographic data is a challenging issue arising in various areas where heterogeneous flow structures comprised of gas-solid and gas-liquid flow phases occur. Such flow patterns are quite common in pneumatic conveying, oil, food, and chemical industry. This paper addresses the reconstruction of a time-varying material distribution inside a closed pipe subject to dynamics of the object position and the object boundary in an Electrical Capacitance Tomography (ECT) system. The main objective is to recover the shape and the current position of a moving material inclusion. The unknown quantities -shape and position -are jointly estimated applying a Bayesian recursive filter approach incorporating new measurements in each measurement update step. Consequently, the inverse ECT problem is recast as a state estimation problem. The object boundaries are modeled using a Fourier descriptor based contour model of second order which is able to cover various physically reasonable shapes. By prescribing the order of the contour model prior information is incorporated which can be interpreted as regularization as high frequency parts in the estimated contour are low-pass filtered. The proposed tomographic signal processing algorithm is validated experimentally using different test objects.

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“…Recent progress on tomography measurement techniques has been reported that enable to visualize the dispersion states of multiphase systems in chemical equipment (Man and Wang, 1997;Holden et al, 1998;Dyakowski et al, 2000). They allow the determination of cross-section dispersion profiles in a non-intrusive way.…”

Section: Introductionmentioning

confidence: 99%