An efficient approach for limited-data chemical species tomography and its error bounds

N. Polydorides; S-A Tsekenis; H. McCann; V-D A. Prat; P. Wright

doi:10.1098/rspa.2015.0875

An efficient approach for limited-data chemical species tomography and its error bounds

N. Polydorides, S-A Tsekenis, H. McCann, V-D A. Prat, P. Wright

Research output: Contribution to journal › Article › peer-review

Abstract

We present a computationally efficient reconstruction method for the limited-data chemical species tomography problem that incorporates projection of the unknown gas concentration function onto a low-dimensional subspace, and regularisation using prior information obtained from a simple flow model. In this context, the contribution of this work is on the analysis of the projection-induced data errors and the calculation of bounds for the overall image error incorporating the impact of projection and regularisation errors as well as measurement noise. As an extension to this methodology we present a variant algorithm that preserves the positivity of the concentration image.

Original language	English
Journal	Royal Society of London. Proceedings A. Mathematical, Physical and Engineering Sciences
Volume	472
Issue number	2187
DOIs	https://doi.org/10.1098/rspa.2015.0875
Publication status	Published - 2016

Keywords

tomography
image reconstruction
regularisation

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10.1098/rspa.2015.0875

1 Finished

Fibre-laser imaging of gas turbine exhaust species
Ozanyan, K. (PI) & Mccann, H. (CoI)
1/03/13 → 30/11/16
Project: Research

7 Article
4 Conference contribution

Constrained models for optical absorption tomography
Polydorides, N., Tsekenis, A., Fisher, E. A., Chighine, A., McCann, H., Dimiccoli, L., Wright, P., Lengden, M., Benoy, T., Wilson, D., Humpries, G. & Johnstone, W., 23 Oct 2017, In: Applied Optics. 57, 7, p. B1-B9
Research output: Contribution to journal › Article › peer-review
Implementation of Non-Intrusive Jet Exhaust Species Distribution Measurements Within a Test Facility
Wright, P., Mccormick, D., Kliment, J., Ozanyan, K., Tsekenis, S., Fisher, E., McCann, H., Archilla, V., González-Núñez, A., Johnson, M., Black, J., Lengden, M., Wilson, D., Johnstone, W., Feng, Y. & Nilsson, J., Mar 2016, Aerospace Conference, 2016 IEEE. IEEE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Progress towards non-intrusive optical measurement of gas turbine exhaust species distributions
Wright, P., Mccormick, D., Ozanyan, K., Johnson, M., Black, J., Fisher, E., Chighine, A., McCann, H., Feng, Y., Khan, K., Bastock, P., Jia, F., Hewak, D., Nilsson, J., Lengden, M., Wilson, D., Armstrong, I., Benoy, T. & Johnstone, W., Jun 2015, Aerospace Conference, 2015 IEEE. IEEEXplore Digital Library: IEEE, p. 1-14 14 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

File
240 Downloads (Pure)

Cite this

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title = "An efficient approach for limited-data chemical species tomography and its error bounds",

abstract = "We present a computationally efficient reconstruction method for the limited-data chemical species tomography problem that incorporates projection of the unknown gas concentration function onto a low-dimensional subspace, and regularisation using prior information obtained from a simple flow model. In this context, the contribution of this work is on the analysis of the projection-induced data errors and the calculation of bounds for the overall image error incorporating the impact of projection and regularisation errors as well as measurement noise. As an extension to this methodology we present a variant algorithm that preserves the positivity of the concentration image.",

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author = "N. Polydorides and S-A Tsekenis and H. McCann and Prat, {V-D A.} and P. Wright",

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AU - Wright, P.

PY - 2016

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AB - We present a computationally efficient reconstruction method for the limited-data chemical species tomography problem that incorporates projection of the unknown gas concentration function onto a low-dimensional subspace, and regularisation using prior information obtained from a simple flow model. In this context, the contribution of this work is on the analysis of the projection-induced data errors and the calculation of bounds for the overall image error incorporating the impact of projection and regularisation errors as well as measurement noise. As an extension to this methodology we present a variant algorithm that preserves the positivity of the concentration image.

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KW - image reconstruction

KW - regularisation

U2 - 10.1098/rspa.2015.0875

DO - 10.1098/rspa.2015.0875

M3 - Article

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JO - Royal Society of London. Proceedings A. Mathematical, Physical and Engineering Sciences

JF - Royal Society of London. Proceedings A. Mathematical, Physical and Engineering Sciences

IS - 2187

ER -

An efficient approach for limited-data chemical species tomography and its error bounds

Abstract

Keywords

Access to Document

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Projects

Fibre-laser imaging of gas turbine exhaust species

Research output

Constrained models for optical absorption tomography

Implementation of Non-Intrusive Jet Exhaust Species Distribution Measurements Within a Test Facility

Progress towards non-intrusive optical measurement of gas turbine exhaust species distributions

Cite this