Dynamical electric wire tomography: Time series approach

Djebar Baroudi, Jari Kaipio, Erkki Somersalo

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)

Abstract

The inverse problem of estimating gas temperature distribution based on the measurement of resistances of thin metal filaments spanned across the gas flow is discussed. The estimation is based on the fact that the resistance of the filament material is a function of the temperature. The gas temperature is modelled as a time-dependent stochastic process, and the temperature estimation is performed by using Kalman filters. The proposed method is tested both with numerically-produced synthetic data and with experimental data.
Original languageEnglish
Pages (from-to)799-813
JournalInverse Problems
Volume14
Issue number4
DOIs
Publication statusPublished - 1998
MoE publication typeA1 Journal article-refereed

Fingerprint

Electric wire
Tomography
Time series
Filament
Synthetic Data
Gas Flow
Temperature Distribution
Random processes
Inverse problems
Gases
Kalman filters
Kalman Filter
Temperature
Flow of gases
Stochastic Processes
Inverse Problem
Temperature distribution
Metals
Experimental Data
Resistance

Cite this

Baroudi, Djebar ; Kaipio, Jari ; Somersalo, Erkki. / Dynamical electric wire tomography : Time series approach. In: Inverse Problems. 1998 ; Vol. 14, No. 4. pp. 799-813.
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Baroudi, D, Kaipio, J & Somersalo, E 1998, 'Dynamical electric wire tomography: Time series approach', Inverse Problems, vol. 14, no. 4, pp. 799-813. https://doi.org/10.1088/0266-5611/14/4/003

Dynamical electric wire tomography : Time series approach. / Baroudi, Djebar; Kaipio, Jari; Somersalo, Erkki.

In: Inverse Problems, Vol. 14, No. 4, 1998, p. 799-813.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Dynamical electric wire tomography

T2 - Time series approach

AU - Baroudi, Djebar

AU - Kaipio, Jari

AU - Somersalo, Erkki

PY - 1998

Y1 - 1998

N2 - The inverse problem of estimating gas temperature distribution based on the measurement of resistances of thin metal filaments spanned across the gas flow is discussed. The estimation is based on the fact that the resistance of the filament material is a function of the temperature. The gas temperature is modelled as a time-dependent stochastic process, and the temperature estimation is performed by using Kalman filters. The proposed method is tested both with numerically-produced synthetic data and with experimental data.

AB - The inverse problem of estimating gas temperature distribution based on the measurement of resistances of thin metal filaments spanned across the gas flow is discussed. The estimation is based on the fact that the resistance of the filament material is a function of the temperature. The gas temperature is modelled as a time-dependent stochastic process, and the temperature estimation is performed by using Kalman filters. The proposed method is tested both with numerically-produced synthetic data and with experimental data.

U2 - 10.1088/0266-5611/14/4/003

DO - 10.1088/0266-5611/14/4/003

M3 - Article

VL - 14

SP - 799

EP - 813

JO - Inverse Problems

JF - Inverse Problems

SN - 0266-5611

IS - 4

ER -