Indiana University-Purdue University Indianapolis (IUPUI) / The Electrical capacitance tomography (ECT) method has recently been adapted
to obtain tomographic images of the cross section of a diesel particulate filter (DPF).
However, a soot mass estimation algorithm is still needed to translate the ECT image
pixel data to obtain soot load in the DPF. In this research, we propose an estimation
method to quantify the soot load in a DPF through an inverse algorithm that uses the
ECT images commonly generated by a back-projection algorithm. The grayscale pixel
data generated from ECT is used in a matrix equation to estimate the permittivity
distribution of the cross section of the DPF. Since these permittivity data has direct
correlation with the soot mass present inside the DPF, a permittivity to soot mass
distribution relationship is established first. A numerical estimation algorithm is then
developed to compute the soot mass accounting for the mass distribution across the
cross-section of the DPF as well as the dimension of the DPF along the exhaust
flow direction. Firstly, ANSYS Electronic Desktop software is used to compute the
capacitance matrix for different amounts of soot filled in the DPF, furthermore it also
analyzed different soot distribution types applied to the DPF. The Analysis helped
in constructing the sensitivity matrix which was used in the numerical estimation
algorithm. Experimental data have been further used to verify the proposed soot
estimation algorithm which compares the estimated values with the actual measured
soot mass to validate the performance of the proposed algorithm.
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/22344 |
Date | 05 1900 |
Creators | Hassan, Salah E. |
Contributors | Anwar, Sohel, El-Mounayri, Hazim, Tovar, Andres |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | en_US |
Detected Language | English |
Type | Thesis |
Rights | Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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