TY - JOUR
T1 - Fast Image Reconstruction Research Based on H∞ Filtering for Electrical Resistance Tomography
AU - Qifang Liu, Han Yan & Xixiang Zhang
JO - Journal of Fiber Bioengineering and Informatics
VL - 1
SP - 125
EP - 132
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.3993/jfbi03201512
UR - https://global-sci.org/intro/article_detail/jfbi/4692.html
KW - Electrical Resistance Tomography
KW - H∞ Filtering
KW - Image Reconstruction
AB - In order to improve the image reconstructed quality affected by soft filed feature and the speed of dynamic
on-line data processing in Electrical Resistance Tomography, we propose a fast image reconstruction
algorithm based on H∞ filtering theory. Mainly, on the H∞ filtering principle, a dynamic system is
formulated firstly, whose inputs have unknown disturbances including noise errors and model errors, and
the outputs have the estimation errors. Then, making the H∞ norm of this dynamic system as a cost
function, a fast H∞ filtering algorithm is proposed whose criterion is to guarantee that the worst-cast
effect of disturbance on estimation error is smaller than a given boundary. Experimental work was carried
out for three typical flow distributions. Results showed that H∞ filter method improves the resolution of
the reconstructed images and gains the strong robustness and anti-interference performance in unknown
interference noise conditions. In addition, it dramatically reduces the computational time compared with
the traditional Gauss-Newton iterative and Kalman filter methods. Therefore, the method is suitable
for on-line multiphase flow measurement.