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.

Qifang Liu, Han Yan and Xixiang Zhang. (2015). Fast Image Reconstruction Research Based on H∞ Filtering for Electrical Resistance Tomography. Journal of Fiber Bioengineering and Informatics. 8 (1). 125-132. doi:10.3993/jfbi03201512