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| Fast Image Reconstruction Research Based on H∞ Filtering for Electrical Resistance Tomography |
| Qifang Liu, Han Yan, Xixiang Zhang |
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Abstract 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.
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| Cite this article: |
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Qifang Liu,Han Yan,Xixiang Zhang. Fast Image Reconstruction Research Based on H∞ Filtering for Electrical Resistance Tomography[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(1): 125-132.
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2015, Vol. 8 
