title: An effective measured data preprocessing method in electrical impedance tomography.
abstract: As an advanced process detection technology, electrical impedance tomography (EIT) has widely been paid attention to and studied in the industrial fields. But the EIT techniques are greatly limited to the low spatial resolutions. This problem may result from the incorrect preprocessing of measuring data and lack of general criterion to evaluate different preprocessing processes. In this paper, an EIT data preprocessing method is proposed by all rooting measured data and evaluated by two constructed indexes based on all rooted EIT measured data. By finding the optimums of the two indexes, the proposed method can be applied to improve the EIT imaging spatial resolutions. In terms of a theoretical model, the optimal rooting times of the two indexes range in [0.23, 0.33] and in [0.22, 0.35], respectively. Moreover, these factors that affect the correctness of the proposed method are generally analyzed. The measuring data preprocessing is necessary and helpful for any imaging process. Thus, the proposed method can be generally and widely used in any imaging process. Experimental results validate the two proposed indexes.
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors.forename: Chenglong
authors.initials: C
authors.lastname: Yu
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors.forename: Shihong
authors.initials: S
authors.lastname: Yue
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors.forename: Jianpei
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors.forename: Huaxiang
authors.initials: H
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D017097:Electric Impedance; D001330:Electronic Data Processing / Q000379:methods*; D008962:Models, Theoretical; D059629:Signal-To-Noise Ratio; D013997:Time Factors; D014054:Tomography / Q000379:methods*