Temperature field estimation using electrical impedance profiling methods. I. Reconstruction algorithm and simulated results

1994 ◽  
Vol 10 (2) ◽  
pp. 209-228 ◽  
Author(s):  
K. D. Paulsen ◽  
M. J. Moskowitz ◽  
T. P. Ryan
Keyword(s):  
Temperature Field ◽  
Electrical Impedance ◽  
Reconstruction Algorithm ◽  
Field Estimation

Patch-based sparse reconstruction for electrical impedance tomography

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Qi Wang ◽  
Pengcheng Zhang ◽  
Jianming Wang ◽  
Qingliang Chen ◽  
Zhijie Lian ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Sparse Representation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Inverse Operator ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Content Type ◽  
Ill Posed ◽  
High Level

Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity. Findings Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Originality/value EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

scholarly journals A Method for Reconstruction of Boiler Combustion Temperature Field Based on Acoustic Tomography

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuhui Wu ◽  
Xinzhi Zhou ◽  
Li Zhao ◽  
Chenlong Dong ◽  
Hailin Wang
Keyword(s):  
Temperature Field ◽  
Temperature Distribution ◽  
Optimal Parameter ◽  
Interpolation Method ◽  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Least Square ◽  
Temperature Fields ◽  
Acoustic Tomography ◽  
Measured Temperature

Acoustic tomography (AT), as a noninvasive temperature measurement method, can achieve temperature field measurement in harsh environments. In order to achieve the measurement of the temperature distribution in the furnace and improve the accuracy of AT reconstruction, a temperature field reconstruction algorithm based on the radial basis function (RBF) interpolation method optimized by the evaluation function (EF-RBFI for short) is proposed. Based on a small amount of temperature data obtained by the least square method (LSM), the RBF is used for interpolation. And, the functional relationship between the parameter of RBF and the root-mean-square (RMS) error of the reconstruction results is established in this paper, which serves as the objective function for the effect evaluation, so as to determine the optimal parameter of RBF. The detailed temperature description of the entire measured temperature field is finally established. Through the reconstruction of three different types of temperature fields provided by Dongfang Boiler Works, the results and error analysis show that the EF-RBFI algorithm can describe the temperature distribution information of the measured combustion area globally and is able to reconstruct the temperature field with high precision.

scholarly journals Analysis of severe convective events from two operational dual polarisation doppler radars

2006 ◽  
Vol 6 (3) ◽  
pp. 397-405
Author(s):  
M. Celano ◽  
P. P. Alberoni ◽  
V. Levizzani ◽  
A. R. Holt
Keyword(s):  
Temperature Field ◽  
Classification Scheme ◽  
Gradual Increase ◽  
Severe Storms ◽  
Cloud Systems ◽  
Po Valley ◽  
Radar Systems ◽  
Field Estimation ◽  
Points Of View

Abstract. The recent gradual increase in the use of polarimetric radars prompts for possible improvements in the estimation of precipitation and the identification of the prevailing hydrometeor type. An analysis of different convection episodes (20 May 2003, 4 and 7 May 2004) is conducted in order to explore the attenuation effects at C band and their consequences on the rainfall field estimation using two polarimetric radars in the Po Valley, Italy, located about 90 km apart. A hydrometeor classification scheme, developed at the National Severe Storms Laboratory (NSSL), is used to detect the microphysical structure of the different cloud systems. The work is focused on the reconstruction of the 3-D organisation of the convective events, highlighting how the two radar systems ''see'' the storms from different points of view. Furthermore, the two distinct observations and the temperature field are used to correct the effect of attenuation.

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