Research On The Algorithm Of Electrical Capacitance Tomography

Electrical capacitance tomography (ECT) technique has the advantage of being non-intrusive, fast in response, simple in structure, low in cost and good in security, so it is one technique which has great developing potential in industrial application. ECT technique can be applied in many areas of two-phase flow detection.At present, linear back-projection (LBP) algorithm and iterative algorithm are the most common used algorithms. LBP algorithm has the advantage of fast speed in image reconstruction. This algorithm is fit for real-time image reconstruction, but its reconstruction quality is not accurate. Iterative algorithm is a multi-step algorithm; the reconstruction image will be amended repeatedly to acquire more accurate result. But more time consuming is its disadvantage. The quality of real-time image reconstructed by ECT system does not satisfy production needs, which limits ECT application in practical industry.There are two main reasons that cause ECT reconstruction images not accurate: the soft field characteristic of ECT sensor sensitivity, and the very small projection data. Two aspects to improve ECT image reconstruction quality are investigated in this paper. One is increasing the number of projection data to obtain more information of medium distribution; the other is researching rapid and accurate image reconstruction algorithm.Using more measurement electrodes in ECT system can obtain more projection data. However, when electrode number is increased, the electrode width must be lessened. This will bring detection difficulty of measured circuit. In this paper, artificial neural network technique is applied to acquire more projection data. 16-electrode ECT system's projection data is acquired when the 28 measurements of an 8-electrode ECT sensor are fed into a pre-trained neural network. Levenberg-Marquardt algorithm and Bayesian regularization are used in network training and the network can convergence rapidly and generalize well. The simulation results show this algorithm can improve image reconstruction quality.In this paper, an image reconstruction algorithm based on singular value decomposition (SVD) of sensitivity matrix is proposed; the inverse of ECT sensitivity matrix is calculated use SVD method. This method can obtain a more accurate approximation of sensitivity inverse, andthe smaller singular value can be neglected to improve stability of the reconstruction result. The time consumed in reconstruction is similar to that of LBP algorithm. The image result is more accurate than that of LBP algorithm and similar to that of iterative algorithm. So this new method is a real-time and more accurate reconstruction algorithm.