Electrical capacitance volume tomography(ECVT) is a recently-developed technique for real-time,non-invasive 3D monitoring of processes involving materials with strong contrasts in dielectric permittivity.This work is ...Electrical capacitance volume tomography(ECVT) is a recently-developed technique for real-time,non-invasive 3D monitoring of processes involving materials with strong contrasts in dielectric permittivity.This work is first application of the method to visualization of water flow in soil.We describe the principles behind the method,and then demonstrate its use with a simple laboratory infiltration experiment.32 ECVT sensors were installed on the sides of an empty PVC column.Water was poured into the column at a constant rate,and ECVT data were collected every second.The column was then packed with dry sand and again supplied with water at a constant rate with data collected every second.Data were analyzed to give bulk average water contents,which proved consistent with the water supply rates.Data were also analyzed to give 3D images(216 voxels) allowing visualization of the water distribution during the experiments.Result of this work shows that water infiltration into the soil,wall flow,progress of the unstable wetting front and the final water distribution are clearly visible.展开更多
In the long distance transportation of slurry filled for mining filling,there exist complex variation rules of pressure and flow velocity,pipe distribution location and other influencing factors.Electrical capacitance...In the long distance transportation of slurry filled for mining filling,there exist complex variation rules of pressure and flow velocity,pipe distribution location and other influencing factors.Electrical capacitance tomography(ECT)is a technique for visualizing two-phase flow in a pipe or closed container.In this paper,a visual detection method was proposed by image reconstruction of core,laminar,bubble and annular flow based on ECT technology,which reflects distribution of slurry in deep filling pipeline and measures the degree of blockage.There is an error between the measured and the real two-phase flow distribution due to two factors,which are immature image reconstruction algorithm of ECT and difference of flow patterns leading to degrees of error.In this paper,convolutional neural networks(CNN)is used to recognize flow patterns,and then the optimal image is calculated by the improved particle swarm optimization(PSO)algorithm with weights using simulated annealing strategy,and the fitness function is improved based on the results of the shallow neural network.Finally,the reconstructed binary image is further processed to obtain the position,size and direction of the blocked pipe.The realization of this method provides technical support for pipeline detection technology.展开更多
The recalibration of electrical capacitance tomography (ECT) system is one of the key problems in keeping the system running steadily.However, for engineering application in solids/gas transport,online calibration can...The recalibration of electrical capacitance tomography (ECT) system is one of the key problems in keeping the system running steadily.However, for engineering application in solids/gas transport,online calibration can not be implemented and the data from this sensor may be unreliable due to the sensor pipe interior wall abrasion during pneumatic transport,so the solids concentration calculated from the reconstructed image based on these data will be highly inaccurate.The simulations show that, the inter-electrode relative capacitance variation of electrode pair spacing 1 is the most sensitive to the abrasion of sensor pipe interior wall, so this relative capacitance variation when the sensor is filled with air can be used as an indicator demanding offline system recalibration when the wall abrasion goes significant.Furthermore, while the pipe interior wall abrasion is not very serious, online correcting measured inter-electrode capacitance with wall capacitance variation can improve the accuracy of concentration calculation.展开更多
文摘Electrical capacitance volume tomography(ECVT) is a recently-developed technique for real-time,non-invasive 3D monitoring of processes involving materials with strong contrasts in dielectric permittivity.This work is first application of the method to visualization of water flow in soil.We describe the principles behind the method,and then demonstrate its use with a simple laboratory infiltration experiment.32 ECVT sensors were installed on the sides of an empty PVC column.Water was poured into the column at a constant rate,and ECVT data were collected every second.The column was then packed with dry sand and again supplied with water at a constant rate with data collected every second.Data were analyzed to give bulk average water contents,which proved consistent with the water supply rates.Data were also analyzed to give 3D images(216 voxels) allowing visualization of the water distribution during the experiments.Result of this work shows that water infiltration into the soil,wall flow,progress of the unstable wetting front and the final water distribution are clearly visible.
基金Project(51704229)supported by the National Natural Science Foundation of ChinaProject(2018YQ2-01)supported by the Outstanding Youth Science Fund of Xi’an University of Science and Technology,China。
文摘In the long distance transportation of slurry filled for mining filling,there exist complex variation rules of pressure and flow velocity,pipe distribution location and other influencing factors.Electrical capacitance tomography(ECT)is a technique for visualizing two-phase flow in a pipe or closed container.In this paper,a visual detection method was proposed by image reconstruction of core,laminar,bubble and annular flow based on ECT technology,which reflects distribution of slurry in deep filling pipeline and measures the degree of blockage.There is an error between the measured and the real two-phase flow distribution due to two factors,which are immature image reconstruction algorithm of ECT and difference of flow patterns leading to degrees of error.In this paper,convolutional neural networks(CNN)is used to recognize flow patterns,and then the optimal image is calculated by the improved particle swarm optimization(PSO)algorithm with weights using simulated annealing strategy,and the fitness function is improved based on the results of the shallow neural network.Finally,the reconstructed binary image is further processed to obtain the position,size and direction of the blocked pipe.The realization of this method provides technical support for pipeline detection technology.
文摘The recalibration of electrical capacitance tomography (ECT) system is one of the key problems in keeping the system running steadily.However, for engineering application in solids/gas transport,online calibration can not be implemented and the data from this sensor may be unreliable due to the sensor pipe interior wall abrasion during pneumatic transport,so the solids concentration calculated from the reconstructed image based on these data will be highly inaccurate.The simulations show that, the inter-electrode relative capacitance variation of electrode pair spacing 1 is the most sensitive to the abrasion of sensor pipe interior wall, so this relative capacitance variation when the sensor is filled with air can be used as an indicator demanding offline system recalibration when the wall abrasion goes significant.Furthermore, while the pipe interior wall abrasion is not very serious, online correcting measured inter-electrode capacitance with wall capacitance variation can improve the accuracy of concentration calculation.
