(13h) Particles Concentration Monitoring Based on Sparse Representation Using Electrical Tomography

Electrical tomography (ET) is an imaging technique which is suitable for the measurement of particles concentration in two-phase flows based on the permittivity or conductivity change of materials. Influencing by the soft-field effect and the ill-posed nature of the inversed problem in ET, the solution of ET is not unique and highly sensitive to the measurement noise. To improve the image quality, a new image reconstruction algorithm for ET based on sparse representation is proposed and implemented. An extended sensitivity matrix consisting of different type of distributions is designed as an expansion frame. The permittivity distributions based on the new frame have a natural sparse representation. Numerical simulations are carried out to investigate the performance of the proposed algorithm. Simulation results show that the proposed method can improve the image quality obviously in terms of the shape and position of objects.