Electrical impedance tomography technology ( EIT) is one of the methods to solve the corrosion localization problem of grounding grid. In order to improve the ill-posedness of EIT inverse problem of grounding grid, improve the stability of the solution and the clarity of the reconstructed image, a hybrid regularization ( Tikhonov-TV) grounding grid imaging algorithm combining classical Tikhonov regularization and total variation regularization (TV) is proposed. Firstly, on the basis of cyclic measurement principle, this paper innovatively uses COMSOL and MATLAB co-simulation to obtain the voltage data of grounding grid EIT forward problem model. Secondly, on the basis of theoretical analysis, the field resistivity distributions of the two grounding grid inverse problem models based on prior topological information and unknown topological information are solved respectively with Tikhonov-TV regularization EIT algorithm. Finally, the EIT reconstruction images of grounding grid for Tikhonov, TV and Tikhonov-TV three regularization algorithms were compared with simulation and experiment, and the resistivity mean square error (resistivity MSE) and transversal resistivity curve were adopted to measure the image quality, the experiment results show that the resistivity MSE in corrosion condition at locations 1 and 2 places based on prior topological information reaches 1. 27×10 -15 and 1. 59×10 -15 respectively, and the resistivity mean square error is the minimum. The results show that the Tikhonov-TV regularization algorithm proposed can effectively improve the ill-posedness of EIT inverse problem, and achieve the best convergence performance. The reconstructed images are better than those of Tikhonov and TV regularization algorithms.