In this study, according to the characteristics of specific application scenarios for the IT equipment identification of State Grid, accurate identification and positioning of the equipment is realized with improved Faster-RCNN, thereby improving the management efficiency of the grid data center. The algorithm is improved mainly in terms of the attention mechanism, the initial anchor box adjustment and the anchor box fusion. The comparison with common image algorithms shows that the improved model has the convergence speed and the accuracy increased by 30% and 1%, respectively.