Tibetan Plateau vortex (TPV for short) is a kind of shallow mesoscale vortex system generated in the main body of the Tibetan Plateau. It occurs frequently, affects a wide range and causes strong disasters. It is one of the most important disaster-causing mesoscale systems in China. To fully reveal the statistical characteristics of TPVs is to lay the important basis for the study of TPVs. Among them, the accurate identification of TPVs is the key to the statistical characteristics of TPVs. With the emergence of reanalysis data with high spatial and temporal resolution, the study of TPVs has a better data basis. However, neither artificial identification method nor objective identification algorithm based on coarser resolution can be effectively applied to the current new reanalysis data. In this paper, a restricted vorticity based TPV identifying algorithm is proposed, which is suitable for high resolution reanalysis data. The method first determines TPV candidate points, divides multiple octants with the candidate points as the center, and determines the center of TPV by limiting conditions of average wind field in octants and counterclockwise rotation (the Northern Hemisphere ) conditions of octant group. The advantage of this approach is that the horizontal and vertical tracing of vortices can be detected quickly without complicated calculation and different thresholds for each pressure layer. A large sample evaluation of 15,466 TPVs (99,090 hours in total) in 42 warm seasons (May-September) from 1979 to 2020 shows that the average hit ratio of RTIA is more than 95%, the average false alarm ratio is less than 9%, and the average missing report rate is less than 5%. Therefore, the RTIA can accurately identify the centers of TPVs. In addition, the test results also show that when RTIA is applied to the reanalysis data with different spatial resolutions (e.g., 0.5°or 0.25°), the high accuracy of TPV identification can still be maintained. The identification results are mainly affected by the strength of vortexes themselves, and the identification accuracy of weak vortexes is lower than that of strong vortexes. This method can be used as a reference for the identification of other mesoscale vortexes.