Abstract: Aiming at the problems of low efficiency and insufficient intelligence of data quality evaluation in dam safety monitoring, in order to meet the needs of real-time data quality evaluation of high-frequency automatic acquisition of dams, a quality evaluation criteria of safety monitoring data composed of six evaluation factors and related evaluation criteria from the four aspects of accuracy, integrity, timeliness and repair ability were proposed.And then a quality evaluation algorithm on historical data of dam safety monitoring was established by the improved random forest algorithm based on AUC value.The algorithm was applied to the evaluation of multi-year safety monitoring data of Liushugou concrete face rockfill dam in Xinjiang.The results showed that the random forest algorithm improved by AUC value was better than the original algorithm.When the feature attributes was 3,the effect was the best.The generalization error for the test set could reach 0.019 5,the average accuracy was stable at 96.97%,and the average accuracy of 10-fold cross validation reached 97.77%,which proved the feasibility of the new algorithm.