Abstract: Due to the system fault or external disturbance, the drift phenomenon of monitoring data often occurs.As for hydraulic structures, because of the structure similarity and the correlation of measuring points arrangement, the monitoring data often have significant spatial correlation making them possess similar variation rules, so as to provide a discriminant basis for the drift correction of the measuring points.According to the above principle, the density clustering analysis based on similar measuring points was proposed, and the DBSCAN algorithm was used to determine the drift interval and drift amount of measuring points.At the same time, in order to overcome the problems of correction mutation and cluster adhesion, the sliding window mode was introduced to establish a dynamic correction model for monitoring data drift.The correction process was divided into two parts, data correction within window and window sliding correction.The engineering example showed that this method has strong applicability and high precision, which provides a new automatic correction idea for the data drift problem of similar measuring points in hydraulic structures.