## 2 Intelligent Anomaly Identification Model of Uplift Pressure
### Anomaly Identification Model of Uplift Pressure Based on DBSCAN  
Through the above analysis about the advantages and disadvantages of the DBSCAN, it can be known that the DBSCAN unsupervised clustering algorithm has good applicability for the identification of abnormal uplift pressure data: 1 the abnormal occurrence data of uplift pressure usually appear in the conversion process of different states. The DBSCAN can precisely identify noise points between different clusters, which respond well to the occurrence characteristics of abnormal monitoring data. 2 Given that the uplift pressure is closely related to the reservoir water level, and it presents similar one-to-one correspondence characteristics, the DBSCAN can identify classes with arbitrary shapes [37], so it can precisely identify the monitoring data clustering of the uplift pressure in the normal and the abnormally stable state. 3 For data with high-dimensional, uneven density and large distance, the clustering effect of the DBSCAN will be worse. The above problems have not occurred in uplift pressure monitoring data because of the reservoir operation mode and monitoring method. Therefore, the anomaly identification model of the uplift pressure proposed in this paper can use the advantages of the DBSCAN algorithm and avoid its defects. This anomaly identification model has good applicability to the uplift pressure, of which the calculation flow is shown in Figure 2.  
Figure 1: Flow chart of DBSCAN algorithm.  
The calculation steps of the anomaly identification model of uplift pressure based on DBSCAN are as follows:  
1. Normalizing the monitoring data of upstream water level and uplift pressure of the concrete dam can fully reflect the monitoring data characteristics.
2. The DBSCAN algorithm is used to identify monitoring points of the uplift pressure one by one. According to the identification results, they are divided into normal and abnormal monitoring points. Repeat this step until all monitoring points of the uplift pressure have completed the anomaly identification.
3. Monitoring points are divided into two major types according to quantity and spatial distribution. One is individual or discontinuous distribution points, and another is multiple and continuous distribution points.
4. If an individual monitoring point is diagnosed as abnormal, or the spatial distribution of the abnormal monitoring point is not continuous, operating personnel should focus on checking whether the corresponding monitoring equipment is operating normally. Based on the inspection results, operating personnel determine whether to carry out the structural diagnosis of the concrete dam.
5. If multiple monitoring points are diagnosed as abnormal, and the spatial distribution of the abnormal monitoring points is relatively continuous, operating personnel should focus on the changes in the structural behavior. The structural diagnosis is carried out for the concrete dam under abnormal uplift pressure.
6. According to the above analysis, we can clarify the abnormal conditions of uplift pressure and its influence on the structural behavior, which can guide the later operation, management, and maintenance of the concrete dam.