A novel component separation method for deformation monitoring of rockfill dams

Abstract

High dams are constructed in mountain valley areas with extremely complex geomorphologies, geologies, and operating environments. The dam body and foundation are subjected to large hydraulic loadings and high stress levels, where many factors affect the structural deformation of the dam, making dam safety monitoring and risk assessment difficult. Since dam deformation is critical for evaluating safe operation, a novel dam deformation monitoring model based on the component separation method is proposed, which can provide scientific significance and high application value for operational safety control. The deformation monitoring data include deformation caused by the water level, the temperature, and the time effect. The homologous monitoring sequence points are selected, and a safety monitoring model is proposed based on the physical causes and the independent component signal decomposition technology. First, the aging component can be extracted by using the correlation consistency of a specific measurement point, where the environment is almost the same at the same time of year, such as the temperature and the water level. Then, fast independent component analysis algorithm is applied to further extract the dam deformation induced by the water level and the temperature via correlation analysis. Finally, a deformation monitoring model based on the component separation can be successfully constructed by combining models of the three components. The proposed dam deformation model can overcome problems of large covariance of deformation component, large collinear interference of periodic component separation, and unstable separation. It is further applied to a high face rockfill dam, and the results shows that the multiple correlation coefficient is greater than 0.995 and the mean absolute percentage error is less than 1.37%, demonstrating the high accuracy and stable separation of the components produced by using this model.