大坝位移监控模型及监控指标拟定研究OA

To address the problems of insufficient accuracy in determining statistical model coefficients,difficulties in component extraction,and unreasonable formulation of monitoring indicators in the analysis of dam monitoring data,this paper introduces the Grey Wolf Algorithm to construct a statistical monitoring model for dam horizontal displacement.Taking the horizontal displacement monitoring data of a reservoir dam section from 2010 to 2020 as an example,the Grey Wolf Algorithm is used to solve the parameter regression of the displacement model,and the typical small probability method is combined to formulate the dam horizontal displacement monitoring indicators.The results show that the Grey Wolf Algorithm has good convergence and stability in model parameter optimization,and the established horizontal displacement statistical model has high fitting accuracy and good prediction effect,which can realistically reflect the deformation law of the dam body.According to the proposed monitoring indicators,the displacement of each measuring point of the dam body is within the safe range.The study shows that the Grey Wolf Algorithm can effectively improve the accuracy and reliability of the dam displacement statistical model,providing a scientific basis for dam safety operation assessment and monitoring indicator formulation.