基于云概率密度分布估计的大坝监测数据分析

大坝运行监测易受自然环境和监测条件影响，存在时间和空间上的变异性，监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础，并与空间数据辐射思想相结合，建立了云滴概率密度分布估计模型，然后导出云概率密度分布函数，依据样本监测数据推求母体空间数据的分布特征，并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征，得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明，云概率密度分布估计不仅能有效合理地分析大坝的运行状态，而且能够依据云数字特征来判断监测状态和监测环境的异常变化。 

Analysis on dam monitoring data based on cloud probability density estimation

The dam monitoring is susceptible to the natural environment and monitoring conditions, and is variable in time and space, so the monitoring data is uncertain. Based on the randomness and uncertainty analysis method of cloud theory, and in combination with the ideas of spatial data radiation, the model of probability density distribution estimation of cloud droplets was established, and the probability density distribution function of cloud droplets was also derived. The distribution characteristic of matrix was obtained by the sample data, and the calculation program was designed on the basis of cloud transformation with backward algorithm. The cloud droplets probability density distribution characteristics and numerical characteristics of tube monitoring data and deformation data from 1979~1999 for Luhun Reservoir are analyzed, so the distribution characteristics and operation condition of monitoring data of the dam is estimated. The results show that the cloud droplet probability density distribution theory can be used to analyze the dam operation condition effectively, and further determine the change of monitoring environment and condition according to the numerical characters of cloud droplets.