水电厂机组设备的状态监测系统采集了大量监测对象的海量数据,有效分析机组设备状态需要基于对多元状态监测对象数值规律的充分挖掘,因此,在海量状态监测数据的基础上构建综合分析平台是一条值得探索的途径。本文以水电厂机组状态监测及故障分析系统为项目背景,从构建状态监测数据仓库综合分析平台的角度,讨论了用户离散性、随机性的分析需求与传统状态量分析方法如何更有效结合的问题,并提出了一种解决策略,即通过相关性分析实现离散输入的快速关联和综合分析。 The state monitoring system of hydropower plant equipment collected a large number of monitoring objects of massive data, the effective analysis of unit equipment status based on the numerical monitoring of multiple conditions of the law of the full mining, therefore, in the state of monitoring data to build a comprehensive analysis platform is A worth exploring way. In this paper, the condition monitoring and fault analysis system of hydropower plant is taken as the project background. From the perspective of building a comprehensive analysis platform for condition monitoring data warehouse, the problem of how user’s discreteness and stochastic analysis needs to be more effectively combined with traditional state quantity analysis methods , And proposes a solution strategy, that is, through the correlation analysis to achieve rapid correlation and comprehensive analysis of discrete inputs.