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Research on Multi-Dimensional Analysis Method of Power Equipment Condition Monitoring Based on OLAP

机译:基于OLAP的电力设备状态监测多维分析方法研究

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Large data analysis of power equipment condition monitoring is a hot research topic, which is of great significance to ensure the safe and stable operation of power equipment. OLAP can quickly access and analyze data from multiple angles. It is an important technical means to realize large data analysis of power equipment condition monitoring. Aiming at the problems of high cost of connection operation and slow query speed in distributed relational OLAP data model, a state monitoring data model for power equipment based on connectionless hierarchical coding is proposed. It codes the hierarchical information of dimension table and stores into the fact table to reduce connection operation and optimize performance. The experimental results show that this proposed method outperforms the conventional data model in data loading speed, roll-up execution time and storage overhead.
机译:电力设备状态监测的大数据分析是当前研究的热点,对确保电力设备安全稳定运行具有重要意义。 OLAP可以从多个角度快速访问和分析数据。实现电力设备状态监测的大数据分析是重要的技术手段。针对分布式关系OLAP数据模型中连接操作成本高,查询速度慢的问题,提出了一种基于无连接分层编码的电力设备状态监测数据模型。它对维度表的分层信息进行编码并存储到事实表中,以减少连接操作并优化性能。实验结果表明,该方法在数据加载速度,汇总执行时间和存储开销方面均优于常规数据模型。

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