Research on Multi-Dimensional Analysis Method of Power Equipment Condition Monitoring Based on OLAP
Li Xi, Hongkai Wang, Jinhu Li, Pei Xu-bin, Yu Zhanpeng · 2019
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.