关键词: 实时大数据, 输变电线路, 故障监测, 分布式迭代自组织数据分析算法（ISODATA）, 分布式模糊k最近邻分类算法（KNN）

Abstract: Since the monitoring data of transmission lines are the largest part of the amount of data in the smart grid, including not only the online condition monitoring data, but also the basic information of the devices, the experimental data, defect records, it requires a higher performance of the reliability and real-time in the data processing. The paper designs and realizes a novel model to solve the real-time fault monitoring of transmission lines according to the practical application of power transmission line faults’ types. In particular, the paper constructs a distributed cluster based on Spark, an efficient real-time data processing system, for the transmission line fault real-time monitoring, develops a distributed ISODATA and fuzzy KNN big data analysis algorithm. Compared with standalone KNN algorithm, it improves 70.75% efficiency of the time performance. Experimental results demonstrate the proposed approach has the obvious advantages of the computational efficiency.

Key words: real-time big data, transmission lines, fault monitoring, distributed Iterative Self Organizing Data Analysis Techniques Algorithm（ISODATA） algorithm, distributed fuzzy k-Nearest Neighbor（KNN） algorithm