Application of Big Data Clustering Algorithm in Electrical Engineering Automation

Yongchang Zhang, Zhe Zhang
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Abstract

The existing control methods have the problem of imperfect automatic distribution linkage model, which leads to excessive noise in the process of practical application. This paper designs an electrical engineering automation control method based on big data clustering algorithm, obtains the load parameters of power cable laying mode, arranges the cable channels hierarchically, extracts the technical characteristics of electrical engineering automation control, integrates the equipment operation information, builds the automatic distribution linkage model, mines the data rules of power index, sets the distribution structure of electrical equipment by big data clustering algorithm, and centrally configures the functional units.Experimental Results. Compared with the other two control methods, the average noise of this control method is 19.774 dB, 35.462 dB, and 36.323 dB, which proves that the control method combined with big data clustering algorithm has better practical application effect.
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大数据聚类算法在电气工程自动化中的应用
现有的控制方法存在自动配电联动模型不完善的问题,导致实际应用过程中噪声过大。本文设计了一种基于大数据聚类算法的电气工程自动化控制方法,获取电力电缆敷设方式的负荷参数,分层布置电缆通道,提取电气工程自动化控制的技术特点,整合设备运行信息,建立自动配电联动模型,挖掘电力指标的数据规律,通过大数据聚类算法设置电气设备分布结构,集中配置功能单元。实验结果。与其他两种控制方法相比,该控制方法的平均噪声分别为19.774 dB、35.462 dB和36.323 dB,证明该控制方法结合大数据聚类算法具有更好的实际应用效果。
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