On-line Monitoring of Capacitive Equipment Based on Big Data

Dongliang Wei, Zhi Wang, Jia Zhou, Jiangtian Chen
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Abstract

With the development of the country in information technology, and those technology products are also used in life. Such as capacitive devices in power systems. But capacitive equipment will also have some failures, so it is necessary to monitor it online. Now researchers have found a lot of online monitoring methods, but in most of the current monitoring methods, the monitoring process will produce a huge amount of data, which is very large, so that technicians may miss some important data. In order to solve this problem which can not be discovered early because of the excessive amount of data, this paper adopts some methods based on big data to dig through the data the data obtained by the dig algorithm are statistically analyzed in big data technology. Using the data collected in this paper, through the analysis and research of these data, the results show that the application of big data technology to the on-line monitoring of capacitive equipment is very accurate and practical.
基于大数据的电容性设备在线监测
随着国家在信息技术方面的发展,而那些技术产品也在生活中得到了应用。如电力系统中的容性器件。但容性设备也会出现一些故障,因此有必要对其进行在线监测。现在研究人员已经发现了很多在线监测的方法,但是在目前的大多数监测方法中,监测过程中会产生大量的数据,数据量非常大,使得技术人员可能会遗漏一些重要的数据。为了解决这一由于数据量过大而无法及早发现的问题,本文采用了一些基于大数据的方法对数据进行挖掘,挖掘算法得到的数据在大数据技术中进行统计分析。利用本文收集的数据,通过对这些数据的分析和研究,结果表明,将大数据技术应用于电容性设备的在线监测是非常准确和实用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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