Research Article
Research of Mobile Inspection Substation Platform Data Analysis Method and System
@INPROCEEDINGS{10.1007/978-3-319-44350-8_6, author={Peng Li and Ruibin Gao and Lu Qu and Wenjing Wu and Zhiqiang Hu and Guang Guo}, title={Research of Mobile Inspection Substation Platform Data Analysis Method and System}, proceedings={Industrial IoT Technologies and Applications. International Conference, Industrial IoT 2016, GuangZhou, China, March 25-26, 2016, Revised Selected Papers}, proceedings_a={INDUSTRIALIOT}, year={2016}, month={9}, keywords={Mobile inspection substation platform Data analysis Data mining Association rules Improved Apriori algorithm}, doi={10.1007/978-3-319-44350-8_6} }- Peng Li
Ruibin Gao
Lu Qu
Wenjing Wu
Zhiqiang Hu
Guang Guo
Year: 2016
Research of Mobile Inspection Substation Platform Data Analysis Method and System
INDUSTRIALIOT
Springer
DOI: 10.1007/978-3-319-44350-8_6
Abstract
With the extensive construction of mobile inspection substation platform, various kinds of substation information is going to be digitized into databases. The scale of data is increasing day by day, which is large enough to provide a data base for data mining technology. Association rules has been applied successfully in various fields which makes it as one of the most active branches in the field of data mining research, development and application. Association rules used in smart substation data analysis to find some rules that people cannot find easily and it can find laws of equipment aging and failures also. This will benefit substation management, as well as equipment maintenance. In this article, we present a data analysis system based on mobile inspection substation platform. And the improved Apriori algorithm is used in substation data analysis to dig out some of the basic laws which provide effective information for substation management.
