Data Mining Integration of Power Grid Companies Enterprise Asset Management

  • Oleg Protalinskiy
  • Nikita Savchenko
  • Anna KhanovaEmail author
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 260)


The issues of integration at the level of enterprise asset management systems data (EAM-systems), ontological modeling systems and data mining on defect identification in electrical equipment of Power Grid Companies are considered. Transformation of EAM-system data will be provided by special converters at the syntactic level, and at the semantic level—by the ontological model of defects and equipment of Power Grid Companies. In order to integrate EAM data with the Data Mining module, ETL procedures (Extract, Transform, Load) are used to load information about defects and equipment of a Power Grid Company. It is proposed to use artificial neural networks and decision trees for the production processes intellectualization of Power Grid Companies. Ontology and data mining models are integrated at the level of metadata concerning defects and equipment.


Data integration Defect Electrical equipment Data mining Ontology Neural networks Decision trees 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Moscow Power Engineering InstituteMoscowRussia
  2. 2.Astrakhan State Technical UniversityAstrakhanRussia

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