Empirical Mode Decomposition Method for Processing Data Monitoring of the Subway Power Supply Network

In this article the scientific problem is raised regarding the insufficiency of processing data monitoring in relation to the subway power supply network. It is proposed to consider the modernization of the monitoring and control subsystem of the power supply network in terms of the Smart Grid concept. The article proposes an empirical mode decomposition (EMD) method for working with diagnostic parameter data monitoring by means of using Python. The authors carried out the dataframe primary processing by current and voltage during the period of 15 calendar days monitoring and obtained the decomposition of the signal into empirical modes. The results showed that the application of the EMD method made it possible to detect the presence of signal components, the content of harmonic components. This makes it possible to study the monitoring data for mutual influences, to identify signal components and to build a system for equipment programmatic search that creates interference.