MATEC Web Conf.
Volume 226, 2018XIV International Scientific-Technical Conference “Dynamic of Technical Systems” (DTS-2018)
|Number of page(s)||7|
|Section||4 Fundamental methods of system analysis, modeling and optimization of dynamic systems|
|Published online||07 November 2018|
Analysis of heterogeneous information and diagnostics of complex technical systems based on methods of diakoptics and correlation analysis
Platov South-Russian State Polytechnic University (NPI), 346400 Novocherkassk, Russia
* Corresponding author: firstname.lastname@example.org
The article is devoted to the investigation of the applicability of the correlation analysis for the processing of heterogeneous data obtained from complex technical systems. In this article, heterogeneous data is understood to mean heterogeneous data obtained from means of monitoring the state of individual objects. The proposed approach is proposed to be used to diagnose complex technical systems using the example of digital substations. For this purpose, an imitation model for power substation based on the method of diakoptics was developed. And all components of the system, regardless of their physical functioning principles, are represented in the form of electrical sub-models. The substitution schemes based on operational amplifiers are used. The model simulates the operation of measuring current and voltage transformers, power transformer, circuit breaker and relay protection. To test the proposed approach, we also considered an amplifier circuit based on three operational amplifiers. The calculation of the circuit is described, as well as the simulation of the circuit in the MicroCap environment. The simulation was carried out with the aim of realizing parametric and structural diagnostics on the basis of correlation analysis. The results of modeling the applicability of the proposed approach for both parametric and structural diagnostics is proved operability.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.