ADVANCED POWER GRID ANALYSIS IN METALLURGICAL PLANTS WITH USAGE OF DISCRETE FOURIER TRANSFORM

1 GRYCZ Ondřej
Co-authors:
2 PASKER Vít 3 HLAVICA Robert 4 ŠPAČKOVÁ Hana 5 MENŠÍK Martin
Institutions:
1 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, ondrej.grycz@vsb.cz
2 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, vit.pasker@vsb.cz
3 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, robert.hlavica@vsb.cz
4 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, hana.spackova@vsb.cz
5 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, martin.mensik@vsb.cz
Conference:
28th International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 22nd - 24th 2019
Proceedings:
Proceedings 28th International Conference on Metallurgy and Materials
Pages:
1863-1867
ISBN:
978-80-87294-92-5
ISSN:
2694-9296
Published:
4th November 2019
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
59 views / 17 downloads
Abstract

The article deals with quality analysis of power grids especially in metallurgical industry when using large engines, arc furnace, induction heating and so on. Nowadays, these non-linear loads which are connected to power grids cause heavy disturbances, which can cause big problems like damage or even destruction of machines or devices connected near the point, where disturbances occur. Identification of disturbances is then very important for elimination of these problems. The article describe progress in detecting mentioned anomalies namely application of discrete Fourier transform which is suitable tool for measuring the anomalies. Discrete Fourier transform can be implemented in modern type microprocessors so there is a possibility to measure and evaluate measured results quickly and efficiently. Based on measured values the power grid in the factory can be analyzed and the improvement can be proposed.

Keywords: Metallurgy, power grid, microprocessor, discrete Fourier transform
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