Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

Milan Oravec, Pavol Lipovský, Miroslav Šmelko, Pavel Adamčík, Mirosław Witoś and Jerzy Kwaśniewski
Additional contact information
Milan Oravec: Faculty of Mechanical Engineering, Technical University of Košice, Letná 9, 042 00 Košice, Slovakia
Pavol Lipovský: Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia
Miroslav Šmelko: Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia
Pavel Adamčík: Technical Diagnostics, Ltd., Jilemnického 3, 080 01 Prešov, Slovakia
Mirosław Witoś: Air Force Institute of Technology, Ul. Księcia Bolesława 6, 01-494 Warsaw, Poland
Jerzy Kwaśniewski: Faculty of Mechanical Engineering and Robotics, The AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland

Sustainability, 2021, vol. 13, issue 16, 1-23

Abstract: The magnetic field created by technical devices is a source of information. This information could be used in contactless diagnostics and predictive maintenance or for resolving problems along with standard NDT (nondestructive testing) methods, especially if we consider large, slow-speed devices, such as electromotors, transmissions, or generators. Identification of causalities of device failure processes with near magnetic field is one of the suitable NDT methods improving sustainability of systems. The measurements presented in the article were performed with the VEMA 04 fluxgate vector magnetometer with the DC-250 Hz bandwidth and 2 nT sensitivity. Postprocessing of the results was performed in the means of standard methods of discrete Fourier Transform, spectrogram creation and Wavelet Transform. The article presents data gathered during the measurement of a pair of extraction fans with power of 140 kW each and maximum revolutions up to 740 rev/min controlled by frequency converters and a single semi-Kaplan water power plant with 400 kW peak power at 1005 rev/min maximum generator speed. The measurements were performed before and after repairs of one of the ventilators in the ventilation system at 60% and 100% of maximal output power. The rotating magnetic fields of the fan electromotor stator, fan rotor revolutions, rotor slip frequency and ball-bearing frequencies were identified in frequency spectrums in the distance of 700 mm from fan electromotor axis in both cases. During the measurements on the semi-Kaplan turbine, the changes in states of mechanical and electrical components of the machine were monitored in the magnetic fields with increase of the power in the range of 0–95%, before and after phasing to the electrical grid. Standard processing methods, Discrete Fourier Transform, spectrograms and Discrete Wavelet Transform were used. In the spectrograms of the measured magnetic fields, the 1st–4th harmonics of the turbine shaft, generator shaft and also their side frequencies were identified. Significant changes of magnetic fields in time were identified in the area of 60–95% power. With the help of the Wavelet, transform intervals were identified where it is desirable to operate the turbine. The analyses of magnetic fields measurements performed on the power plant were compared with vibro-diagnostic principles.

Keywords: magnetism; vector magnetometer; measurements; signal analysis; FFT; spectrogram; DWT; nondestructive testing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/16/9197/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/16/9197/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:16:p:9197-:d:615512

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().