Magnetotelluric power line noise removal using temporally varying sinusoidal subtraction of the grid utility frequency

0574381 - GFÚ 2024 RIV DE eng J - Článek v odborném periodiku
Klanica, Radek - Pek, Josef - Hill, Graham J.
Magnetotelluric power line noise removal using temporally varying sinusoidal subtraction of the grid utility frequency.
Pure and Applied Geophysics. Roč. 180, č. 9 (2023), s. 3303-3317. ISSN 0033-4553. E-ISSN 1420-9136
Institucionální podpora: RVO:67985530
Klíčová slova: magnetotellurics * time series analysis * power grid noise abatement * utility frequency
Obor OECD: Physical geography
Impakt faktor: 2, rok: 2022
Způsob publikování: Open access
https://link.springer.com/article/10.1007/s00024-023-03323-w

The magnetotelluric method relies on variations of natural electromagnetic fields, which in the vicinity of human settlements are persistently distorted by anthropogenic electromagnetic noise. A large source of noise to the magnetotelluric response is caused by the harmonic oscillations of the power network utility frequency centered on 50/60 Hz along with the associated higher harmonics. Removing this type of noise is essential for high frequency magnetotelluric measurements used for shallow surveys. There are a large number of approaches for how to treat power line noise in magnetotelluric signals, however, commonly used methods do not take into account time variations/instabilities of the utility frequency. That is not serious problem in vicinity of well balanced grid networks, but can cause issues in regions with larger utility frequency variations. Under such conditions, commonly used methods loose more of the natural signal, which is undesirable especially in case of very noisy datasets. Hence, we adopted approach for removing of power line noise with respect to time variations of the utility frequency and applied it to magnetotelluric signals to preserve more of natural signal. The method is based on modelling of the grid network harmonic oscillations by the optimum utility frequency and its integer multiples. The resulting sum of sinusoidal signals is subsequently subtracted from recorded data and only particular noise frequencies are removed from the original signal with high precision, while frequency ranges around power line harmonics are cleaned.
Trvalý link: https://hdl.handle.net/11104/0344714