Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Studies on the Experimental Measurement of the Low-Frequency Aerodynamic Noise of Large Wind Turbines

Wenjie Wang, Yan Yan, Yongnian Zhao and Yu Xue
Energies 17 (7) 1609 (2024)
https://doi.org/10.3390/en17071609

Application of wavelet synchrosqueezed transforms to the analysis of infrasound signals generated by wind turbines

Tomasz Boczar, Dariusz Zmarzły, Michał Kozioł and Daria Wotzka
The Journal of the Acoustical Society of America 152 (5) 2863 (2022)
https://doi.org/10.1121/10.0015141

Measurement of Infrasound Components Contained in the Noise Emitted during a Working Wind Turbine

Tomasz Boczar, Dariusz Zmarzły, Michał Kozioł, Łukasz Nagi, Daria Wotzka and Zbigniew Nadolny
Energies 15 (2) 597 (2022)
https://doi.org/10.3390/en15020597

Measurement and Analysis of Infrasound Signals Generated by Operation of High-Power Wind Turbines

Tomasz Malec, Tomasz Boczar, Daria Wotzka and Michał Kozioł
Energies 14 (20) 6544 (2021)
https://doi.org/10.3390/en14206544

The application of time-frequency ridge transformation for the analysis of infrasound signals generated by wind turbines

Tomasz Boczar, Dariusz Zmarzły, Michał Kozioł and Daria Wotzka
Applied Acoustics 177 107961 (2021)
https://doi.org/10.1016/j.apacoust.2021.107961

Application of Correlation Analysis for Assessment of Infrasound Signals Emission by Wind Turbines

Tomasz Boczar, Dariusz Zmarzły, Michał Kozioł and Daria Wotzka
Sensors 20 (23) 6891 (2020)
https://doi.org/10.3390/s20236891

Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods

Daniel Jancarczyk, Marcin Bernaś and Tomasz Boczar
Sensors 19 (22) 4909 (2019)
https://doi.org/10.3390/s19224909