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Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method

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  • Beata Palczynska

    (Department of Marine Telecommunications, Gdynia Maritime University, Morska 81-87, 81-225 Gdynia, Poland)

Abstract

The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs) is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP) algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.

Suggested Citation

  • Beata Palczynska, 2017. "Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method," Energies, MDPI, vol. 10(5), pages 1-13, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:655-:d:97993
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    References listed on IDEAS

    as
    1. Qing Yang & Jing Wang & Wenxia Sima & Lin Chen & Tao Yuan, 2011. "Mixed Over-Voltage Decomposition Using Atomic Decompositions Based on a Damped Sinusoids Atom Dictionary," Energies, MDPI, vol. 4(9), pages 1-18, September.
    2. Yan Zhao & Zhimin Li & Yonghui Nie, 2016. "A Time-Frequency Analysis Method for Low Frequency Oscillation Signals Using Resonance-Based Sparse Signal Decomposition and a Frequency Slice Wavelet Transform," Energies, MDPI, vol. 9(3), pages 1-18, March.
    3. Nabeel A. Khan & Faisal Baig & Syed Junaid Nawaz & Naveed Ur Rehman & Shree K. Sharma, 2016. "Analysis of Power Quality Signals Using an Adaptive Time-Frequency Distribution," Energies, MDPI, vol. 9(11), pages 1-13, November.
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