Login / Signup

Feature Extraction of a Non-Stationary Seismic-Acoustic Signal Using a High-Resolution Dyadic Spectrogram.

Diego Seuret-JiménezEduardo Trutié-CarreroJose Manuel Nieto-JalilErick Daniel García-AquinoLorena Díaz-GonzálezLaura Carballo-SiglerDaily Quintana-FuentesLuis Manuel Gaggero-Sager
Published in: Sensors (Basel, Switzerland) (2023)
Using a novel mathematical tool called the Te-gram, researchers analyzed the energy distribution of frequency components in the scale-frequency plane. Through this analysis, a frequency band of approximately 12 Hz is identified, which can be isolated without distorting its constituent frequencies. This band, along with others, remained inseparable through conventional time-frequency analysis methods. The Te-gram successfully addresses this knowledge gap, providing multi-sensitivity in the frequency domain and effectively attenuating cross-term energy. The Daubechies 45 wavelet function was employed due to its exceptional 150 dB attenuation in the rejection band. The validation process encompassed three stages: pre-, during-, and post-seismic activity. The utilized signal corresponds to the 19 September 2017 earthquake, occurring between the states of Morelos and Puebla, Mexico. The results showcased the impressive ability of the Te-gram to surpass expectations in terms of sensitivity and energy distribution within the frequency domain. The Te-gram outperformed the procedures documented in the existing literature. On the other hand, the results show a frequency band between 0.7 Hz and 1.75 Hz, which is named the planet Earth noise.
Keyphrases
  • gram negative
  • high resolution
  • systematic review
  • machine learning
  • deep learning
  • air pollution
  • mass spectrometry
  • liquid chromatography