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Seismic Signal Analysis Based on Variational Mode Decomposition and Hilbert Transform for Ground Intrusion Activity
Yuan Sun1, Dongdong Qian1, Jing Zheng1,2
1College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Haidian, Beijing 100083, China.
Sensors (Basel, Switzerland)
|April 13, 2023
Summary
This study introduces a new method using Variational Mode Decomposition (VMD) and Hilbert Transform (HT) for classifying ground intrusion seismic signals. The VMD-HT technique achieved high accuracy in identifying activities like footsteps and vehicle movements.
Area of Science:
- Geophysics
- Signal Processing
- Machine Learning
Background:
- Ground intrusion identification is crucial for national security.
- Seismic sensing systems generate complex signals requiring advanced analysis.
- Existing methods may not fully capture the nuances of seismic data from various intrusion types.
Purpose of the Study:
- To propose a novel Variational Mode Decomposition (VMD) and Hilbert Transform (HT) method for classifying seismic signals from ground intrusion activities.
- To evaluate the effectiveness of the VMD-HT technique against other signal processing methods.
- To enhance the accuracy and reliability of ground intrusion detection systems.
Main Methods:
- Collected seismic data for various activities (bicycles, vehicles, footsteps, excavations, noise).
- Decomposed signals using VMD into five Band-limited Intrinsic Mode Functions (BIMF).
- Applied HT to BIMFs to generate marginal spectra, extracting features like energy, entropy, and dominant frequency for Support Vector Machine (SVM) classification.
Main Results:
- The VMD-HT method achieved high classification performance with average accuracy of 99.50%, precision of 98.76%, recall of 98.76%, and F1-Score of 98.75%.
- These results surpassed those obtained using time-domain, frequency-domain, Ensemble Empirical Mode Decomposition (EEMD), and Empirical Wavelet Transform (EWT) methods combined with HT.
- The proposed method accurately distinguished between different types of ground intrusion and environmental noise.
Conclusions:
- The VMD-HT technique is a highly effective and accurate method for classifying seismic signals generated by ground intrusion activities.
- This approach offers significant improvements over existing methods, providing a robust tool for public security applications.
- The study validates the VMD-HT method's potential for real-world deployment in seismic-based intrusion detection systems.
Keywords:
Hilbert transformfeature extractionground intrusion activitymarginal spectrumseismic signal analysissupport vector machinevariational mode decompositionMore Related Videos
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