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Data Acquisition Protocol for Determining Embedded Sensitivity Functions

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Published on: April 20, 2016

Engineering Safety-Oriented Blasting-Induced Seismic Wave Signal Processing: An EMD Endpoint Suppression Method Based

Miao Sun^1,2, Jing Wu^1,2, Yani Lu¹

¹School of Civil Engineering & Research Center of Hubei Small Town Development, Hubei Engineering University, Xiaogan 432000, China.

Sensors (Basel, Switzerland)

|July 12, 2025

Summary

This summary is machine-generated.

This study introduces a novel algorithm to suppress endpoint effects in empirical mode decomposition (EMD) for blasting seismic waves. The improved method enhances time-frequency analysis, leading to more accurate hazard assessments for structures near blasting sites.

Keywords:

blasting seismic wave empirical mode decomposition endpoint effect hazard control intrinsic mode function

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Area of Science:

Geophysics
Signal Processing
Seismology

Background:

Blasting-induced seismic waves are complex nonlinear and non-stationary signals.
Empirical Mode Decomposition (EMD) combined with Hilbert transform is used for time-frequency analysis of seismic waves.
EMD processing of seismic waves suffers from endpoint effects, causing divergence in intrinsic mode functions (IMFs) and inaccurate time-frequency results.

Purpose of the Study:

To propose an improved EMD endpoint effect suppression algorithm for blasting-induced seismic waves.
To enhance the accuracy of time-frequency analysis for seismic signals.
To improve the safety assessment of structures in areas affected by blasting.

Main Methods:

Developed an EMD endpoint effect suppression algorithm considering local endpoint trends, global time distribution, energy, and waveform matching.
Algorithm identifies and replaces endpoint signal fragments using matching criteria from segmented signal parts.
Validated the method using simulated signals, comparing it against mirror extension, polynomial fitting, and extreme value extension.

Main Results:

The proposed algorithm effectively suppresses EMD endpoint effects, reducing IMF divergence.
Comparative studies showed superior performance in reducing error standard deviation and improving correlation coefficients.
Applied to actual blasting seismic signals, the method improved time-frequency characteristic extraction.

Conclusions:

The improved EMD algorithm provides physically meaningful IMF components for seismic wave analysis.
Accurate time-frequency analysis of blasting seismic waves is crucial for structural safety assessments.
This method offers significant practical implications for evaluating risks in seismically active blasting zones.