Wavelet base function selection method and device for identifying seismic motion velocity pulse

CN120652534BActive Publication Date: 2026-07-24CHINA RAILWAY ECONOMIC & PLANNING RES INST +3
View PDF 2 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA RAILWAY ECONOMIC & PLANNING RES INST
Filing Date
2025-05-14
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In existing technologies, the selection of wavelet basis functions has a significant impact on the identification of ground motion velocity pulses, but there is a lack of systematic research, resulting in poor identification results and difficulty in accurately identifying velocity pulses.

Method used

By acquiring ground motion record data, performing integral calculations and determining energy concentration intervals, iterative analysis using different wavelet basis functions is conducted to calculate correlation coefficients and select the optimal wavelet basis function to improve identification accuracy.

Benefits of technology

By optimizing the selection of wavelet basis functions, the accuracy and stability of velocity pulse identification were improved, ensuring that the extracted pulse features better match the physical characteristics of actual ground motion.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN120652534B_ABST
    Figure CN120652534B_ABST
Patent Text Reader

Abstract

The application discloses a wavelet base function selection method and device for identifying seismic velocity pulse, and the method comprises the following steps: performing integral calculation on seismic record data, and calculating an energy concentrated interval of an original velocity time history; iteratively analyzing the original velocity time history by using different wavelet base functions in sequence, and obtaining time history distribution data and the energy concentrated interval corresponding to each wavelet base function; performing down-sampling on the energy concentrated interval corresponding to each wavelet base function, and obtaining the down-sampled interval of each wavelet base function; calculating a first correlation coefficient of the down-sampled interval of each wavelet base function and the energy concentrated interval of the original velocity time history; calculating a second correlation coefficient of the velocity pulse time history identified by each wavelet base function and the original velocity time history; and selecting the wavelet base function by using the size order of the first correlation coefficient and the second correlation coefficient. The application can improve the fidelity of velocity pulse identification.
Need to check novelty before this filing date? Find Prior Art