Automatic extraction method and system for surface wave frequency dispersion curve, and storage medium

By performing data point area segmentation and mean point construction on the surface wave dispersion energy map, the problem of large error in surface wave dispersion curve extraction in complex geological environments is solved, and high-precision and automated dispersion curve extraction is achieved.

CN120009984APending Publication Date: 2025-05-16ANHUI URBAN CONSTR DESIGN & RES INST
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Patent Information

Application Number
CN202510082339.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-01-20
Publication Date
2025-05-16

AI Technical Summary

Technical Problem

The prior art has large errors in extracting surface wave dispersion curves in complex geological environments, and lacks applicable automatic extraction methods.

Method used

By converting the surface wave dispersion energy graph into a collection of data points, region segmentation is performed, the mean point of each region is calculated, and the dispersion curve is constructed based on the mean point of all regions, and the influence of frequency, velocity and energy is comprehensively considered.

Benefits of technology

Improves the accuracy and automation capabilities of dispersion curve extraction, suitable for any geology and modality, and reduces the impact of human operation errors and noise.

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Abstract

The invention relates to the technical field of seismic detection, in particular to a surface wave frequency dispersion curve automatic extraction method and system and a storage medium. According to the surface wave frequency dispersion curve automatic extraction method provided by the invention, data point partitioning is performed on a surface wave frequency dispersion energy diagram based on data point extraction and clustering, then a central point in each region is extracted as a pick-up point through a mean value taking mode, and a frequency dispersion curve is constructed based on the pick-up point. The method breaks the current cognition of screening the frequency scatter points based on the principle of maximum energy, comprehensively considers the speed, energy and frequency to cluster the frequency scatter points, achieves the recognition of an energy concentration region mode, then extracts the frequency scatter points based on the clustering result, can accurately capture local features, avoids manual operation errors, and greatly improves the extraction precision of the frequency scatter points. The consistency and stability of extraction rules of frequency dispersion points in different areas are guaranteed, the height generality of a frequency dispersion curve to a surface wave frequency dispersion energy diagram is guaranteed, and high-precision and high-efficiency extraction of the frequency dispersion curve is guaranteed.
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