Land subsidence prediction method and system based on multi-source data fusion

CN121859423BActive Publication Date: 2026-05-29HEBEI GEO UNIVERSITY +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HEBEI GEO UNIVERSITY
Filing Date
2026-03-18
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies cannot accurately predict ground settlement in tunnel engineering scenarios where two lines pass under each other in parallel. In particular, they fail to effectively identify overlapping areas of construction impact and consider settlement deviations at different time points, resulting in low prediction accuracy.

Method used

By dividing the tunnel underpass area into left and right underpass sections, the disturbance intensity coefficient was calculated, the scope of construction impact was defined, and the cross-impact sections were screened. In addition, settlement prediction was carried out by combining finite element settlement model and settlement prediction model and using multi-source data fusion.

Benefits of technology

It enables precise capture of settlement patterns in the cross-area of ​​two lines, improves prediction accuracy, avoids the blindness of existing technologies, and solves the prediction limitations in the scenario of parallel tunnel crossing.

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Abstract

The application provides a ground subsidence prediction method and system based on multi-source data fusion, and relates to the technical field of ground subsidence, and the specific steps comprise: dividing a lower passing section, determining a subsidence time interval; collecting construction parameters and calculating a disturbance intensity coefficient, and screening out a double-line intersection influence section; obtaining daily cumulative subsidence simulation values, comparing with measured values to obtain a cumulative time sequence deviation sequence; screening time nodes with cumulative subsidence deviation values less than a preset threshold value, constructing a time sequence feature matrix, setting parameters of time nodes not less than the preset threshold value to zero and supplementing to the time sequence feature matrix to obtain next-day intersection influence section cumulative subsidence prediction values. The application not only fully considers double-line intersection disturbance effects, but also distinguishes subsidence differences of the intersection influence section and the single-line lower passing section, avoids blindness of global fitting of the prior art, realizes accurate capture of the subsidence law of the intersection influence section, and greatly improves subsidence prediction accuracy of the region.
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