A method for monitoring displacement of multiple electric towers near a foundation pit based on a Beidou system

CN122149375APending Publication Date: 2026-06-05CHINA RAILWAY FIRST GRP FIRST CONSTR CO LTD +3

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Applications(China)
Current Assignee / Owner: CHINA RAILWAY FIRST GRP FIRST CONSTR CO LTD
Filing Date: 2026-01-12
Publication Date: 2026-06-05

AI Technical Summary

Technical Problem

In existing technologies, the tower displacement monitoring method based on the Beidou system suffers from problems such as inconsistent timestamps from different data sources, inconsistent coordinate systems, and difficulty in coordinating the suppression of data noise. These issues lead to the accumulation of spatial positioning errors at multiple monitoring points, insufficient data consistency, and limited overall monitoring accuracy.

Method used

By constructing a unified dataset, integrating BeiDou positioning data, displacement sensing data, and environmental parameters using a time synchronization mechanism, and establishing a joint mechanical model of the power tower and soil using the finite element method, the monitoring frequency and resources are optimized using genetic algorithms, particle swarm optimization, and simulated annealing algorithms. Deep learning and reinforcement learning are combined for prediction and parameter adjustment, and data link anomalies are identified and adjusted accordingly.

Benefits of technology

This system enhances data consistency, ensures accurate positioning and real-time data alignment during power tower displacement monitoring, and guarantees high reliability, low energy consumption and high efficiency operation of the monitoring system in complex construction environments, providing a highly reliable basis for safety assessment.

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Abstract

The present application relates to the technical field of safety monitoring, and discloses a near-foundation multi-pylon displacement monitoring method based on a Beidou system, comprising the following steps: S1, obtaining the spatial coordinates of a plurality of pylons and foundation periphery sensors through a Beidou positioning unit; S2, constructing a combined mechanical model of the pylons and the soil around the foundation; S3, numerically solving the combined mechanical model of the pylons and the soil; S4, optimizing and adjusting the monitoring frequency, monitoring accuracy and computing resources based on a genetic algorithm, a particle swarm algorithm and a simulated annealing algorithm; S5, using a deep learning model to predict the change trend of the pylon displacement; and S6, identifying abnormal conditions in the data link through diagnostic rules. The unified data set composed of Beidou positioning data, displacement sensing data and environmental parameters achieves the effect of consistent data enhancement in the pylon displacement monitoring process through the spatial accurate positioning and real-time data alignment of the multi-monitoring points of the pylons and the foundation area.

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