A method and device for determining a critical collapse wind speed of a power transmission tower, an electronic device, and a storage medium

By constructing a graph structure of the transmission tower and processing its feature matrix, the problems of spatial topology representation and load allocation weights of the transmission tower were solved, enabling efficient and accurate assessment of the critical collapse wind speed of the transmission tower.

CN122761079APending Publication Date: 2026-09-15ELECTRIC POWER RES INST OF GUANGDONG POWER GRID CO LTD
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Patent Information

Application Number
CN202611188357.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-08-06
Publication Date
2026-09-15

AI Technical Summary

Technical Problem

Existing technologies are unable to accurately characterize the complex spatial topology of transmission towers and cannot precisely quantify the load distribution weight of local components in actual force transmission, resulting in difficulty in quickly screening key weak links and low accuracy and efficiency in assessing critical collapse wind speeds.

Method used

By acquiring 3D point cloud data of transmission towers, a graph structure is constructed, node feature matrices and edge feature matrices are generated, attention coefficients between graph nodes are calculated, and weighted aggregation and pooling are performed to generate graph-level feature vectors. Finally, regression prediction is performed to determine the critical collapse wind speed.

Benefits of technology

It achieves efficient and accurate determination of the critical collapse wind speed of in-service transmission towers, objectively restores the actual load distribution weight of components of different sizes in the wind-resistant force transmission path, and accurately extracts the key node features with the most unfavorable stress.

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Abstract

The application discloses a method and device for determining critical collapse wind speed of a power transmission tower, electronic equipment and a storage medium, and belongs to the technical field of power transmission tower structure safety evaluation. The method comprises the following steps: obtaining three-dimensional point cloud data of a power transmission tower to be measured; constructing a power transmission tower graph structure according to the three-dimensional point cloud data, generating a node feature matrix, an edge feature matrix and a connection relationship between graph nodes and graph edges; calculating attention coefficients between graph nodes based on the node feature matrix, the edge feature matrix and the connection relationship, and performing weighted aggregation on node features according to the attention coefficients to generate an updated feature matrix; performing pooling processing on the updated feature matrix to generate a graph-level feature vector; and performing regression prediction according to the graph-level feature vector to determine the critical collapse wind speed of the power transmission tower to be measured. Through implementation of the application, the problems that the prior art cannot quickly screen key weak links and has low evaluation accuracy and efficiency of critical collapse wind speed can be solved.
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