A fatigue crack detection system for steel structures based on digital twins

By using a digital twin-based steel structure fatigue crack detection system, multi-source data is collected and analyzed in real time to construct a digital twin model, solving the problems of low detection frequency and data isolation in existing technologies, and achieving efficient and accurate crack monitoring and risk management.

CN121437500BActive Publication Date: 2026-04-21TONGJI UNIV
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Patent Information

Application Number
CN202511983372.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-12-26
Publication Date
2026-04-21
Estimated Expiration
2045-12-26

AI Technical Summary

Technical Problem

Existing technologies for detecting fatigue cracks in steel structures suffer from low detection frequency, insufficient efficiency, and strong subjectivity. They are difficult to monitor at multiple points and lack a unified processing and fusion mechanism for multi-source heterogeneous data, which makes it easy to miss early cracks and difficult to form a complete long-term condition record.

Method used

A steel structure fatigue crack detection system based on digital twins is adopted, including a sensing module, a digital twin backend data fusion and management module, an analysis module, and a visualization module. By collecting data in real time, a digital twin model is constructed to identify, locate, and warn of cracks, and to achieve unified processing and management of multi-source data.

Benefits of technology

It enables large-scale, continuous, and effective monitoring of fatigue cracks, ensuring precise synchronization between the virtual model and the on-site structural condition. It supports multi-dimensional comprehensive assessment, improves the accuracy of crack development prediction and the initiative of risk management, and solves the problem of data isolation from multiple devices.

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Abstract

This invention relates to a fatigue crack detection system for steel structures based on digital twins, comprising: a sensing module for real-time acquisition of fatigue crack monitoring data of the steel structure; a digital twin backend data fusion and management module for parsing and standardizing the fatigue crack monitoring data, constructing a digital twin model of the steel structure to map the physical state of the steel structure and the spatial distribution of fatigue cracks; an analysis module for detecting fatigue cracks in the steel structure based on the fatigue crack monitoring data, updating the detection results to the digital twin model for state synchronization, and providing crack risk warnings; and a visualization module for displaying the fatigue crack monitoring data and the detection and warning results output by the analysis module. Compared with existing technologies, this invention, through the coordinated operation of sensing, fusion, analysis, and visualization, achieves real-time detection, trend prediction, and multi-level early warning of fatigue cracks in steel structures, significantly improving the safety and scientific decision-making during the operation and maintenance phase.
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