斜拉索PE护套微裂纹检出方法及系统

By combining wideband composite excitation and circumferential flexible sensing array with multi-layer judgment logic, microcracks in the PE sheath of cable-stayed bridges are identified and a growth-environment coupling model is constructed. This solves the problems of high missed detection rate and high false judgment rate in existing technologies, and realizes efficient and accurate diagnosis and dynamic risk assessment of microcracks in the PE sheath of cable-stayed bridges.

CN121805421BActive Publication Date: 2026-07-17ZHEJIANG GANGXIN DETECTION TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG GANGXIN DETECTION TECH
Filing Date
2026-03-10
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies suffer from high rates of missed detection and false positives when detecting microcracks in the PE sheath of cable stays, and are unable to dynamically assess risks. Traditional methods cannot achieve efficient and accurate early identification and dynamic risk assessment.

Method used

A broadband composite excitation signal was used to excite the multi-physics response of the PE sheath of the cable-stayed bridge. Characteristic parameters were collected by a circumferential flexible sensor array. By combining the spatial gradient mutation algorithm and multi-layer judgment logic, microcracks were identified and confirmed. A crack growth-environment coupling model was constructed for dynamic risk assessment.

Benefits of technology

It enables efficient and accurate diagnosis of microcracks in the PE sheath of cable stays, significantly reducing the rate of missed detections and false alarms. It can dynamically assess the risk evolution trend of cracks and provide a reliable technical support for preventive maintenance of bridges.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明涉及桥梁工程结构健康监测技术领域,具体公开了一种斜拉索PE护套微裂纹检出方法及系统。通过施加宽频复合激励激发护套的多物理场响应,利用环向柔性传感阵列采集应变、声发射和热弛豫信号,基于空间梯度突变检测初筛异常点;结合非线性谐波识别与相邻传感器相位差分析,逐层排除干扰,筛选出高置信裂纹候选;经多次非连续时段复测验证时空一致性,确认实体微裂纹;最后构建裂纹生长‑环境耦合模型,根据动态风险指数实现分级预警。实现了对微裂纹的高灵敏度、高效率自动检出与科学量化评估。
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