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基于分布式光纤传感的节段式干接头全尺寸预应力盖梁损伤分析。

Damage Analysis of Segmental Dry Joint Full-Scale Prestressed Cap Beam Based on Distributed Optical Fiber Sensing.

机构信息

The State Key Laboratory on Safety and Health of In-Service Long-Span Bridges, JSTI Group, Nanjing 210019, China.

College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China.

出版信息

Sensors (Basel). 2023 Apr 6;23(7):3781. doi: 10.3390/s23073781.

Abstract

Distributed fiber optic sensors (DFOS) can detect structural cracks and structural deformation with high accuracy and wide measurement range. This study monitors the segmental prestressed bent cap, assembled with a large key dry joint, based on optical fiber technology, and it allows the comparison of its damaging process with that of a monolithic cast in place counterpart. The obtained results, comprising cross-section strain distributions, longitudinal strain profiles, neutral axis location, crack pattern, and the damage process, show that the DFOS technology can be successfully used to analyze the complex working stress state of the segmental beam with shear key joints, both in the elastic range and at the ultimate load, and to successfully identify the changing characteristics of the stress state of the segmental capping beam model when elastic beam theory no longer applies. The DFOS data confirm that the shear key joint, as the weak point of the segmental cap beam, results in the high stress concentration area, and the damage rate is higher than that of the cast-in-place beam. The accurate monitoring by the DFOS allows for the realization that the damage occurs at the premature formation of a concentrated compression zone on the upper part of the shear key.

摘要

分布式光纤传感器 (DFOS) 可以高精度、宽测量范围地检测结构裂缝和结构变形。本研究基于光纤技术对装配有大型键干接头的节段预应力弯帽进行监测,并将其损伤过程与整体现浇的对应物进行比较。所获得的结果包括截面应变分布、纵向应变分布、中性轴位置、裂缝模式和损伤过程,表明 DFOS 技术可成功用于分析带有剪力键接头的节段梁的复杂工作受力状态,无论是在弹性范围还是在极限荷载下,并成功识别出当弹性梁理论不再适用时,节段盖梁模型的应力状态变化特征。DFOS 数据证实,剪力键接头作为节段盖梁的薄弱点,导致高应力集中区,且损伤率高于现浇梁。DFOS 的精确监测可以实现这样的认识,即在剪力键上部的集中压缩区过早形成时就发生了损伤。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aba3/10098848/276794137c77/sensors-23-03781-g001.jpg

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