苏三庆, 秦彦龙, 王威, 左付亮, 邓瑞泽, 刘馨为. 基于磁记忆检测的桥钢箱梁翼缘损伤状态力磁关系[J]. 工程科学学报, 2022, 44(5): 900-910. DOI: 10.13374/j.issn2095-9389.2020.11.10.00214
引用本文: 苏三庆, 秦彦龙, 王威, 左付亮, 邓瑞泽, 刘馨为. 基于磁记忆检测的桥钢箱梁翼缘损伤状态力磁关系[J]. 工程科学学报, 2022, 44(5): 900-910. DOI: 10.13374/j.issn2095-9389.2020.11.10.00214
SU San-qing, QIN Yan-long, WANG Wei, ZUO Fu-liang, DENG Rui-ze, LIU Xin-wei. Stress‒magnetization of the state of flange damage to a bridge steel box beam based on magnetic memory detection[J]. Chinese Journal of Engineering, 2022, 44(5): 900-910. DOI: 10.13374/j.issn2095-9389.2020.11.10.00214
Citation: SU San-qing, QIN Yan-long, WANG Wei, ZUO Fu-liang, DENG Rui-ze, LIU Xin-wei. Stress‒magnetization of the state of flange damage to a bridge steel box beam based on magnetic memory detection[J]. Chinese Journal of Engineering, 2022, 44(5): 900-910. DOI: 10.13374/j.issn2095-9389.2020.11.10.00214

基于磁记忆检测的桥钢箱梁翼缘损伤状态力磁关系

Stress‒magnetization of the state of flange damage to a bridge steel box beam based on magnetic memory detection

  • 摘要: 金属磁记忆检测技术由于其能够快速便捷的对铁磁性构件的损伤进行识别,且被认为具有识别隐性损伤的能力,而被广泛研究。为推进金属磁记忆检测技术在桥钢箱梁损伤检测方面的应用,对桥钢箱梁进行了静力受弯试验,提取其变形最严重的上翼缘磁信号分布,建立了损伤区域力与磁信号和磁信号梯度的关系曲线,并提出用磁场梯度指数来表征钢梁的受力和损伤状态。结果表明:上翼缘磁信号曲线与应力变化形态正好相反,磁信号曲线在进入塑性后发生反转变为负值,且随应力变化的速度增快,可以判断构件进入塑性状态,即将发生损伤;磁场梯度曲线在损伤最严重的区域出现最大值,且随着荷载的增大,磁梯度最大值点不断向钢梁中间移动,由此可以进行破坏状态的预警;磁场梯度与应力关系曲线可将构件整个受力过程明显的区分为初始、屈服、塑性、损伤4个状态;可以用磁场梯度指数来进行构件受力状态与损伤状态的表征。该研究可为金属磁记忆检测技术在桥钢箱梁损伤状态的定量评估和预警方面的应用提供依据和参考。

     

    Abstract: Metal magnetic memory detection technology has been widely studied because it can identify damage to ferromagnetic components quickly and conveniently, and it is considered to have the ability to identify hidden damage. To promote the application of metal magnetic memory technology in the damage detection of a bridge steel box beam, a static bending test on the steel box beam of the bridge was performed, and the magnetic signal distribution of the upper flange with the most severe deformation was extracted. The quantitative relationship between the stress in the damaged region and magnetic signal or magnetic signal gradient was established, and an approach for characterizing the stress and damage state of the steel beam was proposed using the magnetic field gradient index. The results show that the magnetic signal curve of the upper flange is opposite to that of the stress change form, and the magnetic signal curve reverses to a negative value after entering the plastic state and increases with the stress change speed, so the component can be judged to enter the plastic state and soon be damaged. The maximum value of the magnetic field gradient curve appears in the position with the most severe damage, and with the increase in the load, the maximum value point of the magnetic gradient constantly moves to the middle of the steel beam; thus the early warning of the failure state can be conducted. The relationship curve between the magnetic field gradient and stress can obviously distinguish the entire stress process of the component, which includes four states: initial, yield, plasticity, and damage. The stress state and damage state of components can be characterized using the magnetic field gradient index. This study can provide a reference and basis for the application of metal magnetic memory detection technology in the quantitative assessment and early warning of the damage status of bridge steel box beams.

     

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