| 基于车致桥梁响应和L1正则化的损伤识别研究 |
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| 引用本文： | 贺文宇,武骥元,任伟新.基于车致桥梁响应和L1正则化的损伤识别研究[J].中国公路学报,2021,34(4):61-70. |
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| 作者姓名： | 贺文宇 武骥元 任伟新 |
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| 作者单位： | 1. 合肥工业大学土木与水利工程学院, 安徽合肥 230009;2. 安徽省基础设施安全检测与监测工程实验室, 安徽合肥 230009;3. 深圳大学土木与交通工程学院, 广东深圳 518061 |
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| 基金项目： | 国家自然科学基金项目（51878234，51778204）；中央高校基本科研业务费专项资金项目（JZ2019HGPA0101） |
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| 摘 要： | 桥梁损伤识别是典型的反问题，通常需采用正则化手段求解。基于L1正则化的损伤识别方法能很好地利用损伤所具有的稀疏性，在桥梁监测领域得到了广泛的应用。此类方法通常利用频率和振型的变化作为判断损伤的依据，然而实际测试中可获得的频率阶数有限、振型测试精度低，严重影响其效果。采用移动荷载激励下的桥梁动力响应，提出一种基于有限元模型修正技术和L1正则化的损伤识别方法。首先，采用数值算例系统比较局部损伤导致的桥梁频率变化与车致桥梁动力位移-时间曲线面积变化情况，结果表明相比于频率变化，车致桥梁动力位移-时间曲线面积的变化更适合用于损伤识别。其次，提出基于有限元模型修正技术和L1正则化的桥梁损伤识别方法。将桥梁有限元模型中的单元刚度折减因子作为待修正参数，以模型计算和实测车致桥梁动力位移-时间曲线面积的差值最小为目标函数，并引入L1正则化优化求解，识别桥梁损伤。然后，采用包含单损伤和双损伤工况的简支梁和连续梁数值算例，验证所提方法的有效性，并分析测试噪音、移动荷载速度不均匀和桥梁刚度分布不均匀对识别结果的影响。最后，制作移动车辆和简支梁桥的试验模型，进行移动荷载试验。研究结果表明：提出的损伤识别方法能够较准确地识别桥梁单损伤的位置和程度，但随着损伤数目的增多，其有效性有所下降。
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| 关 键 词： | 桥梁工程 损伤识别 L1正则化 移动荷载 模型修正 |
| 收稿时间： | 2020-08-27 |
Bridge Damage Detection Based on the Moving-vehicle-induced Response and L1 Regularization |
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| HE Wen-yu,WU Ji-yuan,REN Wei-xin.Bridge Damage Detection Based on the Moving-vehicle-induced Response and L1 Regularization[J].China Journal of Highway and Transport,2021,34(4):61-70. |
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| Authors: | HE Wen-yu WU Ji-yuan REN Wei-xin |
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| Affiliation: | 1. College of Civil Engineering, Hefei University of Technology, Hefei 230009, Anhui, China;2. Anhui Engineering Laboratory for Infrastructural Safety Inspection and Monitoring, Hefei 230009, Anhui, China;3. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, Guangdong, China |
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| Abstract: | Structural damage detection is a typically ill-posed problem in which regularization methods are required. L1 regularization has been widely used in bridge health monitoring as it makes good use of the sparsity of structural damage. Such methods usually adopt changes in the frequencies and mode shapes for damage detection. However, the limitation on the frequency order number and the low precision of the mode shape significantly affect their effectiveness. In this paper, a structural damage detection method based on finite element model (FEM) updating and L1 regularization was proposed using the bridge response induced by a moving vehicle. First, numerical examples were conducted to compare the frequency and area changes of the moving-vehicle-induced displacement-time curve caused by local damage. The results indicate that the area change of the moving-vehicle-induced displacement-time curve is more suitable for damage detection. Second, a damage detection method based on FEM updating and L1 regularization was presented. The elemental stiffness reduction factors were taken as the parameters to be updated, and the objective function was formulated by the difference between the area of the moving-vehicle-induced displacement-time curve calculated by the FEM and measured in the field test. L1 regularization optimization was employed to solve the objective function and identify damages. Then, numerical examples of simply supported beams and continuous beams with various damage scenarios were used to verify the proposed method's effectiveness. In addition, the effects of the measurement noise, varying moving velocity, and uneven distribution of flexural rigidity on the damage detection results were investigated. Finally, the experimental model of a moving vehicle and a simply supported beam was set up in the laboratory for the moving load test. The results indicate that the proposed method can effectively identify the location and severity of a single damage occurrence. However, its effectiveness decreases with an increase in the damage number. |
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| Keywords: | bridge engineering damage detection L1 regularization moving load model updating |
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