| 桥梁结构非线性模型修正研究综述 |
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| 引用本文： | 王佐才,丁雅杰,戈壁,袁子青,辛宇.桥梁结构非线性模型修正研究综述[J].交通运输工程学报,2022,22(2):59-75. |
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| 作者姓名： | 王佐才 丁雅杰 戈壁 袁子青 辛宇 |
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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 2300092.合肥工业大学 土木工程防灾减灾安徽省 工程技术研究中心，安徽 合肥 2300093.合肥工业大学 安徽省基础设施安全检测与 监测工程实验室，安徽 合肥 230009 |
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| 基金项目： | 国家自然科学基金项目51922036安徽省重点研发计划1804a0802204中央高校基本科研业务费专项资金项目JZ2020HGPB0117 |
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| 摘 要： | 针对桥梁服役期间由于结构力学性能减弱从而表现出具有时变特征的非线性振动问题，在回顾非线性模型修正发展的基础上，分别从非线性系统识别、非线性模型修正方法和非线性模型不确定性量化3个方面入手，总结了结构非线性模型修正技术中存在的一些关键问题；结合复杂结构损伤识别、性能评估与安全监测等内容，对其在桥梁结构中的应用展开了讨论。研究结果表明:以固有频率和模态振型为代表的响应特征量仅能反映时不变结构的物理特性，对于非线性结构而言其力学性能随外激励作用而不断变化，基于线性系统特征量的模型修正方法不能很好地适用于具有明显时变特性的非线性结构；结构动力响应主分量的瞬时频率和瞬时幅值包含了振动响应信号的相位信息和幅值信息，可以较为全面地反映动力荷载作用下结构响应的非平稳特性，选择具有时变特性的瞬时特征量来构建目标函数能够更为合理地表征非线性结构的动力特性；不确定性模型修正方法通过综合利用实测响应数据，考虑了测量噪声、模型误差和数值计算方法等不确定因素的影响，提高了模型修正结果的准确性；复杂结构非线性模型修正过程中涉及的参数众多，计算量大，极大地限制了其在实际工程结构中的应用，因此，合理选择具有代表性的非线性模型参数以及提高模型修正的计算效率是当前亟需解决的问题。
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| 关 键 词： | 桥梁工程 非线性模型修正 非线性模式识别 不确定性量化 贝叶斯理论 优化算法 |
| 收稿时间： | 2021-10-22 |
Review on nonlinear model updating for bridge structures |
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| WANG Zuo-cai,DING Ya-jie,GE Bi,YUAN Zi-qing,XIN Yu.Review on nonlinear model updating for bridge structures[J].Journal of Traffic and Transportation Engineering,2022,22(2):59-75. |
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| Authors: | WANG Zuo-cai DING Ya-jie GE Bi YUAN Zi-qing XIN Yu |
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| Affiliation: | 1.College of Civil Engineering, Hefei University of Technology, Hefei 230009, Anhui, China2.Engineering Technology Research Center of Disaster Prevention and Mitigation of Civil Engineering of Anhui Province, Hefei University of Technology, Hefei 230009, Anhui, China3.Anhui Province Infrastructure Safety Inspection and Monitoring Engineering Laboratory, Hefei University of Technology, Hefei 230009, Anhui, China |
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| Abstract: | Due to the weakening of the structural mechanical properties during the service period of bridges, the nonlinear vibration with time-varying characteristics occurs. Considering this, the development of nonlinear model updating was reviewed, and on this basis, some critical problems existing in nonlinear model updating technologies were summarized from the aspects of nonlinear system identification, nonlinear model updating methods, and uncertainty quantification of nonlinear models. In addition, in view of the damage identification, performance assessment, and safety monitoring of complex structures, the application of nonlinear model updating in bridge structures was further discussed. Research results indicate that the response characteristic quantities represented by natural frequencies and modes of vibration can only reflect the physical characteristics of time-invariant structures. However, for nonlinear structures, their mechanical properties change with the external excitation, and thus the model updating methods based on characteristic quantities of linear systems are not suitable for nonlinear structures with obvious time-varying characteristics. The instantaneous frequency and amplitude of the principal component of structural dynamic response contain the phase and amplitude information of vibration response signals. They can comprehensively reflect the non-stationary characteristics of structural responses under dynamic loads. The dynamic characteristics of nonlinear structures can be properly represented by using the instantaneous characteristic quantities with time-varying characteristics to construct the objective function. With the consideration of uncertainty factors, such as the measurement noise, model errors, and numerical calculation methods, the uncertainty model updating method can improve the model updating result by comprehensively using the measured response data. Since many parameters and massive computations are involved in the nonlinear model updating of complex structures, its application in the practical engineering structures is greatly limited. Therefore, the reasonable selection of representative nonlinear model parameters and improving the computational efficiency are urgent problems to be solved. 12 figs, 95 refs. |
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