基于模型修正与时序分析的结构损伤识别方法研究
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摘要
随着世界经济与科学技术的快速发展,现代结构设计不断呈现出大型化、复杂化、多样化的趋势,而这些结构设计使用寿命较长、影响力较大,一旦失事,将会造成严重的生命财产损失。因此,为了保障结构的安全性、完整性与耐久性,在许多新建的大型结构和基础设施上增设了长期结构健康监测系统,对结构状态进行实时监测,为实现结构状态评估提供依据。结构损伤识别(Structural damage identification)作为结构健康监测技术的核心,对掌握结构工作状态以及评估结构安全性具有重要的意义。尽管在过去的20年内结构损伤识别得到了广泛的研究,但离实际工程应用还有一定的距离,还需要进行深入研究。基于此,本文通过模型修正与时序分析方法对结构损伤识别进行系统研究,主要取得以下几个方面的研究成果：
(1)详细介绍了新型智能优化算法——和声搜索算法(Harmony Search Algorithm,缩写为HSA)的基本原理以及现有比较常见的改进方法。针对改进的HSA在搜索范围较大时,收敛速度慢且容易陷入局部最优的问题,提出了一种快速和声搜索算法(Fast Harmony Search Algorithm,缩写为FHSA),该算法既保证了最优解的集中性(intensification),也增加了寻求最优解时的多样性(diversification),最后给出了FHSA的适用性建议；
(2)HSA作为一种新近提出的启发式智能优化算法,在许多领域得到应用,但在结构健康监测领域则鲜有见到。本文将HSA引入到结构健康监测领域,并成功应用于结构有限元模型修正。在分析中,将结构有限元模型修正问题转换为非线性优化问题,以模态参数的残差作为目标函数,分别对模态参数为确定性量与不确定性量两种情况进行分析。但在分析中发现,FHSA无法给出选择随机数产生的分布准则,因此对FHSA进行了改进,提出了一种改进的快速和声搜索算法(Improved Fast Harmony Search Algorithm,缩写为IFHSA).通过数值算例验证了HSA在有限元模型修正中的可行性,并将其应用于广州塔benchmark中的缩减模型修正。这不仅拓宽了HSA的应用领域,也为有限元模型修正提供了另一种思路；
(3)将HSA成功应用于结构损伤识别。当采用模型修正方法对结构损伤进行识别时,可以将结构损伤识别转换为优化问题。在分析中,将频率误差、模态置信度以及残余力向量(residual force vector)以不同权重值组合从而建立目标函数,利用IFHSA逐步实现对结构参数模型的修正,进而对结构损伤进行识别。通过算例对该方法在无噪声干扰与有噪声干扰情况下的识别结果进行了分析。分析结果表明,该方法可以用于结构损伤识别,并且具有一定的抗噪性；
(4)时间序列模型作为信息的凝聚器,可用于建立反映结构特性的参数模型。通过对时间序列模型进行理论分析,提出了一种基于时间序列预测模型的结构损伤识别方法。在分析中,首先对结构响应数据进行预处理,建立结构在完好工况下参考自回归(Auto-regression,缩写为AR)预测模型,利用参考AR预测模型计算待识别工况的残差,通过定义待识别工况与参考AR预测模型的残差的方差之比作为损伤指标,对结构损伤进行识别。通过算例分析表明,该损伤指标不仅可以判断结构是否发生损伤,而且还可以识别结构损伤位置；
(5)基于传递函数可以反映结构输入输出相互关系(结构特性)的思想,提出了一种基于ARX (Auto Regressive model with eXogenous input,缩写为ARX)模型建立伪传递函数(Pseudo-Transfer Function,缩写为PTF)的损伤定位方法,并结合自然激励技术对其进行改进,使其可用于环境激励下结构的损伤识别。通过数值模拟与6层剪切型框架模型试验,验证了该方法在损伤识别中的有效性。最后将其应用于广州塔缩减模型的损伤识别,并对该方法在高耸结构损伤识别中应用进行了研究。
With the rapid development of world economy and technology, modern structural design presents a large-scale, complex, diversification trend, and also have a longer life period, influential, once it is crashed, will lead to serious life and property losses. Therefore, in order to ensure the structure of the security, integrity, applicability and durability, many new large-scale structures and infrastructures installed long-term structural health monitoring system, real-time monitoring of the security situation of the structure, it proved valuable data for the study of the structural state assessment. Although the extensive research and application in the past20years, the further research are need for the structural damage identification. Therefore, model updating and time series was brought into the structural damage identification and follow results are obtained:
(1) The fundamental principle of the novelty intelligent algorithm-Harmony Search Algorithm (HSA) and improved methods were introduced. As the improved HSA has a shortcoming of easily plunging into a local optimal solution and convergent slowly when searching in an extensive range. A Fast Harmony Search Algorithm (FHSA) was put forward. This method not only ensures the intensification of the optimal solution and also increases the diversification. Finally, the suggestions of the feasibility of the FHSA was gived;
(2) Harmony Search Algorithm (HSA), as a novel heuristic intelligent optimization algorithm, have been applied in many fields, but rarely seen in the field of structural health monitoring. HSA was introduced into the field of structural health monitoring, and successfully applied into structure finite element model updating. In this paper, structural finite element model updating is converted into a nonlinear optimization problem and solved by the HSA. Structural modal parameters were considered as the certainty and uncertainty respectively. Numerical simulation shows that it is difficult to choose which distribution can be used in FHSA, therefore, Improved Fast harmony search algorithm (IFHSA) was proposed. The feasibility of the HSA in the field of the finite element updating was verified and it was applied into the reduced model updating of the Canton Tower. This not only extends the applying field of HSA, but also proved a new concepts for model updating;
(3) HSA has been successfully applied to the felid of structural damage identification. When structural damage was identified using the model updating method, it can be converted into an optimization problem. In this study, objective function can be established using frequency error, modal assurance criterion and residual force vector combined with different weight value, structural damage were identified by using updating the structural parameter model. The feasibility of the application of HSA in the damage identification was verified and the influence of the noise was studied. The results show that this method has certain noise immunity.
(4) As an information coalescer, time series can be used to establish structural parameter model, therefore, a new damage identification method was proposed based on the time series prediction model. Firstly the structure response data preprocessing, the structural response under health were used as the reference data, reference autoregressive (AR) prediction mode was established; Second, the residual of the test structure using reference AR model, the variance of the residual were taken as the damage index., the structural damage were identified. Finally, a numerical simulation shows that the damage index can not only determine whether the structure damage occurs, but also can identify structural damage location;
(5) Based on the concept that transfer function can reflect the relationship between input and output structure, a damage location method was put forward by using the ARX modal establishing the Pseudo Transfer Function (PTF), and the method was improved by combining the natural excitation technique, and make its feasible in the damage identification of structures under ambient vibration. The effectiveless of this mothod verified through the numerical simulation and6floors shear frame model experimental. Finally, this method was applied into damage identification of reduced model of Canton Tower model and, the application of this method in damage identification of high-rise structure was studied.
(1)详细介绍了新型智能优化算法——和声搜索算法(Harmony Search Algorithm,缩写为HSA)的基本原理以及现有比较常见的改进方法。针对改进的HSA在搜索范围较大时,收敛速度慢且容易陷入局部最优的问题,提出了一种快速和声搜索算法(Fast Harmony Search Algorithm,缩写为FHSA),该算法既保证了最优解的集中性(intensification),也增加了寻求最优解时的多样性(diversification),最后给出了FHSA的适用性建议；
(2)HSA作为一种新近提出的启发式智能优化算法,在许多领域得到应用,但在结构健康监测领域则鲜有见到。本文将HSA引入到结构健康监测领域,并成功应用于结构有限元模型修正。在分析中,将结构有限元模型修正问题转换为非线性优化问题,以模态参数的残差作为目标函数,分别对模态参数为确定性量与不确定性量两种情况进行分析。但在分析中发现,FHSA无法给出选择随机数产生的分布准则,因此对FHSA进行了改进,提出了一种改进的快速和声搜索算法(Improved Fast Harmony Search Algorithm,缩写为IFHSA).通过数值算例验证了HSA在有限元模型修正中的可行性,并将其应用于广州塔benchmark中的缩减模型修正。这不仅拓宽了HSA的应用领域,也为有限元模型修正提供了另一种思路；
(3)将HSA成功应用于结构损伤识别。当采用模型修正方法对结构损伤进行识别时,可以将结构损伤识别转换为优化问题。在分析中,将频率误差、模态置信度以及残余力向量(residual force vector)以不同权重值组合从而建立目标函数,利用IFHSA逐步实现对结构参数模型的修正,进而对结构损伤进行识别。通过算例对该方法在无噪声干扰与有噪声干扰情况下的识别结果进行了分析。分析结果表明,该方法可以用于结构损伤识别,并且具有一定的抗噪性；
(4)时间序列模型作为信息的凝聚器,可用于建立反映结构特性的参数模型。通过对时间序列模型进行理论分析,提出了一种基于时间序列预测模型的结构损伤识别方法。在分析中,首先对结构响应数据进行预处理,建立结构在完好工况下参考自回归(Auto-regression,缩写为AR)预测模型,利用参考AR预测模型计算待识别工况的残差,通过定义待识别工况与参考AR预测模型的残差的方差之比作为损伤指标,对结构损伤进行识别。通过算例分析表明,该损伤指标不仅可以判断结构是否发生损伤,而且还可以识别结构损伤位置；
(5)基于传递函数可以反映结构输入输出相互关系(结构特性)的思想,提出了一种基于ARX (Auto Regressive model with eXogenous input,缩写为ARX)模型建立伪传递函数(Pseudo-Transfer Function,缩写为PTF)的损伤定位方法,并结合自然激励技术对其进行改进,使其可用于环境激励下结构的损伤识别。通过数值模拟与6层剪切型框架模型试验,验证了该方法在损伤识别中的有效性。最后将其应用于广州塔缩减模型的损伤识别,并对该方法在高耸结构损伤识别中应用进行了研究。
With the rapid development of world economy and technology, modern structural design presents a large-scale, complex, diversification trend, and also have a longer life period, influential, once it is crashed, will lead to serious life and property losses. Therefore, in order to ensure the structure of the security, integrity, applicability and durability, many new large-scale structures and infrastructures installed long-term structural health monitoring system, real-time monitoring of the security situation of the structure, it proved valuable data for the study of the structural state assessment. Although the extensive research and application in the past20years, the further research are need for the structural damage identification. Therefore, model updating and time series was brought into the structural damage identification and follow results are obtained:
(1) The fundamental principle of the novelty intelligent algorithm-Harmony Search Algorithm (HSA) and improved methods were introduced. As the improved HSA has a shortcoming of easily plunging into a local optimal solution and convergent slowly when searching in an extensive range. A Fast Harmony Search Algorithm (FHSA) was put forward. This method not only ensures the intensification of the optimal solution and also increases the diversification. Finally, the suggestions of the feasibility of the FHSA was gived;
(2) Harmony Search Algorithm (HSA), as a novel heuristic intelligent optimization algorithm, have been applied in many fields, but rarely seen in the field of structural health monitoring. HSA was introduced into the field of structural health monitoring, and successfully applied into structure finite element model updating. In this paper, structural finite element model updating is converted into a nonlinear optimization problem and solved by the HSA. Structural modal parameters were considered as the certainty and uncertainty respectively. Numerical simulation shows that it is difficult to choose which distribution can be used in FHSA, therefore, Improved Fast harmony search algorithm (IFHSA) was proposed. The feasibility of the HSA in the field of the finite element updating was verified and it was applied into the reduced model updating of the Canton Tower. This not only extends the applying field of HSA, but also proved a new concepts for model updating;
(3) HSA has been successfully applied to the felid of structural damage identification. When structural damage was identified using the model updating method, it can be converted into an optimization problem. In this study, objective function can be established using frequency error, modal assurance criterion and residual force vector combined with different weight value, structural damage were identified by using updating the structural parameter model. The feasibility of the application of HSA in the damage identification was verified and the influence of the noise was studied. The results show that this method has certain noise immunity.
(4) As an information coalescer, time series can be used to establish structural parameter model, therefore, a new damage identification method was proposed based on the time series prediction model. Firstly the structure response data preprocessing, the structural response under health were used as the reference data, reference autoregressive (AR) prediction mode was established; Second, the residual of the test structure using reference AR model, the variance of the residual were taken as the damage index., the structural damage were identified. Finally, a numerical simulation shows that the damage index can not only determine whether the structure damage occurs, but also can identify structural damage location;
(5) Based on the concept that transfer function can reflect the relationship between input and output structure, a damage location method was put forward by using the ARX modal establishing the Pseudo Transfer Function (PTF), and the method was improved by combining the natural excitation technique, and make its feasible in the damage identification of structures under ambient vibration. The effectiveless of this mothod verified through the numerical simulation and6floors shear frame model experimental. Finally, this method was applied into damage identification of reduced model of Canton Tower model and, the application of this method in damage identification of high-rise structure was studied.
引文
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