动力特征解灵敏度分析的结构关键区域判别

Evaluation of critical region based on dynamic eigensensitivity analysis

实际工程结构体量大、病害多,各局部损伤对结构整体性能影响差异大,关键区域的微小损伤将威胁整体结构安全。因此,有必要判定结构的关键区域,使结构监测、评估、管养主次分明,重点突出。提出了加权融合多阶动力特征解灵敏度的结构关键区域判别方法。基于振型质量参与系数确定了特征解数目和各阶特征解的权重系数,建立了融合多阶归一化的加权特征值和特征向量灵敏度的灵敏度指标,对灵敏度指标求二阶范数得到关键区域指标,作为关键区域判定依据。该判定方法是一种定量的判定依据。将该方法运用于一榀平面框架和一座上承式拱桥,结果表明,框架结构的关键区域为梁柱节点和支座附近的柱子区域,拱桥关键区域为拱圈的拱脚区域;另外,结构关键区域并非一成不变,局部损伤会导致原本不关键区域变成关键区域。研究的关键区域判别方法对提高健康监测和评估效率、节约人力物力有重要意义。

The actual engineering structure is usually large-scale and has various local damages.Different damage has different im‐pact on the overall performance of the structure.Small damages in critical regions can threaten the safety of the overall structure.Therefore,it is necessary to identify the critical regions of the structure,so that the monitoring,evaluation,and management of the structure have a clear priority and focus.This paper proposes a method for discriminating structural critical regions based on weighted sensitivity analysis of dynamic eigensolutions.The proposed method deduces the sensitivity of eigenvalues and eigenvec‐tors with respect to element stiffness parameters.Firstly,the number of modes for analysis and the weight coefficient of each re‐tained mode are determined based on modal mass participation coefficient,and a weighted sensitivity index that combines multi-or‐der normalized eigenvalues and eigenvector sensitivity is established.The sensitivity index seeks the second-order norm to obtain the critical region index,which is used as the basis for determining the critical regions.This method is a scientific and quantitative judgment basis,and is applied to a frame and an arch bridge.The results show that the critical regions of the frame structure are the column area near the beam-column node and the support,and the critical regions of the arch bridge are the arch toe area of the arch ring.In addition,the critical region is not static,and local damage can cause the originally uncritical region to become a critical re‐gion.The proposed critical region identification method improves the efficiency of health monitoring and evaluation,and to save manpower and material resources.