短索振动特性及参数识别研究

发布时间：2018-06-06 21:30

本文选题：索 + 频率法　；参考：《西南交通大学》2017年硕士论文

【摘要】：随着含索空间结构形式的推广应用,索结构在土木工程行业中越来越多地出现,也得到越来越多地重视。随之,索结构的索力测试以及参数识别问题需得到更好地解决,包括对索力、抗弯刚度、边界条件等的识别。就目前而言,长索的索力识别精度已达到较高的水平,因为长索受抗弯刚度以及边界条件的影响较小,多数情况下忽略·其影响造成的误差并不大。但对于短粗的索,或者是索力较小的索,抗弯刚度以及边界条件的影响非常大,若是忽略将会造成极大的误差。而现阶段,针对复杂边界条件下有抗弯刚度的索,还没有提出适用范围合理、精度较高的索力计算公式。索结构的参数识别问题也没有得到很好的解决。基于以上问题,本文主要工作如下:(1)基于索在平面内的竖向振动平衡方程,在一般边界条件的振动模型下推导出频率方程的通解。求解该超越方程,分情况将频率方程的求解结果进行曲线拟合,进而提出了考虑索抗弯刚度以及索端弹性转动约束的索力计算实用公式。该公式具有精度高、形式简洁、方便计算、可显式计算索的抗弯刚度等优点,可作为工程实际运用参考。(2)结合本文提出的索力计算公式,提出在特殊边界条件下索参数的识别方法;找出一般边界条件下各参数对索的n-T_n曲线的影响规律,进而提出索的参数识别方法。其原则就是使索的n-T_n曲线保持水平。(3)结合振型节点法的原理,并用有限元模型验证了振型节点法的精度,在本文推出的索力计算公式的基础上,讨论了关于索的参数识别问题。在具备某两阶及以上的实测频率时,对索力和抗弯刚度的识别问题能得到很好的解决。但对于边界条件的识别问题,目前还只能做到避开其影响,而不能识别出来。(4)由于解析方法仍有不可避免的误差存在,便可利用智能搜索的思想提出更为精确的索力计算方法。本文先提出一种矩阵分析方法,可以在索的索力、抗弯刚度、边界条件等已知的情况下得到精确的自振频率。再结合粒子群优化算法以实现索结构的参数识别。该方法精度更高、速度更快、适用范围更广。
[Abstract]:With the popularization and application of cable-bearing spatial structure, cable structure is more and more popular in civil engineering industry. Subsequently, the problems of cable force test and parameter identification need to be solved better, including the identification of cable force, bending stiffness, boundary conditions and so on. At present, the accuracy of cable force identification of long cables has reached a higher level, because long cables are less affected by flexural stiffness and boundary conditions, and the errors caused by neglecting their effects are not large in most cases. But for the short thick cable or the cable with less cable force, the bending stiffness and boundary conditions are greatly affected, and great errors will be caused if the cable is ignored. At present, for the cable with flexural stiffness under complex boundary condition, the calculation formula of cable force with reasonable application range and high precision has not been put forward. The problem of parameter identification of cable structure is not well solved. Based on the vertical vibration equilibrium equation of the cable in the plane, the general solution of the frequency equation is derived under the vibration model of general boundary conditions. By solving the transcendental equation, the results of the frequency equation are fitted by curve fitting, and a practical formula for calculating the cable force considering the bending stiffness of the cable and the elastic rotation constraint at the end of the cable is put forward. The formula has the advantages of high precision, simple form, convenient calculation, explicit calculation of the bending stiffness of cables, and can be used as a reference for engineering practice. The identification method of cable parameters under special boundary conditions is proposed, and the influence of each parameter on n-T _ n curve of cable under general boundary condition is found out, and the parameter identification method of cable is put forward. The principle is to keep the n-Tn curve of the cable horizontal. / 3) combined with the principle of the modal nodal method, the accuracy of the modal nodal method is verified by using the finite element model. On the basis of the cable force calculation formula derived in this paper, the problem of parameter identification of the cable is discussed. The identification problem of cable force and bending stiffness can be solved well when the measured frequency of two or more order is available. However, the problem of boundary condition recognition can only avoid its influence at present, but can not be recognized. (4) because the analytic method still has the inevitable error, we can use the idea of intelligent search to put forward a more accurate calculation method of cable force. In this paper, a matrix analysis method is proposed, which can obtain the exact natural frequency under the condition of cable force, bending stiffness, boundary condition and so on. Then the particle swarm optimization algorithm is used to realize the parameter identification of cable structure. This method has higher precision, faster speed and wider range of application.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU311.3

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