基于影响矩阵及粒子群算法的斜拉桥自动调索

Automatic Cable Force Adjustment For Cable Stayed Bridge Based On The Influence Matrix And Particle Swarm Optimization Algorithm

摘要:

大跨度斜拉桥属于高次超静定结构，其求解索初拉力的过程通常需要具有相当经验的调索计算人员进行反复的迭代试算。本文给出一种基于影响矩阵法和粒子群智能优化算法的调索计算方案，能够根据特定的结构在很短的时间内自动搜索出满足使用要求的索初拉力。利用编制的程序，对某斜拉桥有限元模型的索力进行了自动调索，结果表明，该方案可以快速地获得合理的群索初始拉力，并使得相对误差控制在2%以内。本文建议自动调索方法为斜拉桥建模分析和施工监控索力计算提供了一种新的高效解决思路。

Abstract:

As a high level statically indeterminate structure, the cable forces of cable-stayed bridge are often need to be computed tautologically both when doing FEM structural analysis or construction observation computing of bridge. This time consuming computing process also need well training on analytical mechanics and deep insight to the behavior of bridge structure. In this work, an influence matrix and particle swarm intelligence optimization algorithm based cable force adjustment computing Algorithm are proposed, with the aims to realize the automatic cable force adjustment when facing the cable stayed bridge structural analysis or construction observation computing tasks. The cable force adjustment is modeled as an auto resolution space searching process with the optimization objective expressed by influence matrix of bridge, and particle swarm intelligence optimization algorithm replaces the tautological manual tentative calculation. The programs are developed and applied to the true cable stayed bridge, and the result showed that in most cases, a rational resolution for cable force collection can be arrived at handily and promptly, without any manual interventions. And in all case, the relative errors are under controlled less than 2%. The proposal method is expected to provide a efficient resolution or guideline for structural FEM analysis and construction observation computing on cable stayed bridge.