[论文解读] Frequency-based tension assessment of an inclined cable with complex boundary conditions using the PSO algorithm

Wenming Zhang, Zhiwei Wang+2 more|arXiv (Cornell University)|Aug 11, 2021

Structural Health Monitoring Techniques参考文献 34被引用 7

一句话总结

本研究提出一种基于频率的缆索张力识别方法，用于具有复杂边界条件的斜缆，采用粒子群优化（PSO）算法。通过建模缆索倾斜角、垂度-伸长性、弯曲刚度以及边界转动和侧向刚度，并利用有限差分法对振动模态方程进行离散化，基于PSO的多参数识别方法在张力估计中表现出高精度，已在实际斜拉桥上通过现场测量得到验证，性能优于传统方法。

ABSTRACT

The frequency-based method is the most commonly used method for measuring cable tension. However, the calculation formulas for the conventional frequency-based method are generally based on the ideally hinged or fixed boundary conditions without a comprehensive consideration of the inclination angle, sag-extensibility, and flexural stiffness of cables, leading to a significant error in cable tension identification. This study aimed to propose a frequency-based method of cable tension identification considering the complex boundary conditions at the two ends of cables using the particle swarm optimization (PSO) algorithm. First, the refined stay cable model was established considering the inclination angle, flexural stiffness, and sag-extensibility, as well as the rotational constraint stiffness and lateral support stiffness for the unknown boundaries of cables. The vibration mode equation of the stay cable model was discretized and solved using the finite difference method. Then, a multiparameter identification method based on the PSO algorithm was proposed. This method was able to identify the tension, flexural stiffness, axial stiffness, boundary rotational constraint stiffness, and boundary lateral support stiffness according to the measured multiorder frequencies in a synchronous manner. The feasibility and accuracy of this method were validated through numerical cases. Finally, the proposed approach was applied to the tension identification of the anchor span strands of a suspension bridge (Jindong Bridge) in China. The results of cable tension identification using the proposed method and the existing methods discussed in previous studies were compared with the on-site pressure ring measurement results. The comparison showed that the proposed approach had a high accuracy in cable tension identification.

研究动机与目标

• 解决传统基于频率的方法因边界条件过度简化而导致的显著张力识别误差问题。
• 开发一个综合缆索模型，包含倾斜角、垂度-伸长性、弯曲刚度以及未知的边界刚度（转动和侧向）。
• 利用实测的多阶固有频率，实现对多个缆索参数（张力、轴向刚度、弯曲刚度和边界刚度）的同时识别。
• 通过金洞大桥的实际斜拉桥现场压力环测量结果，验证所提方法的准确性。

提出的方法

• 开发了一种改进的斜拉缆索模型，包含倾斜角、垂度-伸长性、弯曲刚度以及边界转动和侧向支承刚度。
• 采用有限差分法对缆索模型的振动模态方程进行离散化，以实现特征值问题的数值求解。
• 提出一种基于粒子群优化（PSO）算法的多参数识别框架，用于同时估计张力、轴向刚度、弯曲刚度和边界刚度。
• PSO算法通过最小化多阶模态下实测与计算固有频率之间的误差，实现单次优化运行中所有参数的联合优化。
• 该方法在数值上实现，并使用合成数据进行验证，随后应用于金洞大桥的实际现场数据。
• 以现场压力环测量结果作为真实值，将该算法与现有方法进行对比评估。

实验结果

研究问题

• RQ1 在模型中引入复杂边界条件（转动和侧向刚度）如何影响基于频率的缆索张力识别精度？
• RQ2 PSO算法能否有效且同时从实测多阶频率中识别出多个缆索参数（张力、刚度、边界约束）？
• RQ3 与假设理想化边界条件的传统基于频率的方法相比，所提方法在多大程度上降低了张力识别误差？
• RQ4 当应用于具有未知边界条件的实际倾斜缆索时，该方法的准确性如何？该结果通过现场测量得到验证。

主要发现

• 所提方法在缆索张力识别中表现出高精度，其结果与金洞大桥现场压力环测量结果高度一致。
• 在模型中引入边界转动和侧向刚度后，张力估计精度显著优于假设理想铰接或固定支承的方法。
• 基于PSO的多参数识别在多个数值算例中均成功收敛至稳定解，表现出良好的鲁棒性和可靠性。
• 该方法在斜缆且边界条件非理想的情况下，优于传统基于频率的分析方法。
• 对振动模态方程的有限差分离散化为复杂缆索模型提供了准确且高效的数值解法。
• 现场应用结果证实，该方法在实际土木基础设施监测中具有实际可行性和有效性。