基于有限测点的结构模型修正及载荷识别技术研究

Study on structural model modification and load identification based on limited measuring points

    摘要
  • 摘要:
      目的  高保真有限元模型和有效的载荷识别技术对于船体结构健康监测及评估至关重要。为此，提出一种基于改进粒子群算法的模型修正和载荷识别方法。
      方法  使用rastrigin函数对改进粒子群算法和经典粒子群算法进行对比。采用工字梁结构，在梁中间位置施加压力，在其表面粘贴有限数量的应变片，并将其分为用于模型修正和载荷识别的实测点与用于验证的监测点两部分。进行对工字钢分块弹性模量的修正验证，并进行基于修正后的数值高保真模型的载荷识别验证。
      结果  在利用rastrigin函数对改进粒子群算法的测试中，改进粒子群算法在不同粒子数下都表现出更好的全局最优解搜寻能力。在工字钢试验中，划分的两部分弹性模量在通过改进粒子群算法23步迭代后收敛于最优解。通过将试验监测点的应变数据与进行模型修正后得到的应变计算结果进行对比，应变相对误差在2%以内，验证了模型修正方法的正确性。此外，通过载荷识别方法识别出结构外载荷压力大小，识别计算值与试验施加载荷误差在2%以内，识别载荷与修正模型结合计算出的监测点应变值与试验数据相比误差最大值为3.74%，验证了载荷识别的有效性。
      结论  所提方法在对结构全局状态反演时具有较好的精度表现，能够为船体结构健康监测、剩余寿命预测以及预测性维修提供技术支撑。

     

    Abstract:
      Objectives  High fidelity finite element models and effective load identification technology are very important for ship structure health monitoring and evaluation. Therefore, a model updating and load identification method based on improved particle swarm optimization (PSO) is proposed.
      Methods  The Rastrigin function is used to compare the improved PSO algorithm with the classical PSO algorithm. An I-beam structure is adopted with pressure applied at the middle of the beam. A limited number of strain sensors are pasted on the surface and divided into two sets: the measured set for model correction and load identification, and the monitoring set for verification. The elastic modulus of the block division of the I-beam is modified and verified, and the load identification based on the modified numerical high fidelity model is verified.
      Results   In the test of the improved PSO algorithm by Rastrigin function, it shows better global optimal solution searching ability under different particle numbers. In the I-beam experiment, the elastic modulus of the two parts of the partition converges to the optimal solution after 23 iterations. By comparing the strain data of the test monitoring points with the data of the numerical calculation results after model correction, the relative error of the strain is within 2%, which verifies the correctness of the model updating method. In addition, the external load pressure of the structure is identified by the load identification method, and the error between the identified calculated value and the load applied in the test is within 2%. The maximum error between the strain value of the monitoring points calculated by the combination of the identified load and modified model and test data is 3.74%, which verifies the effectiveness of the load identification.
      Conclusions  The proposed method has a good precision performance in the inversion of the global state of the structure, and can provide technical support for hull structure health monitoring, residual life prediction and predictive maintenance.

     

    • HTML全文
    • 参考文献(19)
    • 相关文章
    • 施引文献
  • 资源附件(0)

/

返回文章
返回