Background

Modal parameters of a quayside container crane can reflect the vibration performance of a structure at work. Identifying these parameters through modal tests can be used to improve the design scheme, evaluate performance, and detect damage.

Method

This paper introduces the process of modal parameter identification based on data-driven stochastic subspace identification (SSI). The proposed algorithm is programmed based on the MATLAB platform. The effectiveness of the algorithm is verified by a numerical three-degree-of-freedom vibration model. In this paper, the overall structure of a quayside container crane was modally tested for the first time under ambient excitation. The test scheme using the mobile measurement method is introduced in detail. The signal data collected by the modal test are used as the input data of the data-driven SSI, and the first seven natural frequencies, damping ratios, and mode shapes of the crane are identified successfully. Furthermore, the finite element model of the crane is established with ANSYS, and the first seven frequencies and mode shapes are also obtained.

Results and Conclusions

By comparing the results of the two methods, it can be found that the parameters identified by the proposed algorithm have high accuracy. The proposed method can be applied to the health monitoring system of the quayside container crane.

中文翻译：

---

基于数据驱动随机子空间辨识的码头集装箱起重机模态参数辨识

背景

码头集装箱起重机的模态参数可以反映建筑物在工作中的振动性能。通过模态测试识别这些参数可用于改进设计方案，评估性能和检测损坏。

方法

本文介绍了基于数据驱动的随机子空间识别（SSI）的模态参数识别过程。该算法是基于MATLAB平台进行编程的。通过数值三自由度振动模型验证了该算法的有效性。在本文中，首次在环境激励下对码头集装箱起重机的整体结构进行了模态测试。详细介绍了使用移动测量方法的测试方案。通过模态测试收集的信号数据用作数据驱动的SSI的输入数据，并且成功识别了起重机的前七个固有频率，阻尼比和模式形状。此外，利用ANSYS建立了起重机的有限元模型，

结果与结论

通过比较两种方法的结果，可以发现所提算法识别出的参数具有较高的精度。所提出的方法可以应用于码头集装箱起重机的健康监测系统。