复杂结构试验/理论振型的匹配是模态参数型修正过程的重要内容。以测量并获取用于模态参数识别的最佳信息为目标，实现布置在结构上有限数量的传感器能有效避免信息冗余，提出了一种聚类优化的传感器布置方法。根据结构模态中各自由度振型的动力相似性，应用k-means聚类算法对自由度进行自动集结并分类。采用有效独立法分别从各聚类自由度中搜索出模态分辨率最高的传感器位置作为实际的测量位置。最后通过一个悬臂梁、一个悬臂薄板的数值分析和一个旋转滤光轮组件的模态测试试验对该优化布置方法进行验证。分析结果表明，这种方法能有效选出独立敏感性测点，并且具有较高的搜索效率。
Abstract
The match of experimental/theoretical model of complex structure is an important part in modal parameter modification. To measure and obtain the best information, a clustering optimal method of sensor placement is proposed. This method can effectively avoid redundancy by using a limited number of sensors. According to the similarity of the mode shape values in important modes, the DOFs are auto-clustered by using k-means clustering algorithm. The effective independent method is used to search the sensor locations with the highest modal resolution from each cluster. Finally, the numerical analysis of a cantilever beam and a cantilever plate and the modal test of a filter wheel assembly are carried out to verify the optimization method. The result shows that this method can effectively select the independent sensitive locations, and its search efficiency is much higher.
关键词
传感器布置 /
K-means聚类 /
有效独立法 /
模态试验 /
模型验证
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Key words
sensor placement /
K-means clustering /
effective independent method /
Modal test /
Model validation
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参考文献
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