基于随机减量法的分布式结构模态参数识别

发布时间：2018-02-25 00:25

本文关键词： 随机减量法分布式传感器网络特征系统实现算法稳定图模态识别　出处：《振动与冲击》2017年17期 　论文类型：期刊论文

【摘要】：分区进行平行分析处理的技术已成为大型结构密集布置无线智能传感器网络检测结构系统的重要任务。提出基于随机减量法的分布式数据采集和模态识别方法。以两边简支板模型试验为例,采用ISM400无线智能传感器,通过自然激励法获得测试结构的响应信号,计算随机减量函数,然后运用特征系统实现算法提取系统的状态空间参数,并结合稳定图的方法剔除虚假模态,识别出结构的模态性能参数。以模态置信度为判据对比分析分布式算法与集中式算法的识别效果,结果表明两种算法吻合良好。
[Abstract]:The technology of parallel analysis and processing in partitioning has become an important task in the detection structure system of large-scale structured dense wireless intelligent sensor network. A distributed data acquisition and modal identification method based on random decrement method is proposed. Taking the model test of simply supported plates on both sides as an example, Using ISM400 wireless intelligent sensor, the response signal of the test structure is obtained by natural excitation method, and the random decrement function is calculated. Then, the state space parameters of the system are extracted by using the feature system algorithm. The modal performance parameters of the structure are identified by using the method of stability graph, and the recognition effect of the distributed algorithm and the centralized algorithm is compared and analyzed with the modal confidence degree as the criterion. The results show that the two algorithms are in good agreement with each other.
【作者单位】：烟台大学土木工程学院;蔚山科学技术大学城市与环境工程学院;伊利诺伊大学香槟分校土木与环境工程系;
【基金】：国家自然科学基金(51479174)
【分类号】：TN929.5;TP212.9;TU317

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