基于改进确定-随机子空间算法的桥梁结构模态参数识别

Modal parameter identification of bridge structures based on an improved deterministie-stochastic subspace identification method

为了实现桥梁结构模态参数的智能化在线跟踪识别,提出了一种基于滑窗技术、模糊C均值聚类算法与确定-随机子空间算法的时域识别(SC-CDSI)算法。对桥梁结构的输入信号和输出信号进行加窗划分处理,分析了窗函数、窗口大小及窗口步长的确定标准;将频率、阻尼比及模态振型作为模糊C均值聚类算法的聚类元素完成对稳定图中有效模态的智能化辨识;以某振动台试验桥为参数识别对象,并将所得结果与MIDAS有限元结果作对比分析。结果表明,所提SC-CDSI识别算法可以精确实现桥梁结构频率的在线跟踪智能化识别,且识别的结果具有可靠性。

In order to realize the intelligent online tracking and identification of bridge structural modal parameters,a novel time-domain identification method based on a sliding window-fuzzy C-means algorithm combined with the deterministic-stochastic subspace identification(SC-CDSI)method was proposed.The input and output signals of the bridge structure were divided into separate windows,then the determination standards of window function,window length and step length were analyzed.The frequency,damping ratio and mode shape were used as the clustering elements of the fuzzy C-means clustering algorithm to complete the intelligent identification of effective modes in the stability diagram.A shaking-table test bridge model was used as a parameter identification object,and its results were compared with the MIDAS finite element results.The results indicate that the proposed SC-CDSI method can precisely realize the intelligent online tracking and identification of the frequency of bridge structures and its identification result exhibits higher stability and reliability.