基于自适应最稀疏时频分析的结构损伤检测方法

The damage detection method base on the adaptive and sparsest time-frequency analysis

研究了一种新的自适应时频分析方法——自适应最稀疏时频分析(ASTFA)方法,并将其运用于结构振动响应分析,提出了基于ASTFA的结构损伤检测方法。ASTFA方法在EMD方法和压缩感知的基础上,建立包含所有IMF分量的过完备字典,通过寻找原信号的最稀疏表示,将信号分解问题转化为非线性优化问题,在目标优化的过程中实现信号的自适应分解,并直接得到各个分量的瞬时频率和瞬时幅值。在介绍ASTFA的基础上,对ASTFA和EMD进行了对比,结果表明了ASTFA方法的优越性。利用ASTFA方法识别了结构的模态参数,提出了基于分量信号瞬时频率和瞬时能量的损伤指标,对结构损伤进行了检测。对实际信号的分析结果表明,ASTFA方法可以有效地应用于结构损伤检测。

A self-adaptive time-frequency analysis method—the adaptive and sparsest time-frequency analysis（ASTFA）and its application to damage detection are studied in the paper.Based on the Empirical Mode Decomposition（EMD）and the compressed sensing theory,the ASTFA method translates the signal processing method into a non-linear optimization problem by looking for the sparest decomposition of the signal in the largest possible dictionary consisting of intrinsic mode functions.The adaptive decomposition of the original signal can be obtained through the solution of the optimization problem,and the instantaneous frequency and the instantaneous amplitude can be obtained directly.Then,an comparison is made between the ASTFA method and the EMD method to show the superiority of the ASTFA.The modal parameters are estimated and a damage index is proposed based on the instantaneous frequency and the instantaneous energy.The analysis results of the experiments show that the ASTFA method can be applied to the structural damage detection.