【摘要】 大型复杂工程结构的损伤实际上是一个渐进损伤的过程,为解决结构损伤识别中非平稳随机信号的时变性并有效地识别这个损伤过程,研究了基于Hilbert-Huang变换的结构渐进损伤特征提取方法.首先模拟产生了多自由度结构系统发生渐进损伤的加速度振动信号;然后对加速度振动信号进行经验模式分解,将其分解为多个平稳的固有模式函数之和;再选取若干个包含主要损伤信息的固有模式函数进行Hilbert变换,提取瞬时频率作为特征参数进行损伤特征提取.研究结果表明:HHT是一种有效的信号处理方法,通过提取瞬时频率,可以准确地提取结构渐进损伤的特征.更多还原

【Abstract】 The large complex structure damage is a progressive process actually.In order to solve the time-variable of non-steady random signal during the process of structure health monitoring and to identify the process efficiently,a feature extraction method of structure progressive damage is studied based on Hilbert-Huang transform.First,the acceleration vibration signals of a multiple-degree of freedom structure model are simulated by reducing the stiffness gradually,and decomposed several smoothed intrinsic mode function(IMF).Then,some IMFs which contain main information are selected and transformed by Hilbert,and the instantaneous frequency is extracted as feature parameter.The result indicated that:HHT is an effective signal processing way that can accurately extract progressive damage feature by means of extracting instantaneous frequency.更多还原