Abstract:

The Gaborexpansionbased time frequency filtering is employed to process measured signals before conducting parameter identification. With Gabor expansion, the local characteristics of a signal can be shown in the timefrequency domain, according to which the properties of responses are acquired and the response signals can be filtered by elimination or interception. This technique can be applied to both stationary and nonstationary signals. Attribute to this technique, more information about the signals and systems can be gained, such as the distribution of natural frequencies, energy assemble functions, quantity of properties contents in each channel.

Key words: vibration and wave, gabor expansion, modal parameter identification, time frequency representation, nonstationary signal, stationary signal

摘要： 对Gabor时频变换在模态参数辨识中的应用进行了探讨,将基于Gabor系数展开的时频滤波方法作为参数辨识的前处理手段之一，该方法对于平稳、非平稳信号都适用。根据信号在时频域内的分布特征，可以直接观测系统的频率分布情况、模态密集程度、能量聚集性、各通道响应信号所含特征量的多少等信息，从而对响应信号的特征构成进行初步判断，并通过剔除、截取等操作实现对响应信号的滤波，更有利于模态参数的辨识。

关键词: 振动与波, Gabor变换, 模态参数辨识, 时频分布, 非平稳信号, 平稳信号