机构地区: 华中科技大学机械科学与工程学院数字制造与装备技术国家重点实验室
出 处: 《华中科技大学学报(自然科学版)》 2008年第5期67-70,共4页
摘 要: 系统地阐述了自然激励技术(NExT)与小波分析在大型机械结构的模态参数识别中的应用.机械系统在白噪声激励下利用NExT方法可得到系统响应信号的互相关信号,并结合改进的Morlet小波对其进行了分析,通过调整小波中心频率及分析信号的长度,可有效地抑制端部效应的产生并能较准确地识别机械结构的密集模态参数.仿真试验的分析结果验证了该方法的可行性及准确性. Natural excitation technique (NEXT) and wavelet analysis were described, which are used to identify the modal parameters of large mechanical structure. Under the excitation of white noise, the NExT method is applied to deal with the response signal of mechanical system to get the cross-correlation signal. And it is processed by the improved Morlet wavelet which is tuned by the central frequency of wavelet and length of signal, the closed modal parameters can be identified accurately and the end effect is restrained. The simulation analysis validate that the method is feasible and effective.