摘要
ERA/DC 利用脉冲响应数据构造 Hankel 矩阵时运用了相关技术,因此对信号中的白噪声有抑制效果,但实际数据所含的噪声中,除随机噪声外,还有尖脉冲噪声、漂移等其它噪声。为了获得理想的识别效果,利用小波算法对脉冲响应数据进行去噪处理,再用 ERA/DC 进行识别。两自由度的阻尼弹簧质量系统以及卫星缩尺模型的仿真结果表明,小波去噪方法对多种噪声形式均有抑制作用,能提高 ERA/DC 的识别精度,可用于 ERA/DC识别的信号去噪。
ERA/DC (eingensystem realization algorithm using data correlation) adopts the data correlation approach when constructing the Hankel matrix with impulse response data. Therefore, ERA/DC can restrain the white noise in the signal, but the practical data also contain other kinds of noise, such as random noise, impulsive noise, and excursion. In order to get better identification results, the impulse response data is denoised using the wavelet analysis method. Then, the ERA/DC is adopted to identify the denoised data. Simulations of a two-degree-of-freedom mass-spring-dashpot system and a satellite model are demonstrated. The results show that the denosing method based on wavelet analysis can suppress different kinds of noise, and improve the identification precision of ERA/DC. Therefore, it can be used as the denoising method for ERA/DC.
出处
《工程力学》
EI
CSCD
北大核心
2004年第6期91-96,共6页
Engineering Mechanics
基金
清华大学基础研究基金(JC2002007)资助项目
关键词
特征系统实现算法
模态参数识别
小波算法
信号去噪
脉冲响应数据
eigensystem realization algorithm
modal parameter identification
wavelet analysis
signal denoising
impulse response data
