摘要
基于高拱坝在泄流激励下的实测振动响应,提出了一种基于经验模态分解和固有模态函数小波降噪的信号处理和模态特征提取方法。首先,利用经验模式分解将含有噪声的高拱坝泄洪振动响应信号分解成一系列的固有模态函数;然后,基于对每个固有模态函数的特性分析选取相应的小波基对固有模态函数进行降噪;最后,利用Hilbert-Huang变换识别降噪后的各阶拱坝模态特征参数。通过拱坝室内模型试验验证了该方法识别模态参数的可靠性,并应用于某原型拱坝的实测振动响应降噪和模态特征提取中。该方法可避免传统原始信号先降噪带来的部分高阶模态信息丢失问题,有效降低了噪声对固有模态函数的影响,提高了高拱坝实时模态参数识别的阶次和精度。
A signal processing and mode feature extraction method for arch dam flood discharge vibration response based on empirical mode decom- position and wavelet de-noising of intrinsic mode functions was presented in this paper. Firstly, the signal with noise of the arch dam flood discharge was decomposed into a series of intrinsic mode function. Secondly, wavelet de-noising technology was used to reduce noise on the intrinsic mode function. Finally, the modal parameter was identified by Hilbert-Huang Transform. The reliability of this method was verified on the hydro-elastic arch dam experiment and was applied to the modal parameter identification and noise reduction of a prototype arch dam. This method avoids the problem of higher mode information lost because of the original signal noise reduction, reduces the impact of noise on the intrinsic mode functions effectively, and improves the order and accuracy of real-time modal parameter identification of high arch dam.
出处
《人民黄河》
CAS
北大核心
2012年第12期123-126,129,共5页
Yellow River
基金
国家自然科学基金资助项目(50909049)
江西省自然科学基金资助项目(2010GQC0119)
江西省教育厅科研基金资助项目(GJJ12030)
关键词
信号降噪
小波
HHT
参数识别
泄流
拱坝
noise reduction
wavelet
Hilbet-Huang Transform
modal parameter identification
flood discharge
arch dam
