水流荷载激励下，泄流结构模态识别的实测振动信号常受噪声干扰。以往EEMD算法有添加白噪声造成非标准IMF导致的模态分裂问题及IMF有噪声残余不能完整重构信号的完备性问题。而完备总体经验分解法(CEEMD)，通过在信号分解的每一层面添加特定高斯白噪声，利用分解后第一阶分量加总平均得到唯一余量计算固有模态函数，克服了EEMD的缺点。同时提出CEEMD与小波包阈值结合的组合降噪方法，运用到向家坝水弹性模型实测振动信号降噪中，验证了该组合方法降噪的有效性。为了提高带噪振动响应模态识别的精度，基于数据相关技术，利用Markov参数构造相关矩阵R，用该相关矩阵重构Hankel矩阵后SVD分解得到系统最小实现，即数据相关特征系统实现法(ERA/DC)。最后将文中提出的滤波降噪结合模态识别的整套方法，应用到锦屏一级拱坝的泄流实测振动响应中，得到了较好的应用效果。
Abstract
The vibration signal of flood discharge under water load excitation using for modal identification is often affected by noise. EEMD algorithm has the problem that caused by adding white noise, which leads to the non-standard IMF that causes the modal split and the incompletely reconstructed original signal on account of the residual noise. While Complete Ensemble Empirical Mode Decomposition (CEEMD), by adding the specific white noise to each stage of signal decomposition, uses the first component and adds the average to get the unique residual, which let the IMF overcome the drawbacks of EEMD. According to the record of the experiment which de-noised the vibration signal from Xiangjiaba hydroelastic model, the effectiveness of method based on CEEMD and wavelet packet transform has been proved. In order to improve the precision of modal identification with vibration response mixed noise, this paper, based on the data correlation technology, uses the Markov parameter structure correlation matrix R and SVD the Hankel matrix restricted by R to get minimum system realization, which is also called by Eigensystem Realization Algorithm With Data Correlation (ERA/DC). Finally, the filtering and mode identification method mentioned in the paper is applied to the vibration response analysis of Jinping arch dam, which obtains the good application effect.
关键词
泄流结构 /
滤波降噪 /
完备总体经验模态分解 /
小波包 /
模态识别 /
相关特征系统实现法
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Key words
flood discharge structure /
noise reduction /
CEEMD /
Wavelet packet /
Modal identification /
ERA/DC
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