An improved filtering method based on EEMD and wavelet-threshold for modal parameter identification of hydraulic structure

被引:42
|
作者
Zhang, Yan [1 ]
Lian, Jijian [1 ]
Liu, Fang [1 ]
机构
[1] Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
Modal parameter identification; Noise reduction; Ambient excitation; White noise; Ensemble empirical mode decomposition; Wavelet threshold; HILBERT SPECTRUM; DECOMPOSITION; NOISE;
D O I
10.1016/j.ymssp.2015.06.020
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Modal parameter identification is a core issue in the health monitoring and damage detection of hydraulic structures. The parameters are mainly obtained from the measured vibrational response under ambient excitation. However, the response signal is mixed with noise and interference signals, which will cover the structure vibration information; therefore, the parameter cannot be identified. This paper proposes an improved filtering method based on an ensemble empirical mode decomposition (EEMD) and wavelet threshold method. A 'noise index' is presented to estimate the noise degree of the components decomposed by the EEMD, and this index is related to the wavelet threshold calculation. In addition, the improved filtering method combined with an eigensystem realization algorithm (ERA) and a singular entropy (SE) is applied to an operational modal identification of a roof overflow powerhouse with a bulb tubular unit. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:316 / 329
页数:14
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