Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 68-69, Issue -, Pages 316-329Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2015.06.020
Keywords
Modal parameter identification; Noise reduction; Ambient excitation; White noise; Ensemble empirical mode decomposition; Wavelet threshold
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Funding
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China [51321065]
- National Natural Science Foundation of China [51379140, 51209158, 51379177]
- State Key Laboratory of Hydraulic Engineering Simulation and Safety of China [2011DA105367]
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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.
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