Journal
WATER
Volume 14, Issue 22, Pages -Publisher
MDPI
DOI: 10.3390/w14223735
Keywords
high arch dam; signal processing; working modal identification; vibration under discharge excitation; noise reduction
Categories
Funding
- National Natural Science Foundation of China [52169025, 51779115, 51869011]
- Science and Technology Project of the Jiangxi Provincial Department of Water Resources [202224ZDKT21, 202223YBKT43]
- Jiangxi Provincial Department of Education [GJJ206001]
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This study proposes an improved modal threshold identification method for high arch dam discharge structures, aiming to filter noise and reduce modal aliasing for better identification accuracy. The method utilizes wavelet threshold-empirical mode decomposition and random decrement technique to process vibration response data and obtain the characteristic parameters of the structure system. Engineering examples demonstrate the effectiveness of this method.
Prototype vibration response data of high arch dam discharge structures inevitably mix various noises under the discharge excitation, which adversely affects the accuracy of the working modal identification of the structure. To effectively filter noise and reduce modal aliasing for better identification accuracy, this study proposes an improved modal threshold identification method based on an improved wavelet threshold-empirical mode decomposition (EMD) and random decrement technique (RDT) algorithm for high arch dam discharge structures. On the basis of the measured vibration response data of the dam, the wavelet threshold is adopted to filter out most of the high-frequency white noise and to reduce the boundary accumulation effect of EMD decomposition. Detrended fluctuation analysis (DFA) is utilized to filter white noise and low-frequency flow noise after EMD decomposition. The natural frequency and damping ratio of the structure system are obtained by the improved RDT algorithm. The engineering examples show that the proposed method can accurately filter the measured vibration response signal noise of the discharge structure, retain the signal characteristic information, improve the accuracy of working modal recognition of the structural vibration response, avoid the complex ordering process of the system, and ease the working modal parameter identification of high arch dam discharge structures. This method can be applied to the mode identification of other large structures, as well.
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