引用本文:魏博文,钟紫蒙.基于改进小波阈值-EMD算法的高拱坝结构振动响应分析[J].水利水运工程学报,2019,(4):83-91
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基于改进小波阈值-EMD算法的高拱坝结构振动响应分析
魏博文1,2, 钟紫蒙2
1.南京水利科学研究院水文水资源与水利工程科学国家重点实验室,江苏南京;2.南昌大学建筑工程学院,江西南昌
摘要:
基于高拱坝泄流结构实测振动响应数据资料,针对泄流激励作用下不可避免混有各种噪声进而影响结构工作模态识别精度的问题,提出了一种基于改进的小波阈值-经验模态分解(EMD)联合算法的滤波降噪方法。以拱坝泄流结构实测振动响应资料为基础,利用改进的小波阈值算法滤除大部分高频白噪声,降低EMD分解的边界积累效应,进行EMD分解,通过去趋势波动分析(DFA)方法进一步滤除白噪声及低频水流噪声。工程实例分析结果表明,与小波分析、EMD方法相比,该方法具有更好的降噪效果,能精确滤除泄流结构实测振动响应信号中的低频水流噪声及白噪声,最大程度地保留信号中有效特征信息,并且为拱坝泄流结构在噪声干扰下提取有效信息提供了捷径,为坝体结构的安全监控打下了基础。
关键词:  高拱坝  流激振动  滤波降噪  小波阈值分析
DOI:
分类号:TV37; TV31
基金项目:国家重点实验室开放基金资助项目(2017491511); 国家自然科学基金资助项目(51669013,51779115,51869011)
Flow-induced vibration response analysis of high arch dam discharge structure based on improved wavelet threshold-EMD algorithm
WEI Bowen1,2, ZHONG Zimeng2
1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing;2.College of Civil Engineering and Architecture, Nanchang University, Nanchang
Abstract:
Based on the measured vibration response data of the high arch dam discharge structure, aiming at the problems of various mixed noises under the action of discharge excitation, which will affect the accuracy of the structural working mode identification, a new filtering and de-noising method based on the improved wavelet threshold-empirical mode decomposition (EMD) joint algorithm is proposed in this paper. According to the measured vibration response data of the arch dam, the improved wavelet threshold is used to filter out most of the high frequency white noise, and reduce the boundary accumulation effect of EMD decomposition. After EMD decomposition, a detrended fluctuation analysis method (DFA) is utilized to further filter the white noise and the low-frequency current noise. The analysis results of engineering examples show that this method has better noise reduction effect compared with the wavelet analysis and the EMD method. It can accurately filter the low-frequency water flow noise and the white noise in the measured vibration response signal of the discharge structure. At the same time, the effective characteristic information in the signal is retained to the greatest extent. This method has provided convenience for extracting effective information of the arch dam discharge structure under noise interference and laid a foundation for the safety monitoring of the dam body structures.
Key words:  high arch dam  flow-induced vibration  filtering noise reduction  wavelet threshold analysis
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