基于小波阈值去噪与EMD分解方法提取润扬大桥振动信息

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摘要在以润扬大桥为例的特大型桥梁动态振动监测中，数据量大且复杂，为了更好地滤除噪声获取真实振动信息，提出了一种小波去噪与EMD分解融合的方法。即先用小波方法对信号进行分解，再用本文改进的阈值函数进行滤波，目的主要是滤除白噪声；然后再对小波阈值去噪后的信号进行EMD分解，对分解后的信号进一步频谱滤波，最后进行信号重构。实例分析表明，该方法能够更有效地滤除噪声而提取大桥振动信息，是一种高效的去噪方法。

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	余腾1
	胡伍生2
	吴杰1
	李海锋3
	乔燕1

关键词 ：小波, 阈值函数, EMD分解, 桥梁振动, 去噪

Abstract：The data of dynamic vibration monitoring of the Runyang bridge, a large-span bridge, are large and complex, In order to better filter out noise and obtain real vibration information, a method of wavelet denoising and EMD decomposition was proposed.At first the signal was decomposed with the wavelet method, and then noise was filtered out with an improved threshold function.The signal was decomposed after the wavelet threshold de-noising using the EMD method.Finally the signal was refactored.Example analysis shows that the method can filter out noise more effectively and extract the bridge vibration information.

Key words： wavelet threshold function EMD decomposition bridge vibration de-noising

收稿日期: 2017-12-18 出版日期: 2019-06-15

引用本文:

余腾1,胡伍生2,吴杰1,李海锋3,乔燕1. 基于小波阈值去噪与EMD分解方法提取润扬大桥振动信息[J]. 振动与冲击, 2019, 38(12): 264-270.
YU Teng1, HU Wusheng2, WU Jie1, LI Haifeng3, QIAO Yan1. Extraction of Runyang bridge vibration information based on a fusion method of wavelet threshold denoising and EMD decomposition. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(12): 264-270.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I12/264

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