基于交叉证认的EMD小波滤波在大桥动态监测去噪中的应用
发布时间：2019-05-23 13:52
【摘要】：在大桥动态位移监测中,为了更好地滤除噪声,提出了一种改进的交叉证认EMD小波滤波方法。即先用EMD对信号进行分解,再用交叉证认方法自适应地算出噪声主导分量,最后用小波阈值对噪声主导分量进行滤波;其中阈值函数选取极为关键,给出了一种新的阈值函数计算方法;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,提取大桥振动信息,是一种高效的去噪方法。
[Abstract]:In order to filter noise better in bridge dynamic displacement monitoring, an improved cross-identification EMD wavelet filtering method is proposed. That is, the signal is decomposed by EMD, then the dominant component of noise is calculated adaptively by cross recognition method, and finally, the dominant component of noise is filtered by wavelet threshold. Among them, the selection of threshold function is very important, and a new calculation method of threshold function is given. finally, the signal reconstruction is carried out. The example analysis shows that this method can filter the noise more effectively and extract the vibration information of the bridge, and it is an efficient denoising method.
【作者单位】： 宿迁学院建筑工程学院;南京工业大学土木工程学院;
【基金】：国家自然科学基金项目(51078080) 江苏省高校自然科学研究项目资助(13KJB420004) 江苏省科技支撑(工业)项目(BE2014026)
【分类号】：U446
本文编号：2483950
[Abstract]:In order to filter noise better in bridge dynamic displacement monitoring, an improved cross-identification EMD wavelet filtering method is proposed. That is, the signal is decomposed by EMD, then the dominant component of noise is calculated adaptively by cross recognition method, and finally, the dominant component of noise is filtered by wavelet threshold. Among them, the selection of threshold function is very important, and a new calculation method of threshold function is given. finally, the signal reconstruction is carried out. The example analysis shows that this method can filter the noise more effectively and extract the vibration information of the bridge, and it is an efficient denoising method.
【作者单位】： 宿迁学院建筑工程学院;南京工业大学土木工程学院;
【基金】：国家自然科学基金项目(51078080) 江苏省高校自然科学研究项目资助(13KJB420004) 江苏省科技支撑(工业)项目(BE2014026)
【分类号】：U446
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