机械振动信号分块自适应压缩感知算法
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军械工程学院车辆与电气工程系石家庄050003

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TN911TH393.1

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家自然科学基金(E51305454)项目资助


Adaptive blocked compressed sensing algorithm for the machinery vibration signal
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Department of Vehicle and Electrical Engineering, Ordnance Engineering College, Shijiazhuang 050003, China

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    摘要:

    为提高振动信号分块压缩感知过程中的信号重构效果,提出了机械振动信号的自适应分块压缩感知算法。首先将信号分割,构造信号矩阵,并利用KSVD构造与信号矩阵相适应的冗余字典;然后根据不同信号块在冗余字典下匹配追踪系数的衰减速度,定义不同信号块的复杂度权值;最后以复杂度权值为依据,制定自适应的压缩感知采样策略,在保证振动信号的整体采样率不变的同时,自适应分配不同信号块的观测数目。将该算法应用于机械振动信号压缩感知,与传统压缩感知算法以及其他自适应压缩感知算法相比,信号重构的精度得到提高。

    Abstract:

    In order to improve the reconstruction effect of the vibration signal in the process of blocked compressed sensing, an adaptive compressed sensing algorithm is proposed. Firstly, the signal is transformed into matrix by devising the signal into blocks, and the redundant diction is constructed by KSVD adaptively. Secondly, the complexity weight is defined by the attenuation rate, which comes from the sparse coefficients under the redundant dictionary. At last, based on the complexity weight, the observation number of different signal blocks is allotted adaptively in the guarantee of the same total sampling rate. While this algorithm is applied in the compressed sensing of machinery vibration signal, the reconstruction precision is higher than other compressed sensing algorithms.

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王强,张培林,王怀光,陈彦龙.机械振动信号分块自适应压缩感知算法[J].仪器仪表学报,2017,38(2):312-319

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  • 在线发布日期: 2017-07-20
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