针对目前滚动轴承振动信号频带越来越宽,依据传统香农-内奎斯特采样定理进行数据采集时,将会得到巨量振动数据,对存储、传输和处理带来困难的问题,提出了一种滚动轴承振动信号的数据压缩采集方法。首先分析了振动信号在正交字典傅里叶基上的近似稀疏性,即可压缩性;然后融入振动信号在傅里叶基上稀疏性的结构信息,得到其优化的测量矩阵并进行压缩测量;最后基于压缩测量值采用正交匹配追踪算法对原始振动信号进行重构。通过仿真试验,结果表明,该方法既可以得到较高的信号压缩比又有着精确的信号重构性能,在不丢失振动信息的情况下,大大减少了原始振动数据量。
Abstract
Aiming at the band of rolling bearing vibration signals getting wider, based on the traditional Shannon-Nyquist sampling theorem for data collection, it will get a huge amount of data and produce difficult problems of storage, transmission and processing, we propose a data compression and acquisition method. Firstly, analyzed the sparsity(also called compressibility) of the vibration signal based on orthogonal dictionary Fourier domain; then integrated sparse structure information of the vibration signal into the design of measurement matrix and got its optimized measurement matrix and measured; Finally, based on the compression measurements used orthogonal matching pursuit algorithm to reconstruct the original vibration signal. Through simulation experiments, the results show that the proposed method can get a higher signal compression ratio and has precise signal reconstruction performance, in the case of without losing vibration information, greatly reducing the original amount of vibration data.
关键词
滚动轴承 /
振动信号 /
压缩测量 /
测量矩阵 /
正交字典
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Key words
the rolling bearing /
vibration signal /
compressed sensing /
measurement matrix;orth-ogonal dictionary
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参考文献
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脚注
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