When the compressed sampling theory is applied in mechanical vibration signal acquisition,the existing random measurement matrix occupies a large storage space,the process of compression acquisition and reconstruction need to handle a large amount of computation problems.Here,Gaussian distribution cycle measurement matrix (GCMM) was proposed by integrating advantages of Gaussian sequences and the circulant theory.Firstly,the first row elements of GCMM were generated with a row vector obeying Gaussian distribution,all the remaining row vectors were generated through circular shift.Then part elements of all rows except the 1st row were taken out,each element was multiplied by the same random number or different ones,they were put back at the original position.Finally,the compressed measurement values of mechanical vibration signals obtained based on GCMM were used to reconstruct the original vibrating signals using the orthogonal matching pursuit algorithm.All the elements of GCMM satisfied he randomness requirements of the measurement matrix,the intrinsic certainty of the circulant principle also met the requirement of hardware implementation of the measurement matrix.Simulation results showed that the perception performance of GCMM is similar to that of Gaussian matrix,but the required storage space of GCMM is less than that of Gaussian matrix.
Key words
vibration signal /
compressed sampling /
Gauss sequence /
cycle principle /
structured random measurement matrix
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