Micro-seismic Data Compression And Reconstruction Based On DCS

Precision mining of coal is the only way for human society to develop in the future.With the realization of Mine Internet of Things application system in the mine,the use of large area,distributed and networked intelligent nodes provide the possibility of realizing ubiquitous perception of mine safety.Under the background of mine distributed monitoring,a large number of micro-seismic sensor nodes are distributed in the underground mine to achieve safety monitoring,so sensor nodes need deal with a large amount of data.The main content of this thesis is how to compress a large number of data brought by the micro-seismic sensor nodes and how to reconstruct the compressed data.In this thesis,the basic principle of distributed micro-seismic monitoring system is analyzed,and the design and implementation process of micro-seismic nodes are given.Aiming at the problem of large amount of micro-seismic data in the distributed micro-seismic monitoring environment,the distributed compressed sensing theory is introduced to compress the micro-seismic data.In order to reduce the amount of data transmission,an improved reconstruction algorithm is proposed.Firstly,the characteristics of the Mine Internet of Things and the advantages of applying the distributed compressed sensing theory to the mine are analyzed,which makes the distributed compressed sensing especially suitable in the resource-limited mine networking.According to the premise of distributed compressed sensing theory is that the signal is sparse,with micro-seismic signal as the research object,the sparsity analysis is carried out by using the FFT base.The results show that the micro-seismic signals are sparse in the frequency domain.Then,according to the distributed compressed sensing is based on the correlation between signals,the spatial correlation of the nodes is analyzed under the simulated distributed scene,and the coding and compression process are analyzed.Since most of the existing reconstruction algorithms are based on the sparsity of the signal,on the basis of the generalized orthogonal matching pursuit algorithm and the sparse adaptive matching pursuit algorithm,an improved distributed sparse adaptive orthogonal matching pursuit reconstruction algorithm is proposed and the performance of the improved algorithm is analyzed.Based on the MATLAB simulation platform,the improved algorithm is used to reconstruct the distributed micro-seismic signal after sparse measurement.The simulation results show that thealgorithm can effectively reconstruct the original micro-seismic signal under the premise of reducing the computational complexity.