Research of identification of acoustic emission signal of coal and rock

Abstract

In view of problem that it is difficult to identify acoustic emission signal of coal and rock burst under complicated noise environment, the paper proposed an identification method of acoustic emission signal of coal and rock based on wavelet packet and wavelet feature energy spectrum coefficient analysis. Useful acoustic emission signals are extracted by taking Symlets wavelet as wavelet basis function of acoustic emission signal of coal and rock and making denoising process with hybrid threshold algorithm. Then wavelet feature energy spectrum coefficient and wavelet packet eigenvector are obtained by using Matlab software to separately simulate wavelet packet decomposition for the useful acoustic emission signals and noise signals. Simulation results show that changing degree of each energy of eigenvector of the useful acoustic emission signals is bigger，while changing of energy of eigenvector of the noise signals is relatively stable, which can be used to identify acoustic emission signal of coal and rock.

Keywords

• coal and rock burst
• acoustic emission
• wavelet basis function
• denoising process
• wavelet packet decomposition
• wavelet feature energy spectrum coefficient