Micro Failure Mechanism of Hard Rock Using Scanning Electron Microscope

Because signal of scanning electron microscope (SEM) is severely disturbed by voices and clutters on the condition of complicated mineral composition of hard rock, conventional filtering signal processing methods are difficult to meet the need for an accurate de-noising signal image processing. Combining the wavelet transformation theory and intelligent optimization algorithm, the intelligent reducing noise method of particle swarm optimization (PSO)-wavelet threshold is proposed, which effectively deals with the problem of signal noise. Rational threshold of coefficients of wavelet at different levels is obtained by using PSO algorithm in the global scope, and the intelligent optimization process of reducing the noise of SEM signal is proposed. The micro failure mechanism of hard rock under different temperatures are studied by the method. Result shows that the interference factors in the signals can be quickly removed on the basis of the de-noising method of intelligence wavelet transform. It reveals the main micro failure mechanism of hard rock.