The acoustic emission characteristics of rock specimens under uniaxial compression were investigated by means of AE technique and three dimensional acoustic emission technique was applied to observe the phase the fracture process of rock. Based on the characteristics of signals of Acoustic emission, the signals of AE were analyzed, denoised and reconstruction by means of the wavelet analysis method. The damage features of the time domain response signal are more obvious after being wavelet transformed. Using wavelet analysis to process AE signals then to identificate the position of the AE source will be more precise than the traditi AE (Acoustic Emission, as AE), refers to a natural phenomenon that materials of structures will release some of the strain energy in the form of elastic waves with internally generated deformation of injury inside it at the same time, in the role of external forces, internal forces or the temperature change [1,2,3]. Outside loading will cause small cracks of the rock and then, the rock will release some of the strain energy in the form of elastic waves, this is known as rock AE. Acoustic emission testing aims to find acoustic emission sources and related information as much as possible. Through the analysis of the detected AE signals, much information about the AE sources of the detected materials or the internal structure will be found. But the AE signals gathered in the process of AE test will be mixed with many "interference" or even deformed signals, due to AE's own characteristics and limitations of the existing technologies. Therefore, how to collect the exact signals from the noise is problem remained to be solved. Many scholars believe that wavelet analysis is a good method and tool for signal processing and analysis. Views vary greatly form scholars in different fields about how to choose the suitable wavelet basis and when choosing different wavelet basis of the same signal there will be totally different results. In this paper, satisfactory results have been proved to thanks to the Hyperion UItrasonic System made in ESG in Canada on the rock under the condition of Uniaxial loading, and the wavelet theory, which is used for processing the AE signals. Then the processed data will be used to locate the AE sources accurately. The results indicate that the AE signals processing technology based on wavelet analysis is a promising approach.

Wavelet Analysis

Wavelet analysis, also known as wavelet transform, is the latest achievement of the harmonic analysis and considered as a great breakthrough of the tools and methods. Wavelet analysis based on the signals processing and parallel move and telescopic of a function, is directly due to the Fourier transform, Gabor transform, short-time Fourier transform [4,5,6]. Since Wavelet analysis has the ability to express the partial characteristics of signals in the timedomain and frequency-domain at the same time.

This content is only available via PDF.
You can access this article if you purchase or spend a download.