Study On Characterisics Of Kaiser Signal Of Acoustic Emission In Rock

The characteristic parameter analysis method to determine Kaiser point of rock acoustic emission(AE) in measuring initial stress is widely adopted, it depends on recording some parameters such as ring down count rate, energy count rate, ring down accumulate number and so on, then confirm the point which the parameter obviously increases as Kaiser point according to relationship between parameter and time.When these parameters change prominently in Kaiser point, it's easier to judge, but when these parameters do not change very prominently in Kaiser point, it's often difficult to judge accurately. Moreover the measure precision and dependability lack the systematicly and deeply studying too, especially the parameter analysis method which was used to comfirm the Kaiser point, it can't utilize all the information of rock AE and can't carry on the research of waveform characteristic of AE signal. The development of AE in measuring initial stress is limited due to above problems, it made the mechanism research of rock AE difficult to be developed for a long time, it is also one of the most important reasons why the rock AE technology theoretical research lags behind the project reality.Based on the AE tests of sandstone specimens under uniaxial compression, Kaiser point is determined by parameter method according to the principal of Kaiser effect and AE signal frequency distribution regularity is obtained by means of spectrum analysis, and the signal noise reduction method for AE at Kaiser point is presented basing on wavelet analysis.The results show that wavelet analysis is an effective way in noise reduction and signal processing of AE signal.Then, wavelet packet analysis method is used to research energy distribution of AE signals. Regularity rules of energy distributions for different frequency bands are obtained. Results show that the energy percentage of dominant frequency band at Kaiser point is significantly higher than other points.This characteristic can be used as a new criterion to determine Kaiser point.At last, relevant fractal dimensions of AE process are obtained using G-P algorithm. Results show that the AE process is of obvious fractal characteristics, and the minimum value of relevant fractal dimension is at Kaiser point. The conclusion can be used to identify the characteristics at Kaiser point by waveform analysis.