| Acoustic emission(AE)is often used in the monitoring of rock failure and instability,and as an important means of nondestructive monitoring,it has been gradually extended to the monitoring of backfill stability.However,in the actual filling mining process,there is the phenomenon of joint bearing of backfill-rock combination.Because of the influence of mining operation and blasting and other factors,it is difficult to directly monitor the AE of rock or backfill,so it is necessary to interval the rock or backfill for AE monitoring.Therefore,compared with the direct monitoring of backfill and rock,it is more meaningful to study and analyze the AE characteristics and main differences in the process of compression failure of backfill-rock combination.Therefore,three kinds of standard cylinder specimens of cemented tailing backfill,sandstone and backfill-sandstone combination are prepared in this paper.The uniaxial compression AE tests are carried out respectively,and the mechanical parameters and AE parameters of each specimen during the failure process are obtained,and the waveform data are recorded.Firstly,the characteristics of AE events,ring count,energy and RA value in the process of compression failure of backfill,sandstone and composite body are analyzed.Then the distribution characteristics of the main frequency and amplitude of the three kinds of AE signals and the main differences of the main frequency amplitude signal mode are studied.After that BP neural network is designed to identify and classify the AE signal source of backfill and sandstone caused by compression failure of backfill-sandstone composite.At last,the change characteristics of the fractal dimension of AE under different stress levels of each specimen are studied in order to provide some basis for monitoring and prediction of AE of backfill,rock and backfill-rock composite material compression failure.The main conclusions are as follows:(1)For peak strength and modulus of elasticity,the sandstone specimen is the largest,the backfill-sandstone composite specimen is the second,and the backfill specimen is the smallest.The average peak strength of sandstone,backfill-sandstone combination and backfill is 52.971 MPa,20.550 MPa and 3.826 MPa respectively,and the average modulus of elasticity is 9.364 GPa,2.613 GPa and 0.625 GPa respectively.(2)The critical failure rate of backfill is mainly low AE event rate,low ring count rate and low energy rate;the critical failure rate of sandstone is mainly high event rate,high ring count rate and high energy rate;the critical failure rate of backfill side and sandstone side in composite body is mainly high event rate,high ring count rate and high energy rate,indicating the AE signal of composite body in critical failure It is mainly produced by sandstone.(3)The average value of correlation coefficient of AE event rate,ring count rate and energy rate of sandstone side and backfill side in the composite test piece is greater than 0.8,indicating that the AE signals on both sides have the same change trend,but the number and intensity of AE signals received on the sandstone side are more and stronger than those on the backfill side,indicating that the AE signals in the composite are mainly generated by the sandstone part.(4)The dominant frequency of P2 band(31.25-62.5kHz)on both sides of the backfill,sandstone and composite body is the largest,followed by P1 band(0-31.25kHz),and the sum of P1 and P2 bands accounts for more than 95% of the total dominant frequency.There are P3 frequency band(62.5-93.75kHz)and P9-P12 frequency band(250-375kHz)on both sides of the sandstone and the combination,but the backfill does not appear,which can be used as one of the criteria for identifying the AE signal source of sandstone in the combination.(5)When there are three signal modes of low frequency-middle amplitude,low frequency-high amplitude and high frequency-low amplitude on both sides of the composite test piece,it can be determined as the AE signal source of the sandstone part;when there is only one signal mode of low-frequency low amplitude on both sides of the composite test piece,and no other signal mode,it can be determined as the AE signal source of the backfill part.(6)The BP neural network is designed and trained by combining the AE signal of backfill and sandstone separately.It can identify and classify the AE signal source of backfill and sandstone caused by compression failure of f backfill-sandstone composite,and the recognition accuracy is 94%.At the same time,the AE sensor attached to the side of the backfill can receive the AE signal generated by the sandstone part,but it is still recommended that the effect of AE monitoring on the rock side should be better.(7)Near the peak failure,the AE RA value of each specimen increases sharply,the main frequency band of the AE signal increases,the AE amplitude increases rapidly,and the AE signals with low frequency-high amplitude and high frequency-low amplitude appear.The above characteristics can be used as important feature information of the main fracture precursor of backfill,sandstone and composite specimen.(8)The AE ring count and main frequency of the backfill,sandstone and the filling body side and sandstone side of the composite body have obvious fractal characteristics.Before the peak failure,the correlation dimension D value of the AE ring count and the main frequency of each specimen is rapidly reduced to a lower value,which can be used as the precursory characteristics of the failure of backfill,sandstone and composite specimens. |
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