CN105334266A - Rock acoustic emission source positioning method - Google Patents

Abstract

The invention discloses a rock acoustic emission source positioning method and belongs to the technical field of rock acoustic emission source positioning. According to the method, a granite standard cuboid sample is prepared; N acoustic emission sensors not located on the same plane are placed on the periphery of the cuboid sample, and vaseline is smeared between the sensors and the sample; the acoustic emission sensors are used for receiving acoustic emission signals generated inside the sample due to damage; acoustic emission waveforms received by all the acoustic emission sensors are subjected to wavelet denoising processing and wavelet decomposition; four different sensors and four sub-band signals with the same dominant frequency are selected according to the signals received from the sensors; the four sub-band signals are subjected to all-phase spectral analysis, phases of the four sub-band signals are obtained respectively, time difference measurement is conducted through a phase difference method, and the time difference between the acoustic emission signals received by the four sensors is obtained. Coordinates of an acoustic emission source K are obtained by means of acoustic emission space positioning by the adoption of a least square method according to position coordinates of the four sensors through the time difference, determined in the sixth step, between the acoustic emission signals received by the four sensors.

Description

A kind of Acoustic Emission of Rock source electricity method

Technical field

The invention belongs to Acoustic Emission of Rock source electricity technical field, especially relevant with a kind of Acoustic Emission of Rock source electricity method based on wavelet transformation and all phase spectrum analysis.

Background technology

When rock material is by external force or endogenetic process, due to itself elastic deformation, Crack Extension, cause the Elastic wave phenomenon that in hard brittle material, local sends because of the quick release of energy, be called acoustic emission (acousticemission, AE).Acoustic emission is a good tool of research hard brittle material UNSTABLE FAILURE evolutionary process, can continuously, the generation of hard brittle material internal tiny crack and expansion under monitors load effect in real time, and the location realized its failure position, this is the feature that other any test methods do not have, and has been widely used in the Failure Mechanism research of breaking of the material such as study of rocks, concrete.Acoustie emission event location can not only obtain the activity characteristic of different its acoustic emission of load phase of rock, simultaneously can reflect that in whole loading procedure, rock interior micro-crack breeds, germinate, expand, nucleation and through three dimensions evolutionary process, this is undoubtedly very significant work to understanding rock burst Failure Mechanism further.Therefore, acoustie emission event location is the key of study of rocks ruptured stage, and the research of acoustie emission event location algorithm just becomes top priority.Present stage acoustic emission source location installs multiple sensor on rock sample surface, realizes acoustic emission source location by the mistiming obtaining acoustic emission signal.Current localization method divides by Acoustic Emission location principle: regional mapping method and time-of-arrival loaction.Regional mapping method judges the region residing for acoustic emission source according to the number of probes of acoustic emission signal and relative time error sequential, is a kind of fast and convenient and rough method, has certain uncertainty.In order to obtain unique anchor point, the location technology of acoustic current emissive source mostly adopts positioning using TDOA.For time difference positioning method, accurately determine that each sensor reception acoustic emission signal mistiming seems particularly important, it misses extent and directly affects positioning precision.Because acoustic emission signal velocity of propagation in rock material is very fast, therefore, new more accurate time delay decision method must be adopted, accurately determine the time difference of the acoustic emission signal that time of arrival of acoustic emission wave or each sensor receive.

Summary of the invention

For the problems referred to above, object of the present invention provides a kind of Acoustic Emission of Rock source electricity method based on wavelet transformation and all phase spectrum analysis can carrying out the higher locus prediction of precision to acoustic emission source.

For this reason, the present invention is by the following technical solutions: a kind of Acoustic Emission of Rock source electricity method, is characterized in that, comprise the following steps:

Step 1: prepare grouan standard rectangular parallelepiped sample;

Step 2: place at the periphery of rectangular parallelepiped sample and be not N number ofly in conplane calibrate AE sensor, be coated with vaseline between sensor and sample, strengthen coupling therebetween;

Step 3: utilize calibrate AE sensor to receive the acoustic emission signal of sample internal injury generation;

Step 4: Wavelet Denoising Method process and wavelet decomposition are carried out to the acoustic emission waveform that each calibrate AE sensor receives;

Step 5: pick out from 4 different sensors and identical 4 subband signals of dominant frequency from the signal that sensor receives, for subsequent analysis provides effective acoustic emission signal;

Step 6: carry out all phase spectrum analysis to 4 subband signals in step 5, ask for the phase place of 4 subband signals respectively, utilize phase difference method to carry out time difference measurements, asks for the mistiming that 4 sensors receive acoustic emission signal.

Step 7: the mistiming being received acoustic emission signal by 4 sensors of the determination in step 6, adopts least square method to carry out the coordinate of acoustic emission space orientation acquisition acoustic emission source K point by the position coordinates of four sensors.

As to technique scheme supplement and perfect, the present invention also comprises following technical characteristic.

N in described step 2 is more than or equal to 4.

The acoustic emission signal that the internal injury of described step 3 produces is obtained by disconnected plumbous experiment.

The concrete grammar of described step 5: Fast Fourier Transform (FFT) is carried out to layer signal each after wavelet decomposition, obtain 2-d spectrum figure, the frequency that in 2-d spectrum figure, maximum amplitude is corresponding is the dominant frequency of this acoustic emission signal; Utilize the method to get the dominant frequency value of each layer signal, the subband signal dominant frequency after each sensor of comparative analysis decomposes, therefrom find out immediate 4 subband signals of dominant frequency, 4 subband signals are respectively from 4 different sensors.

Use the present invention can reach following beneficial effect: 1, the present invention carries out the estimation of acoustic emission signal precise time difference by means of wavelet decomposition and all phase spectrum analysis in conjunction with phase difference method, can reduce positioning error; 2, the mean absolute error of the disconnected plumbous location test positioning result of the method three-dimensional reduces 3mm than U.S. PCI-2 type acoustic emission instrument positioning result; 3, in the method, all phase spectrum analysis can realize by FFT module, and computing velocity is very fast, is beneficial to hardware implementing.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention;

Fig. 2 is that in the disconnected plumbous experiment of the present invention, sensor is arranged and coordinate position schematic diagram;

Fig. 3 is the signal that receives of the disconnected plumbous experiment of coordinate points of the present invention (50,45,25) 8 sensors and wavelet decomposition signal spectrum figure thereof;

Fig. 4 is subband signal dominant frequency tabular drawing after the signal that receives of the disconnected plumbous experiment of coordinate points of the present invention (50,45,25) 8 sensors and wavelet decomposition;

Fig. 5 is the present invention's 10 disconnected plumbous experiment all phase phase difference method acoustic emission AT speed test result tabular drawings;

Fig. 6 tests positioning result and error statistics tabular drawing for the present invention is based on 10 disconnected lead measured by wavelet decomposition and all phase spectrum analysis;

Fig. 7 is positioning result and the error statistics tabular drawing of 10 the disconnected plumbous experiments of U.S. PCI – 2 type acoustic emission test;

Fig. 8 is all phase phase difference method of the present invention location and U.S. PCI-2 type acoustic emission instrument positioning result absolute error comparison diagram.

Embodiment

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in detail.

Embodiment: as shown in Fig. 1 ~ Fig. 8, the present invention includes following steps:

Step 1: prepare grouan standard rectangular parallelepiped sample; Select grouan to be test specimen, grouan takes from Laizhou, Shandong mining area, is prepared into the standard rectangular parallelepiped sample of 50mm × 50mm × 100mm.

8 R6 α sensor calibrate AE sensors 2 are attached on the rectangular parallelepiped sample 1 prepared, are coated with vaseline 3 between sensor and sample by step 2: as shown in Figure 2, strengthen coupling therebetween.The coordinate of 8 sensors arranged in the present invention is respectively A1 (25,80,0), A2 (25,20,0), A3 (50,80,25), A4 (50,20,25), A5 (25,80,50), A6 (25,20,50), A7 (0,80,25), A8 (0,20,25), unit is mm.

Step 3: determine that on rectangular parallelepiped sample disconnected plumbous experiment was carried out in position, utilize calibrate AE sensor to receive the acoustic emission signal of sample internal injury generation;

Done 10 disconnected lead tests altogether, disconnected plumbous coordinate points is respectively (25,60,50), (25,45,50), (50,60,25), (50,45,25), (25,60,0), (25,45,0), (0,60,25), (0,45,25), (25,100,35), (25,100,15).

Step 4: Wavelet Denoising Method process and wavelet decomposition are carried out to the acoustic emission waveform that each calibrate AE sensor receives; According to the experience selecting acoustic emission signal wavelet basis in the past, using Daubechies small echo as wavelet basis, select Heursure mixed threshold rule and soft-threshold function, denoising and 5 layers of resolution process are carried out to the acoustic emission signal obtained.

Step 5: as shown in Figure 3 and Figure 4, picks out from 4 different sensors and identical 4 subband signals of dominant frequency in the signal that multisensor of comforming receives, for subsequent analysis provides effective acoustic emission signal; Carry out disconnected lead test result for example with coordinate points (50,45,25), the process of preferred acoustic emission signal is described.Fast Fourier transform analysis is carried out to layer signal each after wavelet decomposition, ask for the dominant frequency value of each layer signal, as shown in Figure 4, can find out that the subband signal frequency of signal after wavelet decomposition that 2,5,7 and 8 these 4 sensors receive is identical, be 43.01kHz, and the subband signal dominant frequency after original Received signal strength dominant frequency Sum decomposition is consistent, therefore subsequent analysis coordinate points (50,45,25), during disconnected lead test result, the 5th of 2,5,7 and 8 these 4 sensors the layer of detail signal can be selected to carry out all phase phase difference calculating.

Step 6: as shown in Figure 5, all phase spectrum analysis is carried out to 4 subband signals in step 5, find the phase place that 4 subband signal dominant frequency are corresponding respectively, utilize phase difference method to carry out time difference measurements, ask for the mistiming of 4 sensor reception acoustic emission signals in disconnected lead test.

Step 7: as shown in Figure 6, adopts least square method to carry out acoustic emission space orientation.

Based on determining in step 6 that 4 sensors receive the mistiming of acoustic emission signal, can choose four sensors and solve to set up equation, the position coordinates of four sensors is respectively: (x ₁, y ₁, z ₁), (x ₂, y ₂, z ₂), (x ₃, y ₃, z ₃), (x ₄, y ₄, z ₄), and suppose that K point is acoustic emission source, coordinate is (x, y, z), then obtain four equations as follows:

$\left\{\begin{array}{c}{\mathrm{V\Δ}}_{12}=\sqrt{{(x-x_2)}^2+{(y-y_2)}^2+{(z-z_2)}^2}-\sqrt{{(x-x_1)}^2+{(y-y_1)}^2+{(z-z_1)}^2}\\ {\mathrm{V\Δ}}_{23}=\sqrt{{(x-x_3)}^2+{(y-y_3)}^2+{(z-z_3)}^2}-\sqrt{{(x-x_2)}^2+{(y-y_2)}^2+{(z-z_2)}^2}\\ {\mathrm{V\Δ}}_{34}=\sqrt{{(x-x_4)}^2+{(y-y_4)}^2+{(z-z_4)}^2}-\sqrt{{(x-x_3)}^2+{(y-y_3)}^2+{(z-z_3)}^2}\\ {\mathrm{V\Δ}}_{41}=\sqrt{{(x-x_1)}^2+{(y-y_1)}^2+{(z-z_1)}^2}-\sqrt{{(x-x_4)}^2+{(y-y_4)}^2+{(z-z_4)}^2}\end{array}\right.$

In formula, V is velocity of wave, Δ _ijfor acoustic emission signal is from the mistiming of K point arrival i-th, a j sensor, the P wave-wave speed that test records in granite sample is 3128.0235m/s, solves the coordinate that above-mentioned system of equations can obtain acoustic emission source K point, determines the positioning result of 10 disconnected plumbous experiments.

Step 8: as shown in Figure 7 and Figure 8, the positioning result of comparative analysis this method and U.S. PCI – 2 Acoustic radiating instrument, the size of the two kinds of method absolute errors that can visually see, all phase phase difference method location absolute error entirety is less than U.S. PCI-2 type acoustic emission instrument location absolute error, and mean absolute error reduces about 3mm.

The method of carrying out acoustic emission source location is combined with all phase spectrum analysis as mentioned above based on wavelet decomposition, wherein:

Theory deduction single-frequency complex exponential is believed number whole phase FFT frequency spectrum.The source of all phase data, can think for the x of in time series (0), only there is N number of N dimensional vector comprising this point:

x ₀＝[x(0)x(1)…x(N-1)] ^T

x ₁＝[x(-1)x(0)…x(N-2)] ^T

…………………

x _N-1＝[x(-N+1)x(-N+2)…x(0)] ^T

Each vector is carried out ring shift, sample point x (0) is moved on to first place, then obtain other N number of N dimensional vector:

x' ₀＝[x(0)x(1)…x(N-1)] ^T

x ₁'＝[x(0)x(1)…x(-1)] ^T

…………………

x' _N-1＝[x(0)x(-N+1)…x(-1)] ^T

According to the Shifting Property of discrete Fourier transform (DFT), the discrete Fourier transform (DFT) X ' of above formula _ithe discrete Fourier transform (DFT) X of (k) and above formula _ivery clear and definite relation is had between (k):

$X_i^{\′}\left(k\right)=X_i\left(k\right)e^{j\frac{2\mathrm{\π}ki}{N}}$

All phase frequency spectrum is by X ' _ik () sum forms, so all phase result of spectrum analysis is as follows:

$\begin{array}{c}{X}_{AP}\left(k\right)\\ =\frac{1}{N}\underset{i=0}{\overset{N-1}{\mathrm{\Σ}}}{X}_i^{\′}\left(k\right)=\frac{1}{N}\underset{i=0}{\overset{N-1}{\mathrm{\Σ}}}{X}_i\left(k\right)e^{j\frac{2\mathrm{\π}ki}{N}}\\ =\frac{1}{N^2}{e}^{{\mathrm{j\θ}}_0}\underset{i=0}{\overset{N-1}{\mathrm{\Σ}}}\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}x(n-i)e^{-j\frac{2\mathrm{\π}}{N}kn}{e}^{j\frac{2\mathrm{\π}ki}{N}}\\ =\frac{1}{N^2}{e}^{{\mathrm{j\θ}}_0}\underset{i=0}{\overset{N-1}{\mathrm{\Σ}}}{e}^{-j2\mathrm{\π}(m-k)i/N}\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{e}^{j\frac{2\mathrm{\π}(m-k)n}{N}}\\ =\frac{1}{N^2}{e}^{{\mathrm{j\θ}}_0}\frac{e^{j\mathrm{\π}(m-k)}-e^{-j\mathrm{\π}(m-k)}}{e^{j\mathrm{\π}(m-k)/N}-e^{-j\mathrm{\π}(m-k)/N}}\frac{e^{-j\mathrm{\π}(m-k)}-e^{j\mathrm{\π}(m-k)}}{e^{-j\mathrm{\π}(m-k)/N}-e^{-j\mathrm{\π}(m-k)/N}}\\ =\frac{1}{N^2}{e}^{{\mathrm{j\θ}}_0}\frac{{\sin }^2\[\mathrm{\π}(m-k)\]}{{\sin }^2\[\mathrm{\π}(m-k)/N\]}\end{array}$

And the phase value of whole phase FFT spectrum is θ ₀, the notional phase value of sampling point x (0) namely, this value and frequency departure value m-k have nothing to do, and that is whole phase FFT has phase invariance.The phase place of 4 subband signals is asked for by said method.

Because the phase place of sampling point in the middle of what during all phase spectrum analysis, the phase place at main spectral line place was corresponding is Received signal strength, thus the mistiming that can arrive in the hope of sampling point in the middle of two-way sensor Received signal strength position.If i-th sensor is at moment t _ireceive sampling point in the middle of signal, the phase place of its correspondence is:

In like manner, if a jth sensor is at moment t _jreceive sampling point in the middle of signal, the phase place of its correspondence is:

with the phase place can obtaining main spectral line by carrying out all phase spectrum analysis to two-way sensor Received signal strength obtains.In formula for initial phase, f _cmain spectral line frequency, the frequency that namely peak point is corresponding, two signal phase differences,

Can time delay be tried to achieve:

I-th and j sensor moment t can be determined by above formula _ireceive the mistiming Δ of same signal _ji.

Experimentally record longitudinal wave velocity, set up system of equations, adopt least square method to carry out acoustic emission space orientation.

In isotropic medium, set up suitable coordinate, theoretical minimum needs to set up 3 equations just can obtain acoustic emission source position coordinates, but when equation can reduce mushing error more than when 3, thus the acoustic emission source coordinate calculated is more accurate.Can choose four sensors to solve to set up equation, the position coordinates of four sensors is respectively: (x ₁, y ₁, z ₁), (x ₂, y ₂, z ₂), (x ₃, y ₃, z ₃), (x ₄, y ₄, z ₄), and suppose that K point is acoustic emission source, coordinate is (x, y, z), then obtain four equations as follows:

$\left\{\begin{array}{c}{\mathrm{V\Δ}}_{12}=\sqrt{{(x-x_2)}^2+{(y-y_2)}^2+{(z-z_2)}^2}-\sqrt{{(x-x_1)}^2+{(y-y_1)}^2+{(z-z_1)}^2}\\ {\mathrm{V\Δ}}_{23}=\sqrt{{(x-x_3)}^2+{(y-y_3)}^2+{(z-z_3)}^2}-\sqrt{{(x-x_2)}^2+{(y-y_2)}^2+{(z-z_2)}^2}\\ {\mathrm{V\Δ}}_{34}=\sqrt{{(x-x_4)}^2+{(y-y_4)}^2+{(z-z_4)}^2}-\sqrt{{(x-x_3)}^2+{(y-y_3)}^2+{(z-z_3)}^2}\\ {\mathrm{V\Δ}}_{41}=\sqrt{{(x-x_1)}^2+{(y-y_1)}^2+{(z-z_1)}^2}-\sqrt{{(x-x_4)}^2+{(y-y_4)}^2+{(z-z_4)}^2}\end{array}\right.$

In formula, V is velocity of wave, can record by experiment; Δ _ijfor acoustic emission signal is from the mistiming of K point arrival i-th sensor and a jth sensor, solve the coordinate that above-mentioned system of equations can obtain acoustic emission source K point.

The method of carrying out acoustic emission source location is combined with all phase spectrum analysis as mentioned above based on wavelet decomposition, wherein: according to the experience selecting acoustic emission signal wavelet basis in the past, using Daubechies small echo as wavelet basis, select Heursure mixed threshold rule and soft-threshold function, denoising and 5 layers of resolution process are carried out to the acoustic emission signal obtained.

More than show and describe ultimate principle of the present invention and principal character and advantage of the present invention.The technician of the industry should understand; the present invention is not restricted to the described embodiments; what describe in above-described embodiment and instructions just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements all fall in the claimed scope of the invention.Application claims protection domain is defined by appending claims and equivalent thereof.

Claims (4)

1. an Acoustic Emission of Rock source electricity method, is characterized in that, comprises the following steps:

Step 1: prepare grouan standard rectangular parallelepiped sample;

Step 2: place at the periphery of rectangular parallelepiped sample and be not N number ofly in conplane calibrate AE sensor, be coated with vaseline between sensor and sample;

Step 3: utilize calibrate AE sensor to receive the acoustic emission signal of sample internal injury generation;

Step 4: Wavelet Denoising Method process and wavelet decomposition are carried out to the acoustic emission waveform that each calibrate AE sensor receives;

Step 5: pick out from 4 different sensors and identical 4 subband signals of dominant frequency from the signal that sensor receives;

Step 6: carry out all phase spectrum analysis to 4 subband signals in step 5, ask for the phase place of 4 subband signals respectively, utilize phase difference method to carry out time difference measurements, asks for the mistiming that 4 sensors receive acoustic emission signal.

Step 7: the mistiming being received acoustic emission signal by 4 sensors of the determination in step 6, adopts least square method to carry out the coordinate of acoustic emission space orientation acquisition acoustic emission source K point by the position coordinates of four sensors.

2. a kind of Acoustic Emission of Rock source electricity method according to claim 1, is characterized in that: the N in described step 2 is more than or equal to 4.

3. a kind of Acoustic Emission of Rock source electricity method according to claim 1, is characterized in that: the acoustic emission signal that the internal injury of described step 3 produces is obtained by disconnected plumbous experiment.

4. a kind of Acoustic Emission of Rock source electricity method according to claim 1, it is characterized in that: the concrete grammar of described step 5: for carrying out Fast Fourier Transform (FFT) to layer signal each after wavelet decomposition, obtain 2-d spectrum figure, the frequency that in 2-d spectrum figure, maximum amplitude is corresponding is the dominant frequency of this acoustic emission signal; Utilize the method to ask for the dominant frequency value of each layer signal, the subband signal dominant frequency after each sensor of comparative analysis decomposes, therefrom find out immediate 4 subband signals of dominant frequency, 4 subband signals are respectively from 4 different sensors.