CN107588878A  A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features  Google Patents
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features Download PDFInfo
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 CN107588878A CN107588878A CN201711059839.2A CN201711059839A CN107588878A CN 107588878 A CN107588878 A CN 107588878A CN 201711059839 A CN201711059839 A CN 201711059839A CN 107588878 A CN107588878 A CN 107588878A
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Abstract
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, carries out the axle Experimental on acoustic emission of rock three, obtains rock sample in the actual triaxial stress state numerical value in underground；The interpretation of Kaiser points is carried out with accumulative Ringdown count time graph；Accumulative sound emission Ringdown count is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process；The fractal characteristic of rock is analyzed using the Ringdown count correlation dimension of sound emission；The time of Kaiser points is picked up, the stress value corresponding to reading on stress time curve, stress now is exactly rock sample axial direction history maximum crustal stress.The present invention determines the time range of Kaiser points appearance using improved tangent line graphing method, Treatment Analysis is carried out to test data based on fractal theory knowledge again, then the time that Kaiser points occur is locked, the stress value at Kaiser points is finally read from stress time curve, so as to realize the accurate easy interpretation to Kaiser points.
Description
Technical field
It is a kind of base the present invention relates to the interpretation method technical field of Acoustic Emission of Rock test measurement crustal stress kasier points
The more accurate interpretation method of kasier effect points is tested to Acoustic Emission of Rock in fractal theory knowledge.
Background technology
Acousticemission is a kind of direct earth stress measuring method, and crustal stress is measured according to rock kaiser effects, with
Traditional method of testing is compared because its is simple and convenient, cheap, and be adapted to indoor extensive batch testing and by wide both at home and abroad
General use.But in the interpretation for obtaining Kaiser points with acousticemission, also there is some shortcomings.
The big multipair rock sample of Acoustic Emission of Rock experiment at present carries out conventional oneaxis compression test, it is impossible to reflects rock mass well
The occurrence status of three received strength in underground, cause the Kaiser point values that measure more relatively low than actual value.
The interpretation of Kaiser points is also the key of acousticemission measurement crustal stress.The interpretation of current Kaiser points is typically all
By the changes of acoustic emission signal some or multiple parameters drastically degree, to determine position that Kaiser points occur.It is conventional
Interpretation method have two kinds, a kind of is by some parameter of sound emission and the direct interpretation of the relation of time, sees Fig. 1.This method
Foundation be whether to have the generation of a large amount of sound emissions after some time point.But there is no quantitative mark for a large amount of sound emissions
Standard, interpretation have certain subjectivity, the more difficult assurance degree of accuracy in application.Another method be according to sound emission some is tired
The rate of change drastically change point interpretation of parameter and the relation curve of time is counted, this method has being easier to for obvious flex point for curve
Interpretation.As shown in Figure 2.And then carry out auxiliary interpretation by tangent line for what accumulative parameter flex point obscured, the point of intersection of tangents is defined as
Kaiser points, as shown in Figure 3.
Above two is in accordance with data on the increase suddenly or bent of a certain parameter for the interpretation method of Kaiser points
The unexpected increase of line slope judges, to the standard of this kind of no Quantitative evaluation of change, when this change unobvious, it is difficult to control
Make the error of artificial interpretation.
The content of the invention
The purpose of the present invention is to measure Kaiser points for current acousticemission to have the defects of interpretation, and is proposed a kind of
Based on the basis of the axle Experimental on acoustic emission of rock three, the method to the accurate easy interpretation of Kaiser points is realized.
The purpose of the present invention is achieved through the following technical solutions：
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, comprises the following steps：
The first step：The axle Experimental on acoustic emission of rock three is carried out, obtains rock sample in the actual triaxial stress state numerical value in underground；
Second step：The interpretation of Kaiser points is carried out with accumulative Ringdown counttime graph；Before Data Management Analysis is carried out
The noise reduction process of Acoustic Emission of Rock time series, noise reduction mistake are carried out with the small wave systems of Daubechie to sound emission Ringdown count sequential
Journey is divided into following 3 steps：
(1) wavelet decomposition is carried out to primary signal：One can be expressed as containing noisy signal model：
S (j)=f (j)+α e (j), (j=0,1, k, n1), in formula：S (j) is containing noisy primary signal, f (j)
For the actual signal of Acoustic Emission of Rock, e (j) is noise signal；It is original to sound emission using Matlab softwares selection db3 wavelet basis
Signal carries out 5 layers of decomposition computation；
(2) to carrying out threshold values quantization containing noisy wavelet coefficient：Using the method noise reduction process of fixed threshold values, valve is chosen
Value Q is：
Q=sqrt [2lg (length (y))], in formula：Y represents the signal of analysis；It is noisy small to containing after Wavelet transformation
Wave system number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, and the wavelet coefficient more than Q is changed into the difference with Q；
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed；
3rd step, accumulative sound emission ring meter is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process
Number；Polynomial of degree n fitting specially is carried out to accumulative Ringdown counttime graph first, then to being cut a little on curve
Line, last picked up water flat level and the linear increase section point of intersection of tangents are defined as the time of Kaiser points appearance compared with the region of concentration
Scope；
4th step：Other neighbouring points are higher than according to the frequency band energy of Kaiser points, fractal dimension is less than the feature of consecutive points,
With reference to the less situation of interpretation noise spot of the accumulative Ringdown count curve to Kaiser points of sound emission, using the ring of sound emission
Correlation dimension is counted to analyze the fractal characteristic of rock；According to Grassberger and Procaccia propose from time series meter
Calculate the GP computational methods of the correlation dimension of sequence, using the basic parameter sequence of sound emission as research object, then each sequence
The sequence sets that a corresponding sample size is n：
X={ x_{1},x_{2},x_{3},…,x_{n}} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), before taking m number as a m of sample space tie up to
Amount：
X_{1}={ x_{1},x_{2},x_{3},…,x_{m}} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form nm+ altogether
1 m dimensional vector, corresponding correlation function are：
In formula (3), H is Heaviside functions, and r is given yardstick；Take
In formula (4), k is proportionality coefficient；
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension is obtained, these scatterplots are such as
Fruit can form straight line on { lnW [r (k)], lnr (k) }, just illustrate that the Acoustic Emission Sequence of sample possesses well under given dimension
Fractal characteristic, it is believed that the slope of regression straight line is exactly correlation dimension；Each sample is calculated by abovementioned GP algorithms
Fractal dimensionwhen m stress relation figure；Fractal dimension minimum value is read in the approximate Kaiser points time range of estimated reading
The place time, interpretation fractal dimension minimum value to the time be Kaiser points occur time；
5th step：Pick up Kaiser points time, in stress time curve read corresponding to stress value, now should
Power is exactly rock sample axial direction history maximum crustal stress.
The present invention determines the time range of Kaiser points appearance using improved tangent line graphing method, then is known based on fractal theory
Know and Treatment Analysis is carried out to test data, this of consecutive points is then less than according to the fractal dimension at Acoustic Emission of Rock Kaiser points
The time that one feature locking Kaiser points occur, the stress value at Kaiser points is finally read from stress time curve, so as to
Realize to the accurately easy interpretation of Kaiser points.The present invention at least has the advantages that：
(1) the indoor axle Experimental on acoustic emission of rock three is carried out, triaxial stress state of the geological diagnostics in underground is preferably gone back, measures
Kaiser point datas closer to actual value.
(2) after carrying out noise reduction process to Acoustic Emission of Rock Ringdown count sequential, the accumulative Ringdown count with reference to sound emission is bent
The advantages of line is less to the interpretation noise spot of Kaiser points, carry out what interpretation obtained from accumulative Ringdown counttime graph
Kaiser points are more accurate；
(3) on the basis of Kaiser point time of occurrences are sentenced according at the beginning of improved traditional tangent line graphing method, with reference to rock sound
Launch screen further less than the feature of consecutive points of the fractal dimension at Kaiser points and obtain more accurate Kaiser point values,
Reduce the influence of human factor in traditional graphing method.
Brief description of the drawings
Fig. 1 is the Kaiser point interpretations of the acoustic emission parameters of prior art, and the relation with acoustic emission parameters and time is direct
The position that interpretation Kaiser points occur；
Fig. 2 is the obvious Kaiser points interpretation of accumulative parameter flex point of prior art, with the accumulative parameter of sound emission and when
Between relation curve rate of change drastically change point interpretation Kaiser points occur position；
Fig. 3 is the fuzzy Kaiser point interpretations of the accumulative parameter flex point of prior art, and the point of intersection of tangents is defined as Kaiser
Point；
Fig. 4 is that fractal dimension and phase space dimension relation curve are associated in the inventive method.
Fig. 51~Fig. 512 and Fig. 61~Fig. 612 is the interpretation of the rock Kaiser points of the present invention, wherein,
Fig. 51 is that 225 ° of1 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 52 is that 225 ° of2 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 53 is that 225 ° of3 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 54 is that 270 ° of1 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 55 is that 270 ° of2 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 56 is that 270 ° of3 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 57 is that 315 ° of1 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 58 is that 315 ° of2 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 59 is that 315 ° of3 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 510 is that 90 ° of1 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 511 is that 90 ° of2 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 512 is that 90 ° of3 sample of horizontal direction adds up acoustic emission ratetime relationship；
Fig. 61 be 225 ° of1 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 62 be 225 ° of2 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 63 be 225 ° of3 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 64 be 270 ° of1 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 65 be 270 ° of2 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 66 be 270 ° of3 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 67 be 315 ° of1 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 68 be 315 ° of2 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 69 be 315 ° of3 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 610 be 90 ° of1 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 611 be 90 ° of2 sample of horizontal direction correlation dimensionwhen m stress relation curve；
Fig. 612 be 90 ° of3 sample of horizontal direction correlation dimensionwhen m stress relation curve.
Embodiment
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, comprises the following steps：
The first step：The axle Experimental on acoustic emission of rock three is carried out, can preferably reflect rock sample in underground under the experiment of three axle confined pressures
Actual triaxial stress state, the data of acquisition are closer to actual value；
Second step：The interpretation of Kaiser points is carried out with accumulative Ringdown counttime graph；Before Data Management Analysis is carried out
The noise reduction process of Acoustic Emission of Rock time series, noise reduction mistake are carried out with the small wave systems of Daubechie to sound emission Ringdown count sequential
Journey is divided into following 3 steps：
(1) wavelet decomposition is carried out to primary signal：One can be expressed as containing noisy signal model：
S (j)=f (j)+α e (j), (j=0,1, k, n1), in formula：S (j) is containing noisy primary signal, f (j)
For the actual signal of Acoustic Emission of Rock, e (j) is noise signal；It is original to sound emission using Matlab softwares selection db3 wavelet basis
Signal carries out 5 layers of decomposition computation；
(2) to carrying out threshold values quantization containing noisy wavelet coefficient：Using the method noise reduction process of fixed threshold values, valve is chosen
Value Q is：
Q=sqrt [2lg (length (y))], in formula：Y represents the signal of analysis；It is noisy small to containing after Wavelet transformation
Wave system number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, and the wavelet coefficient more than Q is changed into the difference with Q；
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed；
The determination of prior art Kaiser points mainly carries out interpretation using characteristics of Acoustic Emission parameter curve, by different
The comparison and analysis of characteristic parameter curve show that the readability of Kaiser points is followed successively by：Accumulative AE EnergyTime curves ＞ adds up
AE rings numbertime graph ＞ adds up AE event numberstime graph.But in graphing method intuitive judgment Kaiser points, add up
AE EnergyTimes curve map is it is possible that multiple catastrophe points, these noise spots will cause larger to the accuracy of sentence read result
Influence；And accumulative AE rings numbertime graph influenceed by contrast by this respect it is smaller.Therefore, the present invention is from accumulative
Ringdown counttime graph carries out the interpretation of Kaiser points.
Additionally due to inevitably there is the interference of various noises in the gatherer process of Rock Acoustic Emission Signal, in order to
Influence of the interference signal to accumulative AE rings numbertime graph is further reduced, sound is sent out before Data Management Analysis is carried out
Penetrate Ringdown count sequential and carry out noise reduction process.Analyze and test by indepth study, it is determined that using the method for wavelet analysis, with
Useful primary signal is extracted from the acoustic emission signal containing various influence of noises, signal to noise ratio is improved, restores trueer
Real acoustic emission signal data.Simultaneously for the feature of Rock Acoustic Emission Signal, different types of wavelet function is integrated
Comparative analysis and experiment, it is determined that carrying out the noise reduction process of Acoustic Emission of Rock time series with the small wave systems of Daubechie；
3rd step, accumulative sound emission ring meter is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process
Number.When determining Kaiser point positions with the mapping of prior art tangential method, big more options level of approximation straightway and linear increase
Section makees two tangent lines respectively, and the intersection point of tangent line is defined as to the position of Kaiser points appearance.During the mapping of reality, tangent line
The selection of position is larger by the interference of people's subjective factor, the Kaiser points position finally determined often vary with each individual exist it is larger
Human error.The present invention makes some improvement using Matlab softwares to conventional tangent line graphing method, first to adding up ring meter
Numbertime graph carries out polynomial of degree n fitting, then to doing tangent line, last picked up water flat level and line on curve a little
Property increase the section point of intersection of tangents compared with the region of concentration be defined as Kaiser points appearance time range；
4th step：Numerous studies show that the frequency band energy of Kaiser points is higher than other neighbouring points, and fractal dimension is less than adjacent
Point.According to this feature of Kaiser effects, with reference to interpretation interference of the accumulative Ringdown count curve to Kaiser points of sound emission
The less situation of point, the fractal characteristic of rock is analyzed using the Ringdown count correlation dimension of sound emission.According to Grassberger
With Procaccia propose the correlation dimension from the time series sequence of calculation GP computational methods, with the basic parameter of sound emission
Sequence answers the sequence sets that a sample size is n as research object, then each sequence pair：
X={ x_{1},x_{2},x_{3},…,x_{n}} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), before taking m number as a m of sample space tie up to
Amount：
X_{1}={ x_{1},x_{2},x_{3},…,x_{m}} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form nm+ altogether
1 m dimensional vector.Corresponding correlation function is：
In formula (3), H is Heaviside functions, and r is given yardstick.In order to control the discreteness of result of calculation typically to take
In formula (4), k is proportionality coefficient；
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension can be obtained, these dissipate
If point can form straight line on { lnW [r (k)], lnr (k) }, just illustrate that the Acoustic Emission Sequence of sample possesses under given dimension
Good fractal characteristic, it is believed that the slope of regression straight line is exactly correlation dimension.Each is calculated by abovementioned GP algorithms
Sample fractal dimensionwhen m stress relation figure.Fractal dimension is read in the approximate Kaiser points time range of estimated reading most
Time where small value, interpretation fractal dimension minimum value institute is to time that the time is the appearance of Kaiser points；
5th step：The time of Kaiser points is picked up, the stress value corresponding to reading in stress time curve, it is believed that now
Stress be exactly sample axial direction history maximum stress level.
Using the inventive method, certain largescale mine has carried out geostress survey experiment at home.Embodiment specifically describes such as
Under：
The first step：Live coring.This is tested is in exploitation stage casing scene coredrilling, direction where institute's coring axis
Close to 90 ° perpendicular to the ground, 225 °, 270 °, the four directions such as 315 ° of horizontal direction, core diameter is in 50mm or so.
Second step：Sample is processed.To ensure the integrality and homogenieity of rock, in manufactured 47 examinations of this experiment
12 close samples of velocity of wave are chosen in sample to be tested.Specimen size is that the ratio of height to diameter of Pass Test code is 2:1 cylinder
Shape sample.The specifying information of sample is shown in Table 1.
The Experimental on acoustic emission sample information table of table 1
3rd step：Test apparatus and parameter setting.Indoor emission experiment needs to use RMT150C rock mechanics experiments system
System and SAEU2S type Full wave shape multiple channel acousto emission detectors carry out the loading of triaxial test and the collection of acoustic emission signal respectively.
Two systems coordinate the change that can gather and record basic variable and parameter during testing, and automatically generate each parameter
Graph of a relation.
The Ushaped probe of resonance that Acoustic Emission Testing System is 1000kHz with centre frequency, data acquisition is selected during data analysis
Complete passage is as research sample.Acoustic emission parameters are shown in Table 2.
The sound emission acquisition parameter of table 2 is set
Threshold value  Preamplification gain  Analog filter lower limit  The analog filter upper limit  Sample rate  Sampling length 
40dB  40dB  100KHz  3MHz  1MSPS  2k 
4th step：Using abovementioned Acoustic Emission of Rock testing equipment, 12 samples of processing are tested, acquisition sound hair
Penetrate stimulus.Db3 wavelet basis is selected using Matlab softwares, using the form of fixed threshold values to sound emission Ringdown count sequential
Carry out noise reduction process.Sound emission is calculated according to the data after noise reduction process and adds up Ringdown count rate, is first drawn out corresponding tired
The relation curve of Ringdown count ratetime is counted, then makees tangent line to every bit on curve, pickup level of approximation straightway and linear increasing
The long section point of intersection of tangents is compared with the time range that the region of concentration is that Kaiser points occur.
5th step：The Ringdown count that whole sound emission process is calculated using GP algorithms associates fractal dimension.By GP algorithms
Process understand that association fractal dimension is influenceed by phase space reconstruction dimension m, so calculating association point calculating each sequence
The phase space dimension to be consistent during shape dimension.This just needs first to inquire into phase space dimension with associating the relation of fractal dimension,
Phase space dimension corresponding to stable association fractal dimension is selected, to ensure the stability of data.By taking sample 2702 as an example, meter
It is as shown in Figure 4 with the variation tendency for associating fractal dimension that calculation obtains phase space dimension.
From Fig. 4 change curve, taken in phase space dimension and associate the variable gradient of fractal dimension relatively after 4
Steadily, illustrate that sample has good fractal characteristic when Embedded dimensions are 4, therefore take m=4., will when calculating association fractal dimension
The parameter that Experimental on acoustic emission obtains takes 1024, i.e. n=1024 as a sequence changed over time, the capacity of sequence.
By GP algorithms be calculated each sample fractal dimensionwhen m stress relation.Each test specimen adds up
The relation of acoustic emission ratetime and it is corresponding correlation dimensionwhen m stress relation curve such as Fig. 51~Fig. 512 and Fig. 61~
Shown in Fig. 612, the time where reading fractal dimension minimum value in the approximate Kaiser points time range of estimated reading, interpretation point
Shape dimension minimum value be time that Kaiser points occur to the time, wherein P points are that fractal dimension is minimum in selected time range
Point, as Kaiser point, stress value corresponding to the point are the stress of primary rock value of sample axial direction.
Interpretation is carried out to the Kaiser points stress value of each sample, as a result converges into table 3.
The rock sample Kaiser point stress values of table 3
6th step：Threedimensional ground stress analytical Calculation simultaneously analyzes the accuracy for verifying that the method obtains kasier points.According to following
Three formula can utilize the direct stress of three different directions in same level to solve to obtain two principal stresses in horizontal plane
Size and Orientation.
The stress value for exploiting three directions of stage casing level is respectively σ_{Ι}=9.13MPa, σ_{ΙΙ}=15.8MPa, σ_{ΙΙΙ}=
18.13MPa substituting into formula has：
Therefore the size of the maximum horizontal principal stress in exploitation stage casing is σ_{1}=18.63MPa, the size of minimum horizontal principal stress are
σ_{2}=8.63MPa.
The factors such as the presence of vertical stress and tectonic activity, superincumbent stratum thickness, temperature, hydraulic pressure are relevant, wherein upper overlying strata
Gravity suffered by layer is main influence factor.The largescale statistics in the whole world shows, in 25~2700m of depth scope
It is interior, σ_{υ}It is about as much as volumeweighted average γ and is equal to 27kN/m^{3}The gravity γ H calculated.Exploit the height of stage casing overlying rock about
For 500m.Exploit stage casing estimation vertical stress σ_{G}, then have：
σ_{G}=γ H=0.027 × 500=13.5MPa
γ is the unit weight of overlying rock in formula, and H is depth
The vertical stress value of sound emission measurement is 11.73Mpa, substantially conforms to overlying rock rule.
Substantial amounts of measured result shows that maximum, the minimum principal stress of world's most area are all distributed in almost horizontal
On inplane, and maximum horizontal principal stress σ_{h,max}With vertical stress σ_{v}Ratio typically in the range of 0.5~5.5.With reference to
The existing largescale field data in the world, two horizontal principal stress average σ_{h,av}With vertical principal stress σ_{v}Ratio σ_{h,av}/σ_{v}Mostly
Number is 0.8~1.5, referring to table 4.
The relation of the countries in the world average level principal stress of table 4 and vertical principal stress
The size that two horizontal principal stress in stage casing are exploited according to the results showed that of 3 direction samples of level is distinguished
For σ_{h,max}=18.63MPa, σ_{h,min}=8.63MPa, average σ_{h,av}=13.63MPa.And the experiment knot of vertical principal stress herein
Fruit average value is σ_{v}=11.73MPa, then understand the horizontal principal stress average of this measuring point and the ratio σ of vertical stress_{h,av}/σ_{v}=
1.16, the ratio σ of maximum horizontal principal stress and vertical principal stress_{h,max}/σ_{v}=1.59, substantially conform to the statistics rule of geodetic stress
Rule.
Claims (1)
1. a kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, it is characterised in that including such as
Lower step：
The first step：The axle Experimental on acoustic emission of rock three is carried out, obtains rock sample in the actual triaxial stress state numerical value in underground；
Second step：The interpretation of Kaiser points is carried out with accumulative Ringdown counttime graph；To sound before Data Management Analysis is carried out
Transmitting Ringdown count sequential carries out the noise reduction process of Acoustic Emission of Rock time series, noise reduction process point with the small wave systems of Daubechie
For following 3 steps：
(1) wavelet decomposition is carried out to primary signal：One can be expressed as containing noisy signal model：
S (j)=f (j)+α e (j), (j=0,1, k, n1), in formula：S (j) is that f (j) is rock containing noisy primary signal
The actual signal of stone sound emission, e (j) are noise signal；Db3 wavelet basis is selected to sound emission primary signal using Matlab softwares
Carry out 5 layers of decomposition computation；
(2) to carrying out threshold values quantization containing noisy wavelet coefficient：Using the method noise reduction process of fixed threshold values, threshold values Q is chosen
For：
Q=sqrt [2lg (length (y))], in formula：Y represents the signal of analysis；To containing noisy wavelet systems after Wavelet transformation
Number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, the wavelet coefficient more than Q is changed into the difference with Q；
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed；
3rd step, accumulative sound emission Ringdown count is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process；
Polynomial of degree n fitting specially is carried out to accumulative Ringdown counttime graph first, then to doing tangent line a little on curve,
Last picked up water flat level and the linear increase section point of intersection of tangents are defined as the time model of Kaiser points appearance compared with the region of concentration
Enclose；
4th step：Other neighbouring points are higher than according to the frequency band energy of Kaiser points, fractal dimension is less than the feature of consecutive points, with reference to
The less situation of interpretation noise spot of the accumulative Ringdown count curve to Kaiser points of sound emission, using the Ringdown count of sound emission
Correlation dimension analyzes the fractal characteristic of rock；According to what Grassberger and Procaccia was proposed sequence is calculated from time series
The GP computational methods of the correlation dimension of row, using the basic parameter sequence of sound emission as research object, then each sequence pair should
The sequence sets that one sample size is n：
X={ x_{1},x_{2},x_{3},…,x_{n}} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), a m dimensional vector of the m number as sample space before taking：
X_{1}={ x_{1},x_{2},x_{3},…,x_{m}} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form nm+1 m altogether
Dimensional vector, corresponding correlation function are：
<mrow>
<mi>w</mi>
<mo>&lsqb;</mo>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>N</mi>
<mn>2</mn>
</msup>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mi>H</mi>
<mo>&lsqb;</mo>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo></mo>
<mo></mo>
<mrow>
<msub>
<mi>X</mi>
<mi>i</mi>
</msub>
<mo></mo>
<msub>
<mi>X</mi>
<mi>j</mi>
</msub>
</mrow>
<mo></mo>
<mo>&rsqb;</mo>
<mo></mo>
<mo></mo>
<mo></mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (3), H is Heaviside functions, and r is given yardstick；Take
<mrow>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>k</mi>
<mfrac>
<mn>1</mn>
<msup>
<mi>N</mi>
<mn>2</mn>
</msup>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mo></mo>
<mrow>
<msub>
<mi>X</mi>
<mi>i</mi>
</msub>
<mo></mo>
<msub>
<mi>X</mi>
<mi>j</mi>
</msub>
</mrow>
<mo></mo>
<mo></mo>
<mo></mo>
<mo></mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (4), k is proportionality coefficient；
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension is obtained, if these scatterplots exist
Straight line can be formed on { lnW [r (k)], lnr (k) }, just illustrates that the Acoustic Emission Sequence of sample possesses good point under given dimension
Shape feature, it is believed that the slope of regression straight line is exactly correlation dimension；Point of each sample is calculated by abovementioned GP algorithms
Shape dimensionwhen m stress relation figure；In the approximate Kaiser points time range of estimated reading where reading fractal dimension minimum value
Time, interpretation fractal dimension minimum value to the time be Kaiser points occur time；
5th step：The time of Kaiser points is picked up, the stress value corresponding to reading in stress time curve, stress now is just
It is rock sample axial direction history maximum crustal stress.
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WO2020248476A1 (en) *  20190610  20201217  华北水利水电大学  Acoustic emission type determination method based on acoustic emission ascending wave band collection parameter 
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Cited By (4)
Publication number  Priority date  Publication date  Assignee  Title 

CN109100247A (en) *  20180718  20181228  太原理工大学  Class coal petrography stone crustal stress K point test method based on Kaiser effect 
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CN110514538A (en) *  20190731  20191129  太原理工大学  Highintensitive rock crustal stress K point test method based on Kaiser effect 
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