CN106918836B - Borehole strain data exception extraction method based on principal component analysis - Google Patents
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- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 claims description 2
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- 239000002243 precursor Substances 0.000 abstract description 9
- 230000002159 abnormal effect Effects 0.000 abstract description 6
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- 230000003203 everyday effect Effects 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 abstract description 2
- 230000005856 abnormality Effects 0.000 description 5
- 238000005553 drilling Methods 0.000 description 3
- 230000002354 daily effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000011888 foil Substances 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 208000033999 Device damage Diseases 0.000 description 1
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Abstract
The present invention relates to a kind of borehole strain data exception extraction method based on principal component analysis, is that the borehole strain data sequence of the same station is carried out into strain conversion first, the data after conversion are pre-processed；By pretreated borehole strain data configuration into a matrix；And principal component analysis is carried out to the matrix of every day, to obtain the characteristic value of each matrix and characteristic vector；Obtained characteristic value is corresponding with seismic events with the characteristic vector angle calculated, to obtain abnormal testing result.Effectively borehole strain data can be analyzed using the method for principal component analysis by the present invention, the correlation of item is respectively surveyed according to borehole strain, possible Earthquake Precursor Anomalies are extracted.Borehole strain data exception extraction method of the present invention, the faint change of the earth's crust is characterized respectively using the characteristic value in principal component analysis and characteristic vector angle；Realize the accurate extraction to borehole strain data exception in the case where there are stronger ambient interferences.
Description
Technical field
The present invention relates to a kind of seismic precursor observation data method for detecting abnormality, and in particular to one kind is based on principal component analysis
Borehole strain data exception extraction method.
Background technology
Geoscience is a subject based on observation and survey data, and the constantly improve to observation system is development
Geoscience, the only way for mitigating disaster.Earth surface deform and the earth's crust inside tectonic movement and its it is caused variously
Matter disaster is all closely related with crustal stress effect, and the change of Crustal stress state is to cause fracture, fold or even generation earthquake
Most direct reason.Borehole strain observation is found by the fine observation changed to stratum internal strain state according to Time Continuous
Spatial and temporal distributions and development and change rule with being adjusted after (length) mid-term-short-term-imminent earthquake of grasp earthquake strain omen and shake, it is
Important earthquake precursor observation means.Borehole strain observation is easy by precision height, strong antijamming capability, more survey item observations, instrument
Become the Precursor means for being only second to GPS observations in safeguard the features such as.
Principal component analytical method in theory can know the signal of relative weak in primary signal from compared with strong jamming background
Do not come out, solve the problems, such as that earth's crust change small-signal is submerged in compared with strong jamming background in Borehole strain observation.
CN104390733A discloses a kind of determination method of crustal stress size and Orientation, in the epoxy resin of measurement stress
Peripherally disposed three strain rosettes on hollow inclusion, the angle of adjacent strain rosette is 120 °, there is four on each strain rosette
Foil gauge, the foil gauge on each strain rosette rotate 45 ° of settings successively；Using 12 different directions strain values on circumferencial direction,
Crustal stress and stress direction can accurately and effectively be calculated.
CN202452947U discloses a kind of Four component seismic technology observation system, including the data storage set on well
The component strain instrument of master four and the signal cable of connection underground that web-transporting device, underground are set, in addition to underground are set
The component strain instrument of auxiliary four.By setting a master, auxiliary two four component strain instrument in observation system, system is added
Reliability, avoid because a device damage allows for the situation of whole system paralysis.
Qiu Zehua etc. (abnormal with the small echo-rate that transfinites analysis extraction Ningshan platform Wenchuan earthquake body strain, 2012) utilizes small echo
To aunt, our the component borehole strain data of the station four are studied with the improved rate analysis method that transfinites for decomposition, and trickle earthquake is different
Often change is fine to be extracted.Chi Shunliang etc. (before the shake of Mount Lushan Ms7.0 earthquakes in 2013 and imminent earthquake strain abnormality, 2013) profits
With our component Borehole strain observation data of the station four of Mount Lushan BEFORE AND AFTER EARTHQUAKE aunt, earthquake is analyzed with shake signal.But at present
Untill, there is not yet with the method for principal component analysis borehole strain data are carried out with the report of anomaly extracting.
The content of the invention
The purpose of the present invention is that for above-mentioned the deficiencies in the prior art, there is provided a kind of drilling based on principal component analysis
Strain data abnormal extraction method.
The purpose of the present invention is achieved through the following technical solutions：
The present invention carries out anomaly extracting using principal component analysis to borehole strain data, is by the drilling of the same station first
Strain data sequence carries out strain conversion, and the data after conversion are pre-processed；By pretreated borehole strain data structure
Cause a matrix；And principal component analysis is carried out to the matrix of every day, to obtain the characteristic value of each matrix and characteristic vector；
Obtained characteristic value is corresponding with seismic events with the characteristic vector angle calculated, to obtain abnormal testing result.
Effectively borehole strain data can be analyzed using the method for principal component analysis by the present invention, it is each according to borehole strain
The correlation of item is surveyed, possible Earthquake Precursor Anomalies are extracted.
A kind of borehole strain data exception extraction method based on principal component analysis, comprises the following steps：
A, typing borehole strain data, and the checking of data validity is carried out, "Yes", carry out in next step；
B, strain conversion is carried out to borehole strain data；
C, data prediction；
D, makes sample data；
E, the covariance matrix of sample data is sought；
F, the characteristic value and characteristic vector of covariance matrix are obtained；
G, the angle of feature value vector is obtained；
H, output characteristic value change curve；
I, output characteristic vector angle change curve and statistic histogram.
Step a, described typing borehole strain data are to choose four component borehole strain numbers of a station from different places
According to, be fabricated to according to minute value sample time series.The checking of data validity is represented by according to different components, data
S1,S2,S3,S4；It is right according to the relational expression of circular hole radial deformation and regional stress as derived from perforated flat plate elastic theory model
Borehole strain data are carried out from being in harmony analysis, and its relational expression is：
S1+S3=k (S2+S4), (1)
It is valid data to be selected from being in harmony data of the coefficient k more than 0.9.
Step b, it is described that borehole strain data are carried out straining conversion to be to be seen four component borehole strains according to formula (2)
Data reduction is surveyed into two shearing strain S13、S24S is strained with a facea,
Step c, described data prediction is to carry out harmonic analysis to data, for removing the periodic term of data；It is adjusted
And analytic functionExpression formula is：
Wherein, A0For the DC component of time series, m is the number of harmonic wave, coefficient Am,BmIt is weight factor, represents each time
Contribution of the harmonic wave to total sequence；The cycle data that initial data subtracts after fitting is exactly data after the pretreatment that we want.
Step d, described makes sample data are that the daily data of the station after pretreatment are expressed as into Z in temporal sequence1
=[Z1(1),Z1(2),...,Z1(1440)],…,Zn=[Zn(1),Zn(2),...,Zn(1440) sample matrix can], be obtained
Y=[Z1,Z2,Z3,...,Zn]T.Sample matrix Y expression formula is：
Step e, sample data Y (n × 1440) its covariance matrix CYThe element γ of (n × n)pqCalculated by formula (5)
Arrive,
Wherein,WithRespectively the i-th row pth and q minute datas；WithIt is the pth and q of N row data respectively
The average of minute data.
Step f, the characteristic value for obtaining covariance matrix are the covariance matrix C to matrix YYCarry out Eigenvalues Decomposition,
CY=R ∧ RT, (6)
In formula, ∧ (n × n) is the characteristic value diagonal matrix of size descending arrangement；R (n × 1) be and characteristic value diagonal matrix
Corresponding eigenvectors matrix.The list of feature values is shown as λ1,λ2,...,λn(λ1＞ λ2＞ ... ＞ λn)。
Step g, the characteristic vector angle of obtaining is to set characteristic vector as R=[V1 V2 ... Vn]T, as shown in Figure 2,
Characteristic vector angle is：
Compared with prior art, the beneficial effects of the present invention are：Borehole strain number of the invention based on principal component analysis
According to abnormal extraction method, the faint change of the earth's crust is characterized respectively using the characteristic value in principal component analysis and characteristic vector angle
Out；Realize the accurate extraction to borehole strain data exception in the case where there are stronger ambient interferences.
Brief description of the drawings
Fig. 1 is the borehole strain data exception extraction method flow chart based on principal component analysis；
Fig. 2 is characterized vectorial angle schematic diagram；
Fig. 3 is our monitoring of earthquake precursors station of aunt and Lushan earthquake epicenter position view；
Fig. 4 is first principal component characteristic value change curve；
Fig. 5 is first principal component characteristic vector angle change schematic diagram；
Fig. 6 a are the characteristic vector angle stereogram of All Time section；
Fig. 6 b are without characteristic vector angle stereogram during shake；
Fig. 6 c are the characteristic vector angle stereogram of 5 months Earthquake Precursor Anomalies data before shake；
Fig. 6 d are the characteristic vector angle stereogram of BEFORE AND AFTER EARTHQUAKE abnormal data.
Embodiment
With reference to embodiment, the present invention is described in detail.
For Lushan earthquake, by taking the borehole strain minute Value Data of our the monitoring of earthquake precursors station of Sichuan province aunt as an example.
Our station of aunt and Lushan earthquake location are as shown in Figure 3.The data use YRY tetra- on December 31,1 day to 2013 January in 2012
Component drilling strain gauge measures.
A, typing aunt we be worth time series station borehole strain minute on December 31,1 day to 2013 January in 2012, according to
Data are designated as S by the southern component in north, thing component, east northeast component, the order of northwest (NW) component respectively1、S2、S3、S4；According to by with holes
The relational expression of circular hole radial deformation and regional stress derived from flat board elastic theory model, borehole strain data are carried out from being in harmony point
Analysis, its relational expression are：
S1+S3=k (S2+S4), (1)
The k values calculated, our station borehole strain on December 31,1 day to 2013 January in 2012 of aunt is understood by k >=0.9
Minute Value Data is effective.
B, it is by four component Borehole strain observation data reductions according to formula (2) borehole strain data to be carried out straining conversion
Into two shearing strain S13、S24S is strained with a facea；
C, data prediction, i.e., harmonic analysis is carried out to the data after conversion, removes the periodic response of strain data；Reconcile
Analytic functionExpression formula is：
Wherein A0For the DC component of time series, m is the number of harmonic wave, coefficient Am,BmIt is weight factor, represents each time
Contribution of the harmonic wave to total sequence.The cycle data that initial data subtracts after fitting is exactly data after the pretreatment that we want.
D, the daily data of pretreated borehole strain are expressed as
Zn=[Zn(1),Zn(2),...,Zn(1440)], n=1,2,3,
Sample matrix Y=[Z can be obtained1,Z2,Z3]T.Sample matrix Y expression formula is：
E, sample data Y covariance matrix, sample data Y (3 × 1440) its covariance matrix C are askedYThe member of (3 × 3)
Plain γpqIt is calculated by formula (5),
Wherein,WithThe respectively pth and q minute datas of the i-th row data；WithIt is Nth row data respectively
Pth and q minute datas average.
F, to matrix Y covariance matrix CYCarry out Eigenvalues Decomposition,
CY=R ∧ RT, (6)
In formula, ∧ (3 × 3) is the characteristic value diagonal matrix of size descending arrangement；R is corresponding with characteristic value diagonal matrix
Eigenvectors matrix, the list of feature values is shown as λ1,λ2,λ3(λ1＞ λ2＞ λ3)。
G, characteristic vector angle is obtained；R is set by taking first principal component characteristic vector as an example1=[V1,V2,V3], according to Fig. 2 institutes
Show, obtained by formula (7)
Second, third principal component characteristic vector can similarly be asked.
H, characteristic value change curve is obtained, as shown in figure 4, in figure, solid line is first principal component characteristic value, --- dotted line is
The Lushan earthquake moment, in rectangle frame for the earthquake relevant abnormalities extracted, it can be seen that characteristic value characterizes earthquake well
Relevant abnormalities.
I, characteristic vector angle change figure and statistic histogram, such as Fig. 5 are obtained, shown in Fig. 6 a- Fig. 6 d.Open circles in Fig. 5
Point is characterized vectorial angle, --- dotted line is the Lushan earthquake moment, in rectangle frame for the earthquake relevant abnormalities extracted.Fig. 6 a-
Fig. 6 d are first principal component characteristic vector angle change stereogram, from Fig. 6 d can be seen that feature in unusual part to
Measuring angle has obvious clustering phenomena, has extracted Earthquake Precursor Anomalies well.
Claims (5)
1. a kind of borehole strain data exception extraction method based on principal component analysis, it is characterised in that comprise the following steps：
A, typing borehole strain data, and the checking of data validity is carried out, "Yes", carry out in next step, specially：Typing is in harmony certainly
Borehole strain minute Value Data of the coefficient more than 0.9；
B, by borehole strain data reduction into two shearing strain S13、S24S is strained with a facea；
C, data prediction, to two shearing strain S after conversion13、S24S is strained with a faceaData carry out harmonic analysis, remove
The periodic response of data；
D, makes sample data；
E, the covariance matrix of sample data is sought；
F, the characteristic value and characteristic vector of covariance matrix are obtained；
G, the angle of characteristic vector is obtained；
H, output characteristic value variation diagram；
I, output characteristic vector angle variation diagram and statistic histogram.
2. a kind of borehole strain data exception extraction method based on principal component analysis according to claim 1, its feature
It is：Step d, described makes sample data, it is that the preprocessed data table in temporal sequence of harmonic analysis will be carried out after conversion
It is shown as Z1=[Z1(1),Z1(2),...,Z1(1440)],…,Zn=[Zn(1),Zn(2),...,Zn(1440) sample can], be obtained
Notebook data Y=[Z1,Z2,Z3,...,Zn]T, sample data Y (n × 1440) expression formula is：
3. a kind of borehole strain data exception extraction method based on principal component analysis according to claim 1, its feature
It is：Step e, the covariance matrix for seeking sample data, sample data Y (n × 1440) its covariance matrix CY(n×n)
Element γpqIt is calculated by formula (2),
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4. a kind of borehole strain data exception extraction method based on principal component analysis according to claim 1, its feature
It is：Step f, the characteristic value for obtaining covariance matrix is covariance matrix C to sample data Y (n × 1440)YCarry out
Eigenvalues Decomposition,
CY=R ∧ RT, (3)
In formula, ∧ (n × n) is the characteristic value diagonal matrix of size descending arrangement；R (n × 1) is relative with characteristic value diagonal matrix
The eigenvectors matrix answered, the list of feature values are shown as λ1,λ2,...,λn(λ1＞ λ2＞ ... ＞ λn)。
5. a kind of borehole strain data exception extraction method based on principal component analysis according to claim 1, its feature
It is：Step g, described to seek characteristic vector angle be to set characteristic vector as R=[V1 V2 ... Vn]T, characteristic vector angle is：
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Wherein, θ and φ represents characteristic vector angle, V respectivelyiAnd VjRespectively i-th and jth characteristic vector.
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| CN109031403B (en) * | 2018-08-20 | 2019-07-26 | 吉林大学 | A kind of borehole strain data exception extraction method based on S-K feature |
| CN109101954B (en) * | 2018-09-11 | 2020-11-27 | 吉林大学 | Method for removing tidal strain components of borehole strain data based on minimum noise separation |
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| CN109740453B (en) * | 2018-12-19 | 2022-03-29 | 吉林大学 | Satellite magnetic field data earthquake precursor anomaly extraction method based on wavelet transformation |
| CN109738939B (en) * | 2019-03-21 | 2022-06-21 | 蔡寅 | Earthquake precursor data anomaly detection method |
| CN110068857B (en) * | 2019-04-02 | 2020-02-04 | 吉林大学 | Swarm double-star magnetic field data earthquake precursor anomaly extraction method based on principal component analysis |
| CN110618458B (en) * | 2019-08-20 | 2020-11-27 | 吉林大学 | ICA-RA-based multi-band cascade correction method for drilling strain data |
| CN115758089A (en) * | 2022-11-08 | 2023-03-07 | 海南师范大学 | Borehole strain data prediction method |
| CN116204760B (en) * | 2023-01-16 | 2023-10-24 | 海南师范大学 | Drilling strain data anomaly extraction method based on GRU network |
| CN116202570B (en) * | 2023-02-17 | 2023-09-05 | 中国地震局地震预测研究所 | Multi-frequency surface wave calibration method and device |
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| 《关于用密集钻孔应变台网监测强震前兆的若干问题》;邱泽华;《地震学报》;20140731;第36卷(第4期);738-746 * |
| 《姑咱台钻孔应变观测值年变化的数值模拟解释》;杨少华等;《地震地质》;20161231;第38卷(第4期);1137-1144 * |
| 《钻孔应变观测现状与展望》;李海亮等;《地质学报》;20100630;第84卷(第6期);895-900 * |
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