CN110223490A - A method of rock slopes stability is judged based on warning grade - Google Patents
A method of rock slopes stability is judged based on warning grade Download PDFInfo
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Abstract
The invention discloses a kind of methods that rock slopes stability is judged based on warning grade, according to different warning grades for determining that the significance level that landslide occurs carries out same order division, the weight that different warning grades occur for determining landslide is calculated using analytic hierarchy process (AHP), weight is assigned respectively according to the installation position of monitoring device, it is introduced by the calculated weight of analytic hierarchy process (AHP) and determines whether landslide enters the subjective probability for facing the sliding stage, it merges multiple monitoring point warning grades and quantitatively judges landslide entirety into the probability for facing the sliding stage, when this probability is more than or equal to 50%, it can assert that the landslide has been in and face the sliding stage, landslide monitoring early warning platform can issue warning information accordingly.The present invention can accurately ignore wrong data, correct identification landslide hazard grade, single error data can be removed for judging the influence of landslide hazard grade, and in this, as the foundation of warning information publication according to the landslide Judging index of fused quantization, prevent the generation of the event of wrong report.
Description
Technical field
The present invention relates to Landslide Stabilities to monitor field, more particularly to a kind of warning grade that is based on judges that rock slopes are stablized
The method of property.
Background technique
It realizes at present and system early warning platform is based on to the intelligent real-time early warning monitoring on landslide more, which can be to existing
The Intelligent monitoring device data collected of field installation are constantly recorded and analyzed, and the monitoring according to embedded by cloud system is pre-
Alert model carries out blue, yellow, orange and red early warning grade classification to landslide hazard grade.It is answered in actual monitoring and warning
In, in order to guarantee the reliability and integrality of monitoring data, in rear crack, installation is greater than one displacement monitor, prison
The each group of data that device can be passed back by surveying early warning platform record and analyze.But existing monitoring and early warning platform is not right
Multi-group data is merged, the whole danger classes according only to single monitoring point highest warning grade as slope, and as
According to the foundation as hydropac publication, because the monitoring device of single monitoring point is easy to because certainly in practical engineering applications
Right factor or human factor are disturbed, until reporting early warning platform to the danger classes on landslide by mistake, set forth herein a kind of energy
Enough based on multiple monitoring point difference danger classes to the method for slope monolithic stability sex determination.
Existing monitoring and early warning platform does not merge multi-group data, according only to single monitoring point highest warning grade
As the whole danger classes on slope, and the foundation as hydropac publication on this basis, because in practical engineering application
In the monitoring device of single monitoring point be easy to be disturbed because of natural cause or human factor, until making early warning platform to landslide
Danger classes is reported by mistake.
Summary of the invention
In order to overcome landslide monitoring early warning platform because single monitoring point is caused Deformation Monitoring rate to be increased sharply by disturbance, and is drawn
The problem of warning information is accidentally sent out is sent out, the invention proposes a kind of method that rock slopes stability is judged based on warning grade, packets
Include following steps:
S1. according to different warning grades for determining that the significance level that landslide occurs carries out same order division；
S2. the weight that different warning grades occur for determining landslide is calculated using analytic hierarchy process (AHP)；
S3. weight is assigned respectively according to the installation position of monitoring device；
S4. it is introduced by the calculated weight of analytic hierarchy process (AHP) and determines whether landslide enters the subjective probability for facing the sliding stage；
S5. multiple monitoring point warning grades are merged and quantitatively judge landslide entirety into the probability for facing the sliding stage, when this probability
When more than or equal to 50%, it can assert that the landslide has been in and face the sliding stage, landslide monitoring early warning platform can be issued pre- accordingly
Alert information.
Further, the step S1 includes following sub-step:
S11. by different warning grades for judging that the significance level of slope stability carries out uniform increments step by step；
S12. warning grade two-by-two is faced the importance degree in sliding stage and compared by 1-9's to judging whether landslide enters again
Scale is divided.
Further, in the step S12, different warning grades include: blue early warning B, yellow early warning Y, orange warning O
With red early warning R, and for judging that the significance level of slope stability carries out uniform increments step by step.
Further, in the step S13, the scale of 1-9 specifically:
Scale 1 indicates that two elements are compared, and has no less important；
Scale 3 indicates that two elements are compared, the former is slightly more important than the latter；
Scale 5 indicates that two elements are compared, the former is more obvious than the latter important；
Scale 7 indicates that two elements are compared, the former is stronger than the latter important；
Scale 9 indicates that two elements are compared, the former is more extremely important than the latter；
Scale 2,4,6 and 8 indicates the median of above-mentioned adjacent judgement.
Further, in the step S12, include: by the result that the scale of 1-9 is divided
(R:B)=9；(R:Y)=6；(R:O)=3；(O:B)=6；(O:Y)=3；(Y:B)=3；
(C can be used in the above results1:C2)=X expression, i.e. warning grade C1With warning grade C2For the important of same event
Degree is X, and has (C2:C1)=1/X；
It can thus be concluded that judgment matrix A:
Further, in the step S2, judgment matrix A consistent for one is exactly phase after each row normalization
The weight vectors answered, therefore using with method is exactly the arithmetic average using this 4 column vectors as weight vectors, specifically calculates step
It is as follows:
S21. the element of judgment matrix A is pressed into row normalization；
S22. each column after normalization are added again；
S23. the vector after finally will add up is divided by 4 up to weight vectors；
It can be obtained according to above-mentioned calculating step:
W=[w1, w2, w3, w4]T=[0.0466,0.1052,0.2571,0.5912]T
Wherein w1,w2,w3,w4Blue early warning B, yellow early warning Y, orange warning O and red early warning R are respectively represented for sentencing
Whether fixed landslide enters the weight for facing the sliding stage.
Further, in the step S3, since the gliding mass of rock slopes has stronger globality, the marginal slit after same
It is almost the same to sew on the change in displacement rate that laid surface displacement device is monitored, special monitoring point is not present, therefore can be with
Assign each monitoring site to equal weight coefficient, it may be assumed that C=1/n, wherein C is the weight of monitoring site, and n is monitoring site
Number.
Further, in the step S4, since early warning event is to occur step by step, the criterion of warning grade is only tired with slope
Meter displacement tangential angle is related, therefore warning grade weight can be overlapped to obtain:
pb=0.05
py=0.05+0.10=0.15
po=0.05+0.10+0.26=0.41
pr=0.05+0.10+0.26+0.59=1
Wherein pb,py,po,prIt is all larger than equal to 0 and less than or equal to 1, meets the definition of subjective probability, therefore can be regarded
To judge landslide into the subjective probability for facing the sliding stage, i.e., to the carry out quantification treatment of warning grade by warning grade.
Further, in the step S5, by the result of step S4 quantification treatment and each monitoring location weight coefficient into
Row is combined and is calculated:
P=C (pb·n1+py·n2+po·n3+pr·n4) 100%
Wherein n1+n2+n3+n4=n, P are to judge to come down after carrying out multisource data fusion according to the warning grade of each monitoring point
The probability of unstability can determine that landslide comes into and face sliding stage, landslide monitoring when probability P is greater than or equal to 50%
Early warning platform can issue warning information on this basis.
Further, in rank order filtering under calculating single criterion, it is necessary to carry out consistency check, specific steps are such as
Under:
S61. coincident indicator C.I. is calculated:
Wherein, λmaxFor the maximum eigenvalue of judgment matrix A, m is the matrix order of judgment matrix A；
S62. corresponding Aver-age Random Consistency Index R.I. is searched according to the order of judgment matrix A；
S63. consistency ration C.R. is calculated:
As consistency ration C.R. < 0.1, it is believed that the consistency of judgment matrix is acceptable.
The beneficial effects of the present invention are: the present invention can accurately ignore wrong data, correct to identify landslide hazard grade,
Single error data can be removed for judging the influence of landslide hazard grade according to the landslide Judging index of fused quantization,
And in this, as the foundation of warning information publication, the generation of the event of wrong report is prevented.
Specific embodiment
A kind of method that rock slopes stability is judged based on warning grade is present embodiments provided, specific as follows:
1, analytic hierarchy process (AHP) (Analytic Hierarchy Process, AHP) is a kind of practical multiple attribute decision making (MADM) side
Method, challenge is resolved into each compositing factor by it, and these factors are grouped to form recursive hierarchy structure by dominance relation,
The relative importance of factors in level is determined by way of comparing two-by-two, then the judgement of integrated decision-making person, determines decision
Total sequence of scheme relative importance.Whole process embodies the essential characteristic of the policy-making thought of people, that is, decompose, judge it is comprehensive
It closes.The present embodiment faces sliding stage significance level difference for that should determine that landslide enters to different warning grades using analytic hierarchy process (AHP)
Assign different important scales.
It, can be by the important journey between two different warning grades for judging slope stability according to Consistent Matrix method
Degree is divided into 9 i.e. 1-9 of scale, in which:
Scale 1 indicates that two elements are compared, and has no less important；
Scale 3 indicates that two elements are compared, the former is slightly more important than the latter；
Scale 5 indicates that two elements are compared, the former is more obvious than the latter important；
Scale 7 indicates that two elements are compared, the former is stronger than the latter important；
Scale 9 indicates that two elements are compared, the former is more extremely important than the latter；
Scale 2,4,6,8 indicates the median of above-mentioned adjacent judgement.
By different warning grades for judging that the significance level of slope stability carries out uniform increments step by step, the early warning etc.
Grade from low to high are as follows: blue early warning B, yellow early warning Y, orange warning O and red early warning R, then will two-by-two warning grade to judgement
Whether landslide compares into the importance degree for facing the sliding stage is divided to obtain by the scale of 1-9:
(R:B)=9；(R:Y)=6；(R:O)=3；(O:B)=6；(O:Y)=3；(Y:B)=3；
(C can be used in the above results1:C2)=X expression, i.e. warning grade C1With warning grade C2For the important of same event
Degree is X, and has (C2:C1)=1/X；
It can thus be concluded that judgment matrix A:
Judgment matrix A consistent for one is exactly corresponding weight vectors after its each row normalization.Therefore it uses
It is exactly the arithmetic average using this 4 column vectors as weight vectors with method.
Its specific steps performed is as follows:
Step 1: the element of judgment matrix A presses row normalization；
Step 2: each column after normalization are added；
Step 3: the vector after will add up is divided by 4 up to weight vectors.
It can be obtained according to calculating:
W=[w1, w2, w3, w4]T=[0.0466,0.1052,0.2571,0.5912]T
Wherein w1,w2,w3,w4Blue early warning B, yellow early warning Y, orange warning O and red early warning R are respectively represented for sentencing
Whether fixed landslide enters the weight for facing the sliding stage.
2, in rank order filtering under calculating single criterion, it is necessary to carry out consistency check.When judgment matrix deviates unanimously
Property it is excessive when, the degree of reliability of this approximate evaluation also just it is doubtful.Therefore it needs to examine the consistency of judgment matrix
It tests, specific steps are as follows:
(1) coincident indicator C.I. is calculated:
Wherein, λmaxFor the maximum eigenvalue of judgment matrix A, m is the matrix order of judgment matrix A；
(2) corresponding Aver-age Random Consistency Index R.I. is searched according to the order of judgment matrix A:
(3) consistency ration C.R. is calculated
As C.R. < 0.1, it is believed that the consistency of judgment matrix is acceptable.
Through consistency check:
Meet coherence request.
3, since the gliding mass of rock slopes has stronger globality, the surface displacement laid on same rear crack
The change in displacement rate that device is monitored is almost the same, special monitoring point is not present, therefore can assign each monitoring site to phase
Same weight coefficient, it may be assumed that C=1/n, wherein C is the weight of monitoring site, and n is the number of monitoring site.
Meanwhile monitoring location can be minimized cloth and set up an office for judging that the weight of slope stability assigns mean value
Error of the position for measurement slope stability.
4, subjective probability is introduced according to the weight that analytic hierarchy process (AHP) calculates.Since early warning event is to occur step by step, early warning etc.
The criterion of grade is only related with slope accumulative displacement tangential angle, therefore warning grade weight can be overlapped to obtain:
pb=0.05
py=0.05+0.10=0.15
po=0.05+0.10+0.26=0.41
pr=0.05+0.10+0.26+0.59=1
Wherein pb,py,po,prIt is all larger than equal to 0 and less than or equal to 1, meets the definition of subjective probability, therefore can be regarded
To judge that landslide into the subjective probability for facing the sliding stage, i.e., has carried out quantification treatment to warning grade by warning grade.
Therefore this quantized result is combined with each monitoring location weight coefficient and is calculated:
P=C (pb·n1+py·n2+po·na+pr·n4) 100%
Wherein n1+n2+n3+n4=n, P are to judge to come down after carrying out multisource data fusion according to the warning grade of each monitoring point
The probability of unstability can determine that landslide comes into and face sliding stage, landslide monitoring when this probability is greater than or equal to 50%
Early warning platform can issue warning information on this basis.
The above is only a preferred embodiment of the present invention, it should be understood that the present invention is not limited to described herein
Form should not be regarded as an exclusion of other examples, and can be used for other combinations, modifications, and environments, and can be at this
In the text contemplated scope, modifications can be made through the above teachings or related fields of technology or knowledge.And those skilled in the art institute into
Capable modifications and changes do not depart from the spirit and scope of the present invention, then all should be in the protection scope of appended claims of the present invention
It is interior.
Claims (10)
1. a kind of method for judging rock slopes stability based on warning grade, which comprises the following steps:
S1. according to different warning grades for determining that the significance level that landslide occurs carries out same order division；
S2. the weight that different warning grades occur for determining landslide is calculated using analytic hierarchy process (AHP)；
S3. weight is assigned respectively according to the installation position of monitoring device；
S4. it is introduced by the calculated weight of analytic hierarchy process (AHP) and determines whether landslide enters the subjective probability for facing the sliding stage；
S5. multiple monitoring point warning grades are merged and quantitatively judge landslide entirety into the probability for facing the sliding stage, when this probability is greater than
When equal to 50%, it can assert that the landslide has been in and face the sliding stage, landslide monitoring early warning platform can issue early warning letter accordingly
Breath.
2. a kind of method for judging rock slopes stability based on warning grade according to claim 1, which is characterized in that
The step S1 includes following sub-step:
S11. by different warning grades for judging that the significance level of slope stability carries out uniform increments step by step；
S12. warning grade two-by-two is faced the importance degree in sliding stage and compares scale by 1-9 to judging whether landslide enters again
It is divided.
3. a kind of method for judging rock slopes stability based on warning grade according to claim 2, which is characterized in that
In the step S12, different warning grades include: blue early warning B, yellow early warning Y, orange warning O and red early warning R, and right
In to judging that the significance level of slope stability carries out uniform increments step by step.
4. a kind of method for judging rock slopes stability based on warning grade according to claim 3, which is characterized in that
In the step S13, the scale of 1-9 specifically:
Scale 1 indicates that two elements are compared, and has no less important；
Scale 3 indicates that two elements are compared, the former is slightly more important than the latter；
Scale 5 indicates that two elements are compared, the former is more obvious than the latter important；
Scale 7 indicates that two elements are compared, the former is stronger than the latter important；
Scale 9 indicates that two elements are compared, the former is more extremely important than the latter；
Scale 2,4,6 and 8 indicates the median of above-mentioned adjacent judgement.
5. a kind of method for judging rock slopes stability based on warning grade according to claim 4, which is characterized in that
In the step S12, include: by the result that the scale of 1-9 is divided
(R:B)=9；(R:Y)=6；(R:O)=3；(O:B)=6；(O:Y)=3；(Y:B)=3；
(C can be used in the above results1:C2)=X expression, i.e. warning grade C1With warning grade C2Significance level for same event is
X, and have (C2:C1)=1/X；
It can thus be concluded that judgment matrix A:
6. a kind of method for judging rock slopes stability based on warning grade according to claim 5, which is characterized in that
In the step S2, judgment matrix A consistent for one is exactly corresponding weight vectors after each row normalization, therefore adopts
Using with method is exactly the arithmetic average using this 4 column vectors as weight vectors, and steps are as follows for specific calculating:
S21. the element of judgment matrix A is pressed into row normalization；
S22. each column after normalization are added again；
S23. the vector after finally will add up is divided by 4 up to weight vectors；
It can be obtained according to above-mentioned calculating step:
W=[w1, w2, w3, w4]T=[0.0466,0.1052,0.2571,0.5912]T
Wherein w1,w2,w3,w4Blue early warning B, yellow early warning Y, orange warning O and red early warning R are respectively represented for determining to come down
Whether the weight for facing the sliding stage is entered.
7. a kind of method for judging rock slopes stability based on warning grade according to claim 6, which is characterized in that
In the step S3, since the gliding mass of rock slopes has stronger globality, the earth's surface laid on same rear crack
The change in displacement rate that shifter is monitored is almost the same, special monitoring point is not present, therefore each monitoring site can be assigned
Give equal weight coefficient, it may be assumed that C=1/n, wherein C is the weight of monitoring site, and n is the number of monitoring site.
8. a kind of method for judging rock slopes stability based on warning grade according to claim 7, which is characterized in that
In the step S4, since early warning event is to occur step by step, the criterion of warning grade only has with slope accumulative displacement tangential angle
It closes, therefore warning grade weight can be overlapped to obtain:
pb=0.05
py=0.05+0.10=0.15
po=0.05+0.10+0.26=0.41
pr=0.05+0.10+0.26+0.59=1
Wherein pb,py,po,prIt is all larger than equal to 0 and less than or equal to 1, meets the definition of subjective probability, therefore can be regarded as by pre-
Alert grade judgement landslide enters the subjective probability for facing the sliding stage, i.e., to the carry out quantification treatment of warning grade.
9. a kind of method for judging rock slopes stability based on warning grade according to claim 8, which is characterized in that
In the step S5, the result of step S4 quantification treatment is combined with each monitoring location weight coefficient and is calculated:
P=C (pb·n1+py·n2+po·na+pr·n4) 100%
Wherein n1+n2+n3+n4=n, P are that judgement landslide will after carrying out multisource data fusion according to the warning grade of each monitoring point
The probability of unstability, when probability P be greater than or equal to 50% when, that is, can determine that landslide comes into and face the sliding stage, landslide monitoring early warning
Platform can issue warning information on this basis.
10. a kind of method for being judged rock slopes stability based on warning grade according to claim 6, feature are existed
In in rank order filtering under calculating single criterion, it is necessary to consistency check is carried out, the specific steps of which are as follows:
S61. coincident indicator C.I. is calculated:
Wherein, λmaxFor the maximum eigenvalue of judgment matrix A, m is the matrix order of judgment matrix A；
S62. corresponding Aver-age Random Consistency Index R.I. is searched according to the order of judgment matrix A；
S63. consistency ration C.R. is calculated:
As consistency ration C.R. < 0.1, it is believed that the consistency of judgment matrix is acceptable.
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| CN112085921A (en) * | 2020-08-20 | 2020-12-15 | 青岛地质工程勘察院(青岛地质勘查开发局) | Landslide comprehensive monitoring and early warning method based on displacement and power multi-parameter |
| CN112085921B (en) * | 2020-08-20 | 2022-11-11 | 青岛地质工程勘察院(青岛地质勘查开发局) | Landslide comprehensive monitoring and early warning method based on displacement and power multi-parameter |
| CN117198018A (en) * | 2023-10-09 | 2023-12-08 | 长安大学 | Slope stability early warning method based on multisource monitoring data change |
| CN117493833A (en) * | 2023-12-29 | 2024-02-02 | 江西飞尚科技有限公司 | Landslide deformation stage identification method, landslide deformation stage identification system, storage medium and computer |
| CN117493833B (en) * | 2023-12-29 | 2024-04-09 | 江西飞尚科技有限公司 | Landslide deformation stage identification method, landslide deformation stage identification system, storage medium and computer |
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