CN117198018A - Slope stability early warning method based on multisource monitoring data change - Google Patents
Slope stability early warning method based on multisource monitoring data change Download PDFInfo
- Publication number
- CN117198018A CN117198018A CN202311298273.4A CN202311298273A CN117198018A CN 117198018 A CN117198018 A CN 117198018A CN 202311298273 A CN202311298273 A CN 202311298273A CN 117198018 A CN117198018 A CN 117198018A
- Authority
- CN
- China
- Prior art keywords
- early warning
- slope
- monitoring
- warning
- early
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 210
- 238000000034 method Methods 0.000 title claims abstract description 38
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 26
- 230000001575 pathological effect Effects 0.000 claims description 25
- 238000012360 testing method Methods 0.000 claims description 11
- 239000002689 soil Substances 0.000 claims description 10
- 230000001687 destabilization Effects 0.000 claims description 9
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 7
- 238000011156 evaluation Methods 0.000 abstract description 4
- 230000000694 effects Effects 0.000 description 7
- 230000002411 adverse Effects 0.000 description 6
- 238000006073 displacement reaction Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000036962 time dependent Effects 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000035605 chemotaxis Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 239000003673 groundwater Substances 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 238000004062 sedimentation Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000000087 stabilizing effect Effects 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
Landscapes
- Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)
Abstract
The invention discloses a slope stability early warning method based on multisource monitoring data change, which relates to the technical field of geotechnical engineering and geological engineering, and comprises the following steps: classifying the monitoring amount of the slope; classifying the duration curves of the main monitoring amount in the whole life cycle of the side slope; determining slope single-point early warning grading standards according to the main monitoring quantity monitoring points; respectively determining a slope linear early warning grading standard, a slope section early warning grading standard and a slope three-dimensional early warning grading standard; by comparing the slope single-point real-time monitoring data with the four early warning grading standards, the slope single-point early warning, the slope linear early warning, the slope section early warning and the slope three-dimensional early warning are respectively realized. Meanwhile, the monitoring quantity type and the monitoring point position number are considered, so that the method is easy to be understood by masses and popularized and used in various slope monitoring projects, single-point early warning, linear early warning, section early warning and three-dimensional early warning of a single slope are realized, and stability early warning and evaluation of the monitored slope points, lines, faces and bodies can be realized.
Description
Technical Field
The invention relates to the technical field of geotechnical engineering and geological engineering, in particular to a slope stability early warning method based on multisource monitoring data change.
Background
In human engineering such as highway, railway, water conservancy, house construction and mining, and natural mountain areas, side slopes are visible everywhere and numerous. Under the conditions of extreme rainfall weather, strong earthquake action, complex engineering geological conditions, great engineering disturbance and human treatment errors, the stability of the side slope is extremely easy to be reduced, so that the side slope is induced to be unstable and damaged, and ecological damage, casualties, building damage, vehicle damage, traffic jam, river damming, property loss and the like are caused. Each year, reports are common in messages concerning slope destabilization damage. Therefore, in order to avoid instability damage to the slope, different monitoring means are adopted to dynamically analyze and evaluate the slope stability. At present, due to the fact that the monitoring quantity types of the side slopes are multiple, the monitoring points of the side slopes are multiple, and the side slope stability early warning theories are strong, the simple, easy-to-understand and easy-to-use side slope stability early warning method considering the monitoring quantity types and the monitoring point positions is not available, and the method is used for effectively assisting urgent demands of disaster prevention, disaster avoidance and disaster control of common masses. Therefore, a slope stability early warning method based on multi-source monitoring data change is needed to solve the slope monitoring early warning problem.
Disclosure of Invention
The invention aims to provide a slope stability early warning method based on multi-source monitoring data change, and meanwhile, the monitoring quantity type and the monitoring point position quantity are considered, so that the method is easy to popularize and use in various slope monitoring projects after being understood by masses, single-point early warning, linear early warning, section early warning and three-dimensional early warning of a single slope are realized, and the stability early warning and evaluation of the points, lines, surfaces and bodies of the monitoring slope can be realized.
In order to achieve the above purpose, the invention provides a slope stability early warning method based on multisource monitoring data change, which comprises the following steps:
s1, classifying slope monitoring quantities;
s2, classifying the duration curves of the main monitoring amount in the whole life cycle of the side slope;
s3, determining slope single-point early warning grading standards according to the main monitoring quantity monitoring points;
s4, respectively determining a slope linear early warning grading standard, a slope section early warning grading standard and a slope three-dimensional early warning grading standard;
s5, comparing the slope single-point real-time monitoring data with the four early warning grading standards, and respectively realizing slope single-point early warning, slope linear early warning, slope section early warning and slope three-dimensional early warning.
Preferably, in step S1, the monitoring quantity of the side slope includes a primary monitoring quantity and a secondary monitoring quantity, and the types of the primary monitoring quantity are divided into an anchor rod axial force, an anchor rope pulling force and a slope deformation; the types of the auxiliary monitoring quantity comprise rainfall, earthquake, engineering disturbance, soil humidity and water pressure of the ground.
Preferably, in step S2, the duration curve types of the anchor rod shaft force, the anchor rope tension and the slope deformation in the whole life cycle of the side slope are divided into six types: i-stable form; II-single slow-change steady-state trend; III-breathing steady state; IV-single slow-change destabilization; v-breathing instability type; VI-mutant destabilization type.
Preferably, in step S3, a slope single-point early warning level WL is issued according to the master monitoring point p The method is divided into a main category 2 and a sub category 9, wherein the main category 2 comprises health warning-free and pathological warning, and the sub category 9 comprises warning-free, blue warning, blue warning+, yellow warning, yellow warning+, orange warning, orange warning+, red warning and red warning+.
Preferably, in step S3,
wherein:
WL p -slope single point pre-warning level;
V i，w primary monitored magnitude V i Corresponding early warning values;
V i -primary monitored magnitude, i e {1,2,3}, V 1 Represents the axial force value of the anchor rod, V 2 Representing the tension value of the anchor rod, V 3 Representing a slope deformation value;
V f，j secondary monitoring magnitude, j e {1,2,3,4,5}, V f，1 Represents the accumulated rainfall of the earlier month, V f，2 Representing the number of early month seismic events, V f，3 Representing the number of early moon man Cheng Raodong events, V f，4 Representing the humidity of the soil body in real time, taking the humidity at the sensitive point position or the average humidity of all the point positions of slope humidity monitoring, V f，5 Representing real-time underground water pressure, and taking water pressure at sensitive points or average water pressure of all points monitored by slope water pressure;
ζ 1 the dimensionless coefficient for judging the blue early warning and the yellow early warning is 1.2-1.3;
ζ 2 the dimensionless coefficient for judging the yellow early warning and the orange early warning is 1.4-1.5;
ζ 3 the dimensionless coefficient for judging the orange early warning and the red early warning takes 1.7-1.8.
Preferably, in step S3, the function f (V) related to the constraint of formula (1) f，j ) Satisfies the formula (2), f (V) f，j ) The value of (2) depends on the change condition of the side slope auxiliary monitoring quantity, and is as follows:
wherein:
V f，jw secondary monitoring quantity early warning value, j epsilon {1,2,3,4,5}, V f，1w Representing early warning value of accumulated rainfall in early month, taking 100-200 mm and V f，2w The early warning value representing the number of early-stage month earthquake events is 1-3V f，3w Representing early warning value of the number of the events of the early moon worker Cheng Raodong, taking 1-3V f，4w Representing the early warning value of the humidity of the soil body, and obtaining 20-23% of corresponding mass water content, V f，5w Representing the pre-warning value of the underground water pressure, and taking 3kPa to 10kPa.
Preferably, in step S4, the slope line-shaped early warning classification criteria are as follows:
the monitoring slope is respectively provided with an anchor rod, an anchor rope, deformation, rainfall, humidity, water pressure, video and vibration monitoring points, wherein n1, n2, n3, n4, n5, n6, n7 and n8 are arranged, m measuring lines are arranged, the numbers of the measuring lines are respectively #L1, # L2, … …, # Lk and … … #Lm, m measuring line sections are arranged, the numbers of the measuring lines are respectively #S1, # S2, … …, # Sk and … … #Sm, and for the measuring line with the number #Lk, the total n of the monitoring points with the main monitoring quantity are assumed to be arranged on the measuring line #Lk For the section of the test line numbered #Sk, a total of n is assumed to be the monitoring points with the master monitoring amount #Sk A plurality of;
when there is n on the #Lk line #Lk，w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be L ＝n #Lk，w *100/n #Lk ，R L In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the test line numbered as # Lk, the early warning level WL of the # Lk test line #Lk As shown in formula (3):
wherein:
η 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
η 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
η 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
Preferably, in step S4, the slope section early warning classification criteria are as follows:
when the # Sk line has n on its cross section #Sk，w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be S ＝n #Sk，w *100/n #Sk ，R S In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the cross section of the # Sk measuring line, the early warning level WL of the cross section of the # Sk measuring line #Sk As shown in formula (4):
wherein:
δ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
δ 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
δ 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
Preferably, in step S4, the three-dimensional early warning grading criteria of the side slope are as follows:
when the side slope is counted as n T When the monitoring points of the master monitoring quantity trigger the pathological early warning, R is the other T ＝n T *100/(n1+n2+n3)，R T For triggering the ratio of the main monitoring quantity monitoring point of the pathological early warning to the anchor rod, the anchor cable and the deformation total monitoring point, the three-dimensional early warning level WL of the side slope T As shown in formula (5):
wherein:
ξ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
ξ 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
ξ 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
Therefore, the slope stability early warning method based on the multisource monitoring data change has the following technical effects:
(1) The method can consider the type of the monitoring quantity and the number of the monitoring points at the same time;
(2) The method is easy to be understood by the masses and popularized and used in various slope monitoring projects;
(3) The method realizes single-point early warning, linear early warning, section early warning and three-dimensional early warning of a single slope at the same time, and can realize early warning and evaluation of the stability of the monitored slope points, lines, surfaces and bodies.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
FIG. 1 is a block diagram of a slope stability early warning method based on multiple monitoring quantities;
FIG. 2 is a graph of the type of time-dependent change in the shaft force of the anchor rod over the entire life cycle of the slope;
fig. 3 is a graph of the type of time-dependent change in cable tension over the entire life cycle of the side slope;
FIG. 4 is a time-varying curve type of deformation over the entire life cycle of the slope;
FIG. 5 is a schematic view of a slope monitoring arrangement;
FIG. 6 is a schematic cross-sectional view of a side slope # Lk line;
FIG. 7 is a schematic diagram of an A-side slope monitoring arrangement
FIG. 8 is a schematic cross-sectional view of the line Δslope #L2.
Detailed Description
The technical scheme of the invention is further described below through the attached drawings and the embodiments.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art. Such other embodiments are also within the scope of the present invention.
It should be further understood that the above-described embodiments are only for explaining the present invention, the protection scope of the present invention is not limited thereto, and any person skilled in the art should be able to substitute or change the technical solution according to the present invention and the inventive concept thereof within the scope of the present invention.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be considered part of the specification where appropriate.
The disclosures of the prior art documents cited in the present specification are incorporated by reference in their entirety into the present invention and are therefore part of the present disclosure.
Example 1
As shown in FIG. 1, the invention provides a slope stability early warning method based on multi-source monitoring data change, which comprises the steps of firstly classifying the monitoring quantity of a slope and classifying the duration curve of the main monitoring quantity in the whole life cycle of the slope, further determining single-point early warning classification standards of the slope, and further determining linear early warning classification standards, section early warning classification standards and three-dimensional early warning classification standards of the slope. By comparing the slope single-point real-time monitoring data with the four early warning grading standards, the slope single-point early warning, the slope linear early warning, the slope section early warning and the slope three-dimensional early warning can be respectively realized, and the method specifically comprises the following steps:
s1, classifying monitoring quantity of side slope
The classification of the monitoring amount of the side slope is shown in the table 1, and the monitoring amount of the side slope is divided into a main monitoring amount and a sub-monitoring amount. Comprehensive factors such as economy and convenience are comprehensively considered, and the types of main monitoring measures are divided into anchor rod axial force, anchor rope tension and slope deformation. The types of the auxiliary monitoring quantity comprise rainfall, earthquake, engineering disturbance, soil humidity and water pressure of the ground. The slope deformation refers to any deformation monitored based on GNSS monitoring points, inclinometry monitoring points, relative displacement monitoring points and the like. For a general slope, the main monitoring amount can directly reflect the dynamic stability condition of the slope, and the auxiliary monitoring amount is only an inducing factor reflecting the dynamic stability of the slope and can assist the main monitoring amount to judge the dynamic stability condition of the slope. The anchor rod axial force, the anchor rope tension and the slope deformation can be obtained regularly through a field-mounted reinforcement meter, an anchor rope meter and a deformation sensor. The rainfall can be obtained in real time through a rainfall gauge installed on site. The earthquake can be obtained in real time through a China earthquake table network or a vibration sensor installed on site. Engineering disturbance can be obtained in real time through video shooting equipment on site. Soil humidity can be obtained periodically through a humidity sensor. The groundwater pressure may be periodically obtained by a water pressure sensor. For slope early warning, the method of the patent takes the dynamic change of the main monitoring quantity as a main basis and takes the dynamic change of the auxiliary monitoring quantity as an auxiliary basis. It should be noted that, for a certain monitoring slope object, only the primary monitoring amount and no secondary monitoring amount can also be used for carrying out early warning by the method of the patent, and only one of the primary monitoring amounts can also be used for carrying out early warning by the method of the patent.
TABLE 1 side slope monitoring quantity classification table
S2, classifying main monitoring quantity duration curves in slope full life cycle
As shown in table 1, the method mentioned in this patent classifies the main monitoring amount type into three types: the anchor rod shaft force, the anchor rope tension and the slope body are deformed. In the following, classification and explanation will be made for each main monitor duration curve in the full life cycle of the side slope.
As shown in fig. 2-4, the types of curves of the anchor rod axial force, the anchor rope tension and the slope deformation duration in the whole life cycle of the side slope can be divided into six types: i-stable form; II-single slow-change steady-state trend; III-breathing steady state; IV-single slow-change destabilization; v-breathing instability type; VI-mutant destabilization type. In the whole life cycle of the side slope, the early warning value V of the side slope in a stable state exists respectively in the axial force of the anchor rod, the tensile force of the anchor rope and the deformation of the slope body 1，w 、V 2，w And V is equal to 3，w 。V 1，w 、V 2，w And V is equal to 3，w The value of the (C) can be reasonably determined according to slope initial monitoring duration data, similar engineering monitoring data, numerical simulation analysis results, design parameters and the like. Especially, the early warning value V of the tension of the anchor cable 2，w The anchor cable pretightening force should be taken or a value slightly greater than the anchor cable pretightening force. The anchor rod axial force value V 1 Tension value V of anchor rod 2 Are all positive in pull; the slope deformation takes a positive value in terms of vertical downward sedimentation or horizontal displacement or inclination deformation toward the slope.
I-stable form: in the whole life cycle of the side slope, adverse effects of factors such as climate and external interference on the side slope are negligible, the axial force of the anchor rod, the tensile force of the anchor rope and the deformation of the slope body do not exceed set early warning values, the overall trend of the time-varying curve of the three is basically kept horizontal, and the side slope is characterized to be in a relatively stable state. At this time, it is reasonable to believe that the side slope has a greater probability of continuously maintaining a steady state of health for a subsequent period of time.
II-single slow-onset stabilizing type: in the whole life cycle of the side slope, the adverse effects of factors such as climate and external interference on the side slope are accompanied, the axial force of the anchor rod, the tension of the anchor rope and the deformation of the slope body all exceed set early warning values, the overall trend of the time-varying curve of the anchor rod, the tension of the anchor rope and the deformation of the slope body tend to be horizontal after undergoing a relatively obvious increase, and the side slope is characterized by being temporarily stable after being slowly deformed once. At this time, under the continuous influence of factors such as climate and external interference, whether the side slope can continuously keep a stable health state in a subsequent time cannot be ensured, and the side slope is in a first representation form of a pathological state.
III-breathing chemotaxis type: in the whole life cycle of the side slope, the adverse effects of factors such as climate and external interference on the side slope are accompanied, the axial force of the anchor rod, the tension of the anchor rope and the deformation of the slope body all exceed set early warning values, the overall trend of the time-varying curve of the anchor rod, the tension of the anchor rope and the deformation of the slope body tend to be horizontal after undergoing a plurality of relatively obvious intermittent increases, and the side slope is characterized as tending to be temporarily stable after undergoing a plurality of intermittent slow deformations. At this time, under the continuous influence of factors such as climate and external interference, whether the side slope can continuously keep a stable health state in a subsequent time cannot be ensured, and the side slope is in a second representation form of a pathological state.
IV-single ramp destabilization: in the whole life cycle of the side slope, the adverse effects of factors such as climate and external interference on the side slope are accompanied, the axial force of the anchor rod, the tension of the anchor rope and the deformation of the slope body all exceed preset early warning values, the overall trend of the time-varying curve of the anchor rod, the tension of the anchor rope and the deformation of the slope body are accelerated to increase after undergoing a relatively obvious increase, the side slope is characterized by gradually generating instability and damage after undergoing a slow deformation, and the side slope is in a third representation form of a pathological state.
V-breathing instability type: in the whole life cycle of the side slope, the adverse effects of factors such as climate and external interference on the side slope are accompanied, the axial force of the anchor rod, the tension of the anchor rope and the deformation of the slope body all exceed set early warning values, the overall trend of the three time-varying curves is accelerated to grow after being subjected to a plurality of relatively obvious intermittent increases, the side slope is characterized by gradually generating instability damage after being subjected to a plurality of intermittent slow deformations, and the side slope is in a fourth expression form of a disease state.
VI-mutant destabilization type: in the whole life cycle of the side slope, the axial force of the anchor rod, the tension of the anchor rope and the deformation of the slope body exceed preset early warning values along with adverse effects of factors such as climate and external interference on the side slope, the overall trend of the three time-varying curves undergoes an obvious acceleration increase, and the side slope is characterized by sudden unstable damage. At this time, the slope eventually becomes unstable and destroyed, which is the fifth manifestation of the slope being in a pathological state.
S3, determining single-point early warning grading standard of side slope
The single-point early warning grading standard of the side slope is shown in the formula (1) and the table 2. As can be seen from Table 2, the single-point early warning level WL of the side slope p Is divided into 2 major classes and 9 minor classes. The 2 main categories include health alarm-free and pathological early warning. Subclasses 9 include no warning, blue warning+, yellow warning, yellow warning+, orange warning, orange warning+, red warning, and red warning+. The single point of the representative slope without early warning is stable, and the closer the early warning level is to the red early warning + the representative slope is unstable. For a single point of the side slope, when any one of blue early warning, blue early warning+, yellow early warning, yellow early warning+, orange early warning, orange early warning+, red early warning and red early warning+ occurs on the side slope, a sick early warning should be issued to remind relevant units and personnel of taking precautions. As can be seen from the description of (1), the slope single-point early warning level WL p From the main monitored value V i And the auxiliary monitoring value V f，j And (5) jointly determining.
TABLE 2 Single-point early warning hierarchical table for side slope
Wherein:
WL p -slope single point pre-warning level;
V i，w primary monitored magnitude V i Corresponding early warning values;
V i -primary monitored magnitude, i e {1,2,3}, V 1 Represents the axial force value of the anchor rod, V 2 Representing the tension value of the anchor rod, V 3 Representing a slope deformation value;
V f，j secondary monitoring magnitude, j e {1,2,3,4,5}，V f，1 Represents the accumulated rainfall of the earlier month, V f，2 Representing the number of early month seismic events, V f，3 Representing the number of early moon man Cheng Raodong events, V f，4 Representing the humidity of the soil body in real time (the humidity at the sensitive point position or the average humidity of all the point positions which can be monitored by the humidity of the slope), V f，5 Representing real-time underground water pressure (water pressure at sensitive points or average water pressure of all points of the water pressure monitoring of the side slope);
the dimensionless coefficient for judging the blue early warning and the yellow early warning is adopted, and the suggested value is 1.2-1.3;
the dimensionless coefficient for judging the yellow early warning and the orange early warning is adopted, and the recommended value is 1.4-1.5;
the dimensionless coefficient for judging the orange early warning and the red early warning is 1.7-1.8 in recommended value.
The function f (V) related to the constraint of the formula (1) f，j ) Satisfying the formula (2). f (V) f，j ) The value of (2) depends on the change condition of the side slope auxiliary monitoring quantity, and is as follows:
wherein:
V f，w secondary monitoring quantity early warning value, j epsilon {1,2,3,4,5}, V f，1w Representing early warning value of accumulated rainfall (100-200 mm is recommended) of earlier month, V f，2w Representing early warning value (1-3 are recommended) of early month earthquake event quantity, V f，3w Representing early warning value of the number of the events of the early moon worker Cheng Raodong (1-3 are recommended), V f，4w Representing the early warning value of the soil humidity (suggesting that the water content corresponding to the mass is 20% -23%) V f，5w Representing the pre-warning value of underground water pressureIt is recommended to take 3kPa to 10 kPa).
The monitoring points capable of issuing slope single-point early warning are all master monitoring quantity monitoring points.
S4, respectively determining a slope linear early warning grading standard, a slope section early warning grading standard and a slope three-dimensional early warning grading standard
S41, slope linear early warning grading standard
For a general slope, the corresponding monitoring scheme is shown in fig. 5. At this time, it is assumed that the monitoring slopes are respectively provided with anchor rods, anchor cables, deformation, rainfall, humidity, water pressure, video and vibration monitoring points n1, n2, n3, n4, n5, n6, n7 and n8, m (respectively numbered #L1, #L2, … …, # Lk, … … #Lm), and m (respectively numbered #S1, # S2, … …, # Sk, … … #Sm). As shown in FIG. 6, for the test line numbered #lk, it is assumed that the monitoring points provided with the master monitoring amount sum to n #Lk And each. For the section of the test line numbered #Sk, it is assumed that a total of n is set up for the monitoring points of the master monitoring amount #Sk And each.
When there is n on the #Lk line #Lk，w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be L ＝n #Lk，w *100/n #Lk ，R L In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the test line numbered as # Lk, the early warning level WL of the # Lk test line #Lk As shown in formula (3):
wherein:
η 1 -dimensionless coefficients for judging blue early warning and yellow early warning, and taking a suggested value of 20% -30%;
η 2 -dimensionless coefficients for judging orange warning and yellow warning, and taking a suggested value of 50% -60%;
η 3 -dimensionless coefficients for judging red early warning and orange early warning, the recommended value taking 70% -80%.
Equation (3) is the set slope linear early warning grading standard. WL (WL) #Lk The closer to the red early warning, the larger the line length of the instability of the slope test line is.
S42, slope section early warning grading standard
When the # Sk line has n on its cross section #Sk，w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be S ＝n #Sk，w *100/n #Sk ，R S In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the cross section of the # Sk measuring line, the early warning level WL of the cross section of the # Sk measuring line #Sk As shown in formula (4):
wherein:
δ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, and taking a suggested value of 20% -30%;
δ 2 -dimensionless coefficients for judging orange warning and yellow warning, and taking a suggested value of 50% -60%;
δ 3 -dimensionless coefficients for judging red early warning and orange early warning, the recommended value taking 70% -80%.
The formula (4) is the set slope section early warning grading standard. WL (WL) #Sk The closer to the red early warning, the larger the area of instability of the slope section is indicated.
S43, three-dimensional early warning grading standard for side slope
When the side slope is counted as n T When the monitoring points of the master monitoring quantity trigger the pathological early warning, R is the other T ＝n T *100/(n1+n2+n3)，R T For triggering the ratio of the main monitoring quantity monitoring point of the pathological early warning to the anchor rod, the anchor cable and the deformation total monitoring point, the three-dimensional early warning level WL of the side slope T As shown in formula (5):
wherein:
ξ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, and taking a suggested value of 20% -30%;
ξ 2 -dimensionless coefficients for judging orange warning and yellow warning, and taking a suggested value of 50% -60%;
ξ 3 -dimensionless coefficients for judging red early warning and orange early warning, the recommended value taking 70% -80%.
Equation (5) is the set slope section early warning grading standard. WL (WL) T The closer to the red early warning, the larger the volume of instability is generated in the three-dimensional whole of the slope.
S5, comparing the slope single-point real-time monitoring data with the four early warning grading standards, and respectively realizing slope single-point early warning, slope linear early warning, slope section early warning and slope three-dimensional early warning.
Example two
The method in the first embodiment is adopted to combine with the examples for comparison, and the specific steps are as follows:
as shown in FIG. 7, anchor rod monitoring points (14, the numbers are respectively V) are distributed on the slope A 1，1 、V 1，2 、……、V 1，14 ) Anchor cable monitoring points (9, the serial numbers are V respectively) 2，1 、V 2，2 、……、V 2，9 ) Deformation monitoring points (20, the serial numbers are V respectively) 3，1 、V 3，2 、……、V 3，20 ) And the rainfall monitoring points (1) and the video monitoring points (1) are used for respectively monitoring the axial force of the side slope anchor rod, the tension of the anchor rope, the horizontal displacement deformation, the rainfall and the engineering construction dynamics. The earthquake event dynamic can be obtained by inquiring the China earthquake table network every day. In fig. 7, the slope a has 3 monitoring lines, the numbers are #l1, #l2 and #l3 respectively, as shown in fig. 8, there are 3 anchor cable monitoring points and 5 deformation monitoring points on the #l2 measuring line, 6 anchor rod monitoring points, 3 anchor cable monitoring points and 9 deformation monitoring points in the #l2 measuring line section. Assume that all monitoring points of the slope work normally from 6 months 1 in 2020 to 12 months 30 in 2020.
At 12/30/2020, the monitored data were checked and verified for findings: 2 anchor rodsMonitoring point V 1，1 And V is equal to 1，6 The overall trend of the anchor rod axial force time-varying curve conforms to the abrupt instability and V 1，1 And V is equal to 1，6 The anchor rod axial force of the device reaches 1.85 times of a set anchor rod axial force early warning value; 1 anchor rope monitoring point V 2，2 The overall trend of the anchor cable tension time-varying curve accords with the abrupt instability, and V 2，2 The anchor cable tension reaches a set anchor cable tension early warning value which is 1.35 times; 3 deformation monitoring points V 3，4 、V 3，10 And V is equal to 3，18 The deformation time-varying curve of (2) is in accordance with the abrupt instability and V 3，4 、V 3，10 And V is equal to 3，18 The deformation of the steel plate reaches a set deformation early warning value which is 1.60 times; the accumulated rainfall in the early month is only 11mm; the number of early month seismic events is 0, and the number of early moon Cheng Raodong events is 20.
At this time, the slope single-point early warning analysis can be judged by adopting the formulas (1) and (2): anchor rod monitoring point V 1，1 And V is equal to 1，6 The early warning levels of (a) are red early warning+; anchor rope monitoring point V 2，2 The early warning level of (2) is yellow early warning+; deformation monitoring point V 3，4 、V 3，10 And V is equal to 3，18 The early warning levels of the system are orange early warning+, which indicates that the side slope may have the problem of poor stability at local monitoring points, and the problem has a great relation with engineering disturbance events, and the system should draw attention of related units and responsible persons.
For the #L2 line, it is assumed that only the cable monitoring point V 2，2 With deformation monitoring point V 3，4 On which it is located. As can be seen from the formula (3), the early warning level of the #L2 line is yellow early warning (assumed to be η) 1 Taking 20%), it shows that the slope # L2 line may have a problem of poor stability in a local length range, and the problem has a great relation with engineering disturbance events, and should draw attention from related units and responsible persons.
For the # L2 survey line section, assume an anchor monitoring point V 1，1 And V is equal to 1，6 Anchor rope monitoring point V 2，2 With deformation monitoring point V 3，4 、V 3，10 And V is equal to 3，18 Are all located therein. As can be seen from (4), the #L2 lineThe section is provided with yellow warning (delta is assumed) 1 20 percent is taken, which indicates that the stability of the section of the side slope # L2 survey line in the local area range is poor, and the problem has a great relation with engineering disturbance events, and the attention of related units and responsible persons should be drawn.
For the three-dimensional whole of the side slope, 43 main monitoring quantity monitoring points are added, and the number of the occurrence of the sick early warning main monitoring quantity is 6. According to the formula (5), the side slope section early warning level is blue early warning, which indicates that the three-dimensional whole side slope may have the problem of poor stability in the local volume range, and the problem has a great relation with the engineering disturbance event, and the attention of related units and responsible persons should be paid.
Therefore, the slope stability early warning method based on the multi-source monitoring data change is adopted, meanwhile, the monitoring quantity type and the monitoring point position quantity are considered, the method is easy to popularize and use in various slope monitoring projects after being understood by masses, single-point early warning, linear early warning, section early warning and three-dimensional early warning of a single slope are realized, and the stability early warning and evaluation of the monitored slope points, lines, surfaces and bodies can be realized.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting it, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that: the technical scheme of the invention can be modified or replaced by the same, and the modified technical scheme cannot deviate from the spirit and scope of the technical scheme of the invention.
Claims (9)
1. The slope stability early warning method based on the multisource monitoring data change is characterized by comprising the following steps of:
s1, classifying slope monitoring quantities;
s2, classifying the duration curves of the main monitoring amount in the whole life cycle of the side slope;
s3, determining slope single-point early warning grading standards according to the main monitoring quantity monitoring points;
s4, respectively determining a slope linear early warning grading standard, a slope section early warning grading standard and a slope three-dimensional early warning grading standard;
s5, comparing the slope single-point real-time monitoring data with the four early warning grading standards, and respectively realizing slope single-point early warning, slope linear early warning, slope section early warning and slope three-dimensional early warning.
2. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S1, the slope monitoring quantity includes a primary monitoring quantity and a secondary monitoring quantity, and the types of the primary monitoring quantity are divided into an anchor rod shaft force, an anchor rope tension force and a slope deformation; the types of the auxiliary monitoring quantity comprise rainfall, earthquake, engineering disturbance, soil humidity and water pressure of the ground.
3. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S2, the duration curve types of the anchor rod axis force, the anchor rope tension and the slope deformation in the whole life cycle of the slope are divided into six types: i-stable form; II-single slow-change steady-state trend; III-breathing steady-state trend; IV-single slow-change destabilization; v-breathing instability; VI-mutant destabilization type.
4. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S3, a slope single-point early warning level WL is issued according to a master monitoring amount monitoring point p The method is divided into a main category 2 and a sub category 9, wherein the main category 2 comprises health warning-free and pathological warning, and the sub category 9 comprises warning-free, blue warning, blue warning+, yellow warning, yellow warning+, orange warning, orange warning+, red warning and red warning+.
5. The method for slope stability early warning based on multi-source monitoring data change according to claim 4, wherein, in step S3,
wherein:
WL p -slope single point pre-warning level;
V i,w primary monitored magnitude V i Corresponding early warning values;
V i -primary monitored magnitude, i e {1,2,3}, V 1 Represents the axial force value of the anchor rod, V 2 Representing the tension value of the anchor rod, V 3 Representing a slope deformation value;
V f,j secondary monitoring magnitude, j e {1,2,3,4,5}, V f,1 Represents the accumulated rainfall of the earlier month, V f,2 Representing the number of early month seismic events, V f,3 Representing the number of early moon man Cheng Raodong events, V f,4 Representing the humidity of the soil body in real time, taking the humidity at the sensitive point position or the average humidity of all the point positions of slope humidity monitoring, V f,5 Representing real-time underground water pressure, and taking water pressure at sensitive points or average water pressure of all points monitored by slope water pressure;
ζ 1 the dimensionless coefficient for judging the blue early warning and the yellow early warning is 1.2-1.3;
ζ 2 the dimensionless coefficient for judging the yellow early warning and the orange early warning is 1.4-1.5;
ζ 3 the dimensionless coefficient for judging the orange early warning and the red early warning takes 1.7-1.8.
6. The slope stability warning method based on multi-source monitoring data change according to claim 4, wherein in step S3, the function f (V f,j ) Satisfies the formula (2), f (V) f,j ) The value of (2) depends on the change condition of the side slope auxiliary monitoring quantity, and is as follows:
wherein:
V f,jw secondary monitoring quantity early warning value, j epsilon {1,2,3,4,5}, V f,1w Representing early warning value of accumulated rainfall in early month, taking 100-200 mm and V f,2w The early warning value representing the number of early-stage month earthquake events is 1-3V f,3w Representing early warning value of the number of the events of the early moon worker Cheng Raodong, taking 1-3V f,4w Representing the early warning value of the humidity of the soil body, and obtaining 20-23% of corresponding mass water content, V f,5w Representing the pre-warning value of the underground water pressure, and taking 3kPa to 10kPa.
7. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S4, slope linear early warning grading criteria are as follows:
the monitoring slope is respectively provided with an anchor rod, an anchor rope, deformation, rainfall, humidity, water pressure, video and vibration monitoring points, wherein n1, n2, n3, n4, n5, n6, n7 and n8 are arranged, m measuring lines are arranged, the numbers of the measuring lines are respectively #L1, # L2, … …, # Lk and … … #Lm, m measuring line sections are arranged, the numbers of the measuring lines are respectively #S1, # S2, … …, # Sk and … … #Sm, and for the measuring line with the number #Lk, the total n of the monitoring points with the main monitoring quantity are assumed to be arranged on the measuring line #Lk For the section of the test line numbered #Sk, a total of n is assumed to be the monitoring points with the master monitoring amount #Sk A plurality of;
when there is n on the #Lk line #Lk,w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be L ＝n #Lk,w *100/n #Lk ，R L In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the test line numbered as # Lk, the early warning level WL of the # Lk test line #Lk As shown in formula (3):
wherein:
η 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
η 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
η 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
8. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S4, the slope section early warning grading criteria are as follows:
when the # Sk line has n on its cross section #Sk，w When the monitoring points of the individual master monitoring quantity trigger the pathological early warning, R is led to be S ＝n #Sk,w *100/n #Sk ，R S In order to trigger the ratio of the number of main monitoring quantity monitoring points to the number of main monitoring quantity monitoring points of the pathological early warning on the cross section of the # Sk measuring line, the early warning level WL of the cross section of the # Sk measuring line #Sk As shown in formula (4):
wherein:
δ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
δ 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
δ 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
9. The slope stability early warning method based on multi-source monitoring data change according to claim 1, wherein in step S4, the slope three-dimensional early warning grading criteria are as follows:
when the side slope is counted as n T When the monitoring points of the master monitoring quantity trigger the pathological early warning, R is the other T ＝n T *100/(n1+n2+n3)，R T The main monitoring quantity monitoring points for triggering the pathological early warning occupy the anchor rod and the anchorThe ratio of the cable to the deformation total monitoring point is the three-dimensional early warning level WL of the side slope T As shown in formula (5):
wherein:
ξ 1 -dimensionless coefficients for judging blue early warning and yellow early warning, the values are 20% -30%;
ξ 2 -dimensionless coefficients for judging orange warning and yellow warning, the values are 50% -60%;
ξ 3 the dimensionless coefficient for judging the red early warning and the orange early warning takes 70% -80%.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311298273.4A CN117198018A (en) | 2023-10-09 | 2023-10-09 | Slope stability early warning method based on multisource monitoring data change |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311298273.4A CN117198018A (en) | 2023-10-09 | 2023-10-09 | Slope stability early warning method based on multisource monitoring data change |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117198018A true CN117198018A (en) | 2023-12-08 |
Family
ID=89005339
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311298273.4A Pending CN117198018A (en) | 2023-10-09 | 2023-10-09 | Slope stability early warning method based on multisource monitoring data change |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117198018A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110223490A (en) * | 2019-05-28 | 2019-09-10 | 成都理工大学 | A method of rock slopes stability is judged based on warning grade |
| CN114965100A (en) * | 2022-05-20 | 2022-08-30 | 长安大学 | Method for determining shear strength parameters of unstable slope rock-soil mass |
| CN115424426A (en) * | 2022-08-15 | 2022-12-02 | 中国地质环境监测院(自然资源部地质灾害技术指导中心) | Method for improving accuracy of regional geological disaster early warning and forecasting |
| CN116612622A (en) * | 2023-06-05 | 2023-08-18 | 中国电建集团西北勘测设计研究院有限公司 | Safety monitoring and early warning system for complex high-steep slope |
-
2023
- 2023-10-09 CN CN202311298273.4A patent/CN117198018A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110223490A (en) * | 2019-05-28 | 2019-09-10 | 成都理工大学 | A method of rock slopes stability is judged based on warning grade |
| CN114965100A (en) * | 2022-05-20 | 2022-08-30 | 长安大学 | Method for determining shear strength parameters of unstable slope rock-soil mass |
| CN115424426A (en) * | 2022-08-15 | 2022-12-02 | 中国地质环境监测院(自然资源部地质灾害技术指导中心) | Method for improving accuracy of regional geological disaster early warning and forecasting |
| CN116612622A (en) * | 2023-06-05 | 2023-08-18 | 中国电建集团西北勘测设计研究院有限公司 | Safety monitoring and early warning system for complex high-steep slope |
Non-Patent Citations (1)
| Title |
|---|
| 孙巍锋: "土-岩二元结构路堑边坡失稳机理与智能预警研究", 中国知网, 16 May 2021 (2021-05-16), pages 110 - 177 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wallace | Earthquake recurrence intervals on the San Andreas fault | |
| Birkland | After disaster: Agenda setting, public policy, and focusing events | |
| Eguchi et al. | Real-time loss estimation as an emergency response decision support system: the early post-earthquake damage assessment tool (EPEDAT) | |
| Hirsch | Flux of nitrogen, phosphorus, and suspended sediment from the Susquehanna River basin to the Chesapeake Bay during Tropical Storm Lee, September 2011, as an indicator of the effects of reservoir sedimentation on water quality | |
| National Research Council et al. | Safety of dams: flood and earthquake criteria | |
| Biedenharn et al. | Effective discharge calculation: A practical guide | |
| Tanaka et al. | Impact of a disaster on land price: evidence from Fukushima nuclear power plant accident | |
| Biedenharn et al. | Large-scale geomorphic change in the Mississippi River from St. Louis, MO, to Donaldsonville, LA, as revealed by specific gage records | |
| CN115187033A (en) | Intelligent construction site construction safety risk early warning system and method thereof | |
| CN117198018A (en) | Slope stability early warning method based on multisource monitoring data change | |
| Bosta | Crowd management based on scientific research to prevent crowd panic and disasters | |
| Purwantoro et al. | Sabo dam infrastructure system performance index model in Mount Merapi | |
| Mangalagiri et al. | Fractal Seismicity and Coulomb Stress Pattern Analysis for 7 January 2020 M w 6.4 Puerto Rico Earthquake | |
| Khalik Al-Tae et al. | Prediction analysis of trip production using cross-classification technique | |
| Daniell et al. | The socio-economic impact of historic Australian earthquakes | |
| KAMEDA et al. | Seismic hazard estimation based on non-Poisson earthquake occurrences | |
| Aslani | Hazard rate modeling and risk analysis of water mains | |
| Shoji et al. | Development of damage functions on road infrastructures subjected to extreme ground excitations by analyzing damage in the 2011 off the Pacific coast of Tohoku earthquake | |
| Chandler | Review of Hong Kong seismic parameters and determination of design level earthquake events | |
| Nakashima et al. | A Lesson from the 2011 Tohoku Earthquake–The necessity for collaboration and dialog among natural scientists, engineers, social scientists, government agencies, and the general public | |
| Pan et al. | Influence factors analysis of seismic liquefaction risk for tailings dam | |
| ROBISON | Surface-fault rupture: A guide for land-use planning, Utah and Juab Counties, Utah | |
| Tuncer et al. | Cross Comparison of Traditional and Innovative Trend Methodologies to Understand Climate Change Process | |
| Kinilakodi et al. | Evaluating equivalence of the safe performance index (SPI) to a traditional risk analysis | |
| Shiwua | Seismicity in Nigeria: the need for earthquake-resistant structures |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |