CN113821949B - Rock slope stability safety and reliability prediction method based on deformation monitoring - Google Patents
Rock slope stability safety and reliability prediction method based on deformation monitoring Download PDFInfo
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Abstract
The invention discloses a rock slope stability safety and reliability prediction method based on deformation monitoring, which comprises the following steps: establishing a mathematical model according to rock slope deformation monitoring data, selecting a high-precision sequence as a target sequence, and separating an aging component; establishing a three-dimensional finite element model of the side slope according to engineering data, and performing excavation, support and creep characteristic simulation to obtain a side slope displacement calculated value sequence; determining a stable control sliding surface, extracting a stress sequence, and calculating to obtain a slope stability safety coefficient sequence by applying a stress algebra and ratio method; establishing a slope stability function, and obtaining a slope stability reliability sequence by adopting an JC method; and establishing a mathematical model of slope deformation aging components, slope stability safety coefficients and reliability, and realizing rapid prediction of the slope stability safety coefficients and the reliability by deformation monitoring. The method disclosed by the invention accords with engineering practice, can quickly identify and respond to the side slope accident risk in real time, and provides effective guarantee for side slope safety control.
Description
Technical Field
The invention belongs to the technical field of rock slope stability, and particularly relates to a rock slope stability safety and reliability prediction method based on deformation monitoring.
Background
The hydraulic and hydroelectric engineering provides necessary material basis for the development of the economy and society of China, and plays an irreplaceable role in shipping, power generation, flood control, environmental protection and regional economy development. Hydraulic buildings are often constructed while forming high and steep artificial slopes, wherein rock slopes are used as main representatives. The instability of the side slope can endanger the safety of main buildings and downstream people life and property when serious, such as the instability of the side slope of the Waang arch dam, and causes great loss to the downstream people life and property, so the analysis of the side slope stability is particularly important. The method is one of effective ways for scientifically and reasonably analyzing the stability and safety of the side slope and effectively preventing or reducing the life and property loss of people caused by the instability of the side slope. The method effectively realizes the on-line safety monitoring and control of the side slope, ensures the stable operation of the side slope, and is a problem which is always focused by the dam industry.
The running state of the side slope is dynamically fluctuated and changed along with the change of the surrounding environment of the side slope along with the time, and the development is needed. Before the slope is unstable, a certain precursor is usually provided, or the trend of the instability is developed after a certain time, and the trend of the instability can be reflected in monitoring data, so that massive monitoring data are required to be timely tidied and analyzed, the stability of the slope and possible influences and consequences after the instability are judged according to the monitoring data, further slope operation management is dynamically carried out, and dynamic assessment on the slope operation safety is realized. Therefore, how to evaluate the slope stability based on safety monitoring is a main challenge of the current slope stability analysis, the most visual reflection of the slope stability state is the slope stability safety coefficient and stability reliability, and the reasonable combination of monitoring data and stability indexes is a necessary trend of development.
The traditional slope stability analysis method can only give a stability conclusion under a given condition, cannot consider the dynamic development of the slope, and cannot quickly identify and respond to the slope accident risk in real time.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a rock slope stability safety and reliability prediction method based on deformation monitoring, so as to solve the problems that the traditional slope stability analysis method cannot consider the dynamic development of a slope and cannot quickly identify and respond to the failure risk of the slope in real time.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a rock slope stability safety and reliability prediction method based on deformation monitoring comprises the following steps:
s1, monitoring a sequence { y ] according to the slope deformation 1 ,y 2 ,y 3 …y n And constructing a mathematical model of the displacement of the monitoring point by considering the influence of temperature, aging, rainfall and water level on the deformation of the side slope:
Y(t)＝G(T(t),θ(t),J(t),H(t))
wherein Y (T) is a statistical estimation value of slope deformation at time T, T (T) is an ambient temperature component, θ (T) is an aging component, J (T) is a rainfall component, and H (T) is a water level component;
selecting R 2 A sequence larger than 0.85 is used as a target sequence, and an aging component { theta } of the displacement of the monitoring point is separated according to the constructed mathematical model of the displacement of the monitoring point 1 ,θ 2 ,θ 3 …θ n }；
S2, constructing a three-dimensional finite element model of the side slope, performing side slope excavation, support and rock creep characteristic simulation based on side slope physical and mechanical parameters and rock creep parameters, and calculating and actually measuring a deformation sequence { y } 1 ,y 2 ,y 3 …y n Slope deformation calculated value sequence { x } with corresponding relation in time 1 ,x 2 ,x 3 …x n }。
S3, determining a stable control sliding surface with the minimum safety coefficient according to the three-dimensional finite element calculation result of the side slope, and extracting a stress sequence { (sigma) of the side slope stable control sliding surface 1 ，τ 1 ) 1 ,(σ 2 ，τ 2 ),(σ 3 ，τ 3 )…(σ m ，τ m )}；
S4, solving by adopting a stress algebra sum ratio method to obtain a slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn }；
Wherein K is s For the stable safety coefficient of the side slope, m is the total number of units on the sliding surface, l i The length of the unit i along the sliding surface direction; sigma (sigma) i Is the positive stress of unit i on the slip plane; τ i Shear stress for unit i on the slip plane; f (f) i ' is the coefficient of friction of unit i on the slide; c i Is the cohesion of the unit i on the slip surface;
s5, according to the slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing a rock slope stability safety coefficient prediction model by coupling analysis of the stability safety coefficient of the slope and the deformation aging component, taking the stability safety coefficient as a dependent variable and taking aging deformation as an independent variable;
K S (t)＝F 1 [θ(t)]+C
wherein K is S (t) is the statistical estimation value of the slope stability safety coefficient at time t, C is the undetermined constant term, F 1 [θ(t)]Is an ageing component;
s6, establishing a slope stability function:
wherein Z is a slope stabilizing function, m is the total number of units on the sliding surface, l i The length of the unit i along the sliding surface direction; sigma (sigma) i Is the positive stress of unit i on the slip plane; τ i Shear stress for unit i on the slip plane; f (f) i ' is the coefficient of friction of unit i on the slide; c i Is the cohesion of the unit i on the slip plane.
According to the function, solving by JC method to obtain a slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn }；
S7, according to the slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing and constructing a rock slope stability reliability prediction model by coupling analysis of slope stability reliability and deformation aging components, taking the stability reliability as a dependent variable and aging deformation as an independent variable;
β S (t)＝F 2 [θ(t)]+C
wherein beta is S (t) is the statistical estimation value of the stable and reliable index of the side slope at time t, C is a constant term to be determined, F 2 [θ(t)]Is an ageing component;
s8, rapidly predicting the stability safety coefficient and the stability reliability of the side slope according to the rock slope stability safety coefficient prediction model and the rock slope stability reliability prediction model.
Further, in S1, according to the slope deformation monitoring sequence, a mathematical model of the displacement of the monitoring point is constructed in consideration of the influence of temperature, aging, rainfall and water level on the slope deformation, and the aging component of the displacement of the monitoring point is separated, including:
according to the slope deformation monitoring sequence { y } 1 ,y 2 ,y 3 …y n Considering slope aging deformation, environmental temperature, rainfall and water level influence factors, taking slope deformation as dependent variables, taking aging deformation, environmental temperature, rainfall and water level as independent variables, and establishing a mathematical model of a rock slope deformation sequence through statistical analysis:
Y(t)＝T(t)+θ(t)+J(t)+H(t)+C
wherein Y (T) is a statistical estimation value of slope deformation at time T, T (T) is an ambient temperature component, θ (T) is aging, J (T) is a rainfall component, H (T) is a water level component, and C is a constant term to be determined;
and separating out the aging component of deformation according to the established mathematical model:
θ(t)＝Y(t)-T(t)-J(t)-H(t)+C。
further, in S5, according to the slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n To (S)The stable safety coefficient is a dependent variable, the aging deformation sequence is taken as an independent variable, and a rock slope stable safety coefficient prediction model is constructed through statistical analysis, and the method comprises the following steps:
slope stability safety coefficient sequence { K ] obtained by step S4 s1 ,K s2 ,K s3 …K sn And constructing a mathematical model of the rock slope stability safety coefficient by taking deformation aging component data as an independent variable and the slope stability safety coefficient as a dependent variable:
K S (t)＝F 1 [θ(t)]+C
wherein K is S (t) is the slope stability safety coefficient in time t C is a constant term of undetermined value, F 1 [θ(t)]As the ageing component, F 1 [θ(t)]The method comprises the following steps:
wherein a is i For undetermined coefficient, y i Time-effect component sequence in deformation monitoring value; n is the number of deformation sequences on the dangerous sliding surface.
Further, in S7 { beta } according to the slope stability reliability sequence s1 ,β s2 ,β s3 …β sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n And constructing a rock slope stability safety coefficient prediction model by taking the stability and reliability as a dependent variable and taking the aging deformation as an independent variable, wherein the method comprises the following steps of:
slope stability reliability sequence { beta }, obtained by step S6 s1 ,β s2 ,β s3 …β sn And constructing a mathematical model of the stability and reliability of the rock slope by using deformation aging component data as an independent variable and the stability and reliability of the slope as a dependent variable through statistical analysis:
β S (t)＝F 2 [θ(t)]+C
wherein beta is S (t) is the statistical estimation value of the stable and reliable index of the side slope at time t, C is a constant term to be determined, F 2 [θ(t)]As the ageing component, F 2 [θ(t)]The method comprises the following steps:
wherein b i For undetermined coefficient, y i Time-effect component sequence in deformation monitoring value; n is the number of deformation sequences on the dangerous sliding surface.
The rock slope stability safety and reliability prediction method based on deformation monitoring provided by the invention has the following beneficial effects:
when a prediction model is built, firstly, an aging component of the displacement of the side slope is obtained, then, a mathematical model of the aging deformation same side slope stability safety coefficient and stability reliability is built by utilizing finite element simulation, and finally, the quick prediction of the rock side slope stability safety coefficient and stability reliability is realized through the built mathematical model; the method provided by the invention effectively solves the problems that the traditional slope stability analysis method only can give a stability conclusion under a given condition, can not consider the dynamic development of the slope and can not quickly identify and respond the failure risk of the slope in real time.
Drawings
FIG. 1 is a flow chart of a rock slope stability safety and reliability prediction method based on deformation monitoring.
Fig. 2 tp2l vertical displacement statistical regression process line.
Fig. 3 tp9l horizontal displacement statistical regression line.
Fig. 4 side slope finite element model (before excavation).
Fig. 5 side slope finite element model (after excavation).
FIG. 6 is a graph of simulation results of the TP2L—Z inverse analysis versus actual measurement results.
FIG. 7 is a graph of the simulation of the analysis of TP9L-Y against the actual measurement.
FIG. 8 is F s Plastic region plot of =1.35.
Fig. 9 is a schematic view of a dangerous slip surface.
Fig. 10 is a schematic view of feature points after the 9 th step of excavation.
FIG. 11 shows the course of the P1 point transverse stress.
Fig. 12 shows the course of the P2 point transverse stress.
Fig. 13 shows the course of P3 point transverse stress.
Fig. 14 shows the course of the P1 point transverse strain.
Fig. 15 shows the P2 point transverse strain change process.
Fig. 16 shows the P3 point transverse strain change process.
FIG. 17 is a graph showing the duration of the stability safety factor of the left bank slope of the hillside water power station.
FIG. 18 is a graph of the reliability index of the left bank slope of the hillside water power station and the duration of failure probability.
FIG. 19 is a process line of the left bank slope stability safety factor of the hillside water power station.
FIG. 20 is a graph showing the course of the stable and reliable index of the left bank slope of the hillside water power station.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
According to one embodiment of the present application, referring to fig. 1, the rock slope stability safety and reliability prediction method based on deformation monitoring in the present solution includes:
step S1, according to a slope deformation monitoring sequence { y } 1 ,y 2 ,y 3 …y n Establishing a mathematical model of monitoring point displacement by considering the influences of temperature, aging, rainfall, water level and the like on slope deformation:
Y(t)＝G(T(t),θ(t),J(t),H(t))
selecting a high precision sequence as the target sequence, typically R 2 Sequences greater than 0.85 were used as target sequences. Separating out monitoring points according to the constructed mathematical modelAge component of displacement { θ ] 1 ,θ 2 ,θ 3 …θ n }；
In the embodiment of the invention, the deformation monitoring sequence of the left bank high side slope of the hillside water power station is unfolded and analyzed, and as rainfall and water level factors have little influence on the side slope deformation, a mathematical model of the side slope deformation is constructed mainly by considering aging and environmental temperature factors, and the specific construction is as follows:
Y(t)＝T(t)+θ(t)+C (1)
wherein C is a constant term to be determined; y (t) is a statistical estimation value of a slope deformation (horizontal displacement and vertical displacement) monitoring value at time t; t (T) is the temperature component of the slope deformation (horizontal displacement, vertical displacement); θ (t) is the aging component of the slope deformation (horizontal displacement, vertical displacement).
T (T) is specifically as follows:
wherein T is 1 ,T 2 …T 8 The average temperature of the current day, the first 1 day, the first 2 to 5 days, the first 6 to 15 days, the first 16 to 30 days, the first 31 to 60 days, the first 61 to 90 days and the first 90 to 120 days is observed; b 1 ,b 2 …b 8 Is a pending model coefficient.
The specific form of θ (t) is:
wherein t is i Observing the total days at the moment i; c 1 、c 2 Is a pending model coefficient.
Then according to the result of the mathematical model, R is selected 2 And taking the monitoring point sequence larger than 0.85 as a target value of the inverse analysis, and separating out an aging component according to the constructed mathematical model, as shown in figures 2 and 3.
S2, constructing a three-dimensional finite element model of the side slope, and carrying out side slope excavation, support and rock based on the physical and mechanical parameters of the side slope and the creep parameters of the rock massSimulating the body creep characteristic, and calculating and actually measuring a deformation sequence { y } 1 ,y 2 ,y 3 …y n Slope deformation calculated value sequence { x } with corresponding relation in time 1 ,x 2 ,x 3 …x n }。
In the embodiment of the invention, the side slope excavation time of the hillside water power station is 2007 8 months 1 to 2009 4 months 30 days, and water storage is started when the diversion tunnel is started under the gate in 2014 12 months 30 days. The simulation time interval is selected from 7 months in 2007 to 20 days in 2014 to 12 months in 30 days, namely, before the slope excavation stage and the engineering water storage stage, the action load only considers the gravity load. A finite element model is built according to engineering data, and is shown in figures 4 and 5.
And determining rock physical and mechanical parameters and creep parameters of the left bank side slope engineering of the big sentry mountain and water power station according to engineering design results of the big sentry mountain and water power station and related literature data, wherein the rock physical and creep parameters are shown in tables 1 and 2.
TABLE 1 petrophysical and mechanical parameters
TABLE 2 LUBBY2 model creep parameters
And obtaining a side slope deformation calculated value sequence with a corresponding relation with the actual measurement deformation sequence in time through finite element simulation, wherein the side slope deformation calculated value sequence is shown in fig. 6 and 7.
S3, determining a stable control sliding surface with the minimum safety coefficient according to the three-dimensional finite element calculation result of the side slope, and extracting a stress sequence { (sigma) of the side slope stable control sliding surface 1 ，τ 1 ) 1 ,(σ 2 ，τ 2 ),(σ 3 ，τ 3 )…(σ m ，τ m )}；
In the embodiment of the invention, an intensity reduction method is adopted to search the non-support control slip surface of the left bank high side slope of the hillside water power station, the intensity reduction iteration step length is 0.05, F st See fig. 8 for progression of the plastic region of =1.35.
By doubling down the coefficient F st Analysis of slope plasticity area distribution map at 1.35 to obtain boundary line of IV-class rock mass and V-class rock mass, vein, V-class rock mass and V-class rock mass 2 The joint surface of the rock-like body is a control sliding surface with stable side slope, and the safety is the lowest. The schematic diagram of the dangerous slip surface sliding channel of the side slope after the excavation is completed is shown in fig. 9. 3 monitoring points P1, P2 and P3 are selected at elevations of side slopes 1430m, 1300m and 1195m, and a schematic diagram of the monitoring points and a transverse stress sequence of the monitoring points are shown in figures 10-16.
S4, solving by adopting a stress algebra sum ratio method to obtain a slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn }：
In the embodiment of the invention, the stress sequence { (sigma) of the slope stability control slip surface obtained according to the step S3 1 ，τ 1 ) 1 ,(σ 2 ，τ 2 ),(σ 3 ，τ 3 )…(σ m ，τ m ) And (3) solving by using the formula (1) to obtain a slope stability safety coefficient sequence, as shown in figure 17.
Step S5, according to the slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing a rock slope stability safety coefficient prediction model by coupling analysis of the stability safety coefficient of the slope and the deformation aging component, taking the stability safety coefficient as a dependent variable and taking aging deformation as an independent variable;
K S (t)＝F 1 [θ(t)]+C (3)
in the embodiment of the invention, based on deformation measuring points TP2L, TP L on a slope control slip, a model framework of a formula (3) is adopted, and a mathematical model of a left-bank rock slope stability safety coefficient of a hillside power station is established as a prediction model:
K S (t)＝-4.5*10 -4 *y 1 +3.0*10 -4 *y 2 +6.9*10 -4 *y 3 -1.4*10 -4 *y 4 +1.39 (4)
wherein y is 1 For TP2L measuring point horizontal displacement, y 2 For TP2L measuring point vertical displacement, y 3 For TP9L measuring point horizontal displacement, y 4 The vertical displacement of the TP9L measuring point is adopted.
S6, establishing a slope stability function
According to the function, solving by JC method to obtain a slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn }
In the embodiment of the invention, the lack of statistical information of creep model parameters and the small variation of rock mass volume weight and poisson ratio are considered as the determination quantity. The rock mass elastic modulus E, the cohesive force C and the friction angle phi are considered as random variables, and the characteristic values are shown in Table 3.
TABLE 3 sliding surface rock mass material parameter tables
And constructing a left bank slope control slip surface response surface equation of the hillside power station by adopting a quadratic polynomial without cross terms. And obtaining the equation coefficients of slope stability response surfaces at different moments by adopting an orthogonal test method, wherein the equation coefficients of the typical moment response surfaces are shown in tables 4 and 5.
TABLE 4 equation coefficients of response surface before excavation
TABLE 5 response surface equation coefficients after the 11 th step of excavation
The physical and mechanical parameters of the rock mass are subjected to tail cutting, and the values of the parameters in the range of 3 sigma of the mean value have a guarantee rate of 99.7%, so mu-3 sigma and mu+3 sigma are respectively selected as left and right tail cutting points of random variables. Establishing a functional function according to a formula (5), and obtaining a slope reliability index beta and a failure probability P by adopting a JC method f The sequence is shown in FIG. 18.
S7, according to the slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing and constructing a rock slope stability reliability prediction model by coupling analysis of slope stability reliability and deformation aging components, taking the stability reliability as a dependent variable and aging deformation as an independent variable;
β S (t)＝F 2 [θ(t)]+C (6)
in the embodiment of the invention, based on deformation measuring points TP2L, TP L on the slope control slip, a model framework of a formula (6) is adopted to construct a left-bank rock slope stability reliability degree model of the hillside water power station as a prediction model:
β S (t)＝-1.1*10 -2 *y 1 +7.4*10 -3 *y 2 +1.8*10 -2 *y 3 -3.5*10 -3 *y 4 +2.55
wherein y is 1 For TP2L measuring point horizontal displacement, y 2 For TP2L measuring point vertical displacement, y 3 For TP9L measuring point horizontal displacement, y 4 The vertical displacement of the TP9L measuring point is adopted.
S8, rapidly predicting the stability safety coefficient and the stability reliability of the side slope according to the rock slope stability safety coefficient prediction model and the rock slope stability reliability prediction model.
The prediction effect of the invention is described below with reference to a left bank side slope of a hillside water power station:
(1) Fast prediction result of stability safety coefficient between slopes:
fig. 19 shows a process line of the fitted value and the calculated value of the slope stability safety factor, and table 6 shows the simulation accuracy statistics of the slope stability safety factor. The graph shows that the complex correlation coefficient of the slope stability safety coefficient prediction model based on deformation monitoring is larger than 0.9, the average error between the safety coefficient calculation and the fitting value is 0.12%, the maximum error is 0.36%, and the accuracy is high. The average error and the maximum error of the stability safety coefficient prediction analysis of the side slopes of 90 days and 180 days are within 5 percent, so that the engineering requirements are met.
Table 6 simulation accuracy statistics of slope stability safety factor
(2) And (3) a fast prediction result of stability, safety and reliability between slopes:
FIG. 20 shows the process lines of the slope stability safety reliability index fitting value and the calculated value, and Table 7 shows the slope stability reliability simulation accuracy statistics. The graph shows that the complex correlation coefficient of the slope stability and reliability prediction model based on deformation monitoring is larger than 0.9, the average error between the reliability index calculation and the fitting value is 1.94%, the maximum error is 4.96%, and the accuracy is high. Through the prediction analysis of the stable and reliable indexes of the side slopes of 90 days and 180 days, the average error and the maximum error are within 10 percent, thereby meeting the engineering requirements.
Table 7 simulation accuracy statistics of slope stability reliability
According to the invention, through a large number of finite element simulation analysis, a rock slope stability safety coefficient prediction model and a rock slope stability reliability prediction model based on deformation monitoring are established, and the rapid prediction of the rock slope stability of the deformation monitoring is realized.
Although specific embodiments of the invention have been described in detail with reference to the accompanying drawings, it should not be construed as limiting the scope of protection of the present patent. Various modifications and variations which may be made by those skilled in the art without the creative effort are within the scope of the patent described in the claims.
Claims (4)
1. The rock slope stability safety and reliability prediction method based on deformation monitoring is characterized by comprising the following steps of:
s1, monitoring a sequence { y ] according to the slope deformation 1 ,y 2 ,y 3 …y n And constructing a mathematical model of the displacement of the monitoring point by considering the influence of temperature, aging, rainfall and water level on the deformation of the side slope:
Y(t)＝G(T(t),θ(t),J(t),H(t))
wherein Y (T) is a statistical estimation value of slope deformation at time T, T (T) is an ambient temperature component, θ (T) is an aging component, J (T) is a rainfall component, and H (T) is a water level component;
selecting R 2 A sequence larger than 0.85 is used as a target sequence, and an aging component { theta } of the displacement of the monitoring point is separated according to the constructed mathematical model of the displacement of the monitoring point 1 ,θ 2 ,θ 3 …θ n }；
S2, constructing a three-dimensional finite element model of the side slope, performing side slope excavation, support and rock creep characteristic simulation based on side slope physical and mechanical parameters and rock creep parameters, and calculating and actually measuring a deformation sequence { y } 1 ,y 2 ,y 3 …y n Slope deformation calculated value sequence { x } with corresponding relation in time 1 ,x 2 ,x 3 …x n }；
S3, determining a stable control sliding surface with the minimum safety coefficient according to the three-dimensional finite element calculation result of the side slope, and extracting a stress sequence { (sigma) of the side slope stable control sliding surface 1 ，τ 1 ) 1 ,(σ 2 ，τ 2 ),(σ 3 ，τ 3 )…(σ m ，τ m )}；
S4, solving by adopting a stress algebra sum ratio method to obtain a slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn }；
Wherein K is s For the stable safety coefficient of the side slope, m is the total number of units on the sliding surface, l i The length of the unit i along the sliding surface direction; sigma (sigma) i Is the positive stress of unit i on the slip plane; τ i Shear stress for unit i on the slip plane; f (f) i ' is the coefficient of friction of unit i on the slide; c i Is the cohesion of the unit i on the slip surface;
s5, according to the slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing a rock slope stability safety coefficient prediction model by coupling analysis of the stability safety coefficient of the slope and the deformation aging component, taking the stability safety coefficient as a dependent variable and taking aging deformation as an independent variable;
K S (t)＝F 1 [θ(t)]+C
wherein K is S (t) is the statistical estimation value of the slope stability safety coefficient at time t, C is the undetermined constant term, F 1 [θ(t)]Is an ageing component;
s6, establishing a slope stability function:
wherein Z is a slope stabilizing function, m is the total number of units on the sliding surface, l i The length of the unit i along the sliding surface direction; sigma (sigma) i Is the positive stress of unit i on the slip plane; τ i Shear stress for unit i on the slip plane; f (f) i ' is the coefficient of friction of unit i on the slide; c i Is the cohesion of the unit i on the slip surface;
according to the function, solving by JC method to obtain a slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn }；
S7, according to the slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing and constructing a rock slope stability reliability prediction model by coupling analysis of slope stability reliability and deformation aging components, taking the stability reliability as a dependent variable and aging deformation as an independent variable;
β S (t)＝F 2 [θ(t)]+C
wherein beta is S (t) is the statistical estimation value of the stable and reliable index of the side slope at time t, C is a constant term to be determined, F 2 [θ(t)]Is an ageing component;
s8, rapidly predicting the stability safety coefficient and the stability reliability of the side slope according to the rock slope stability safety coefficient prediction model and the rock slope stability reliability prediction model.
2. The deformation monitoring-based rock slope stability safety and reliability prediction method according to claim 1, wherein the method is characterized in that: in the step S1, according to a slope deformation monitoring sequence, a mathematical model of monitoring point displacement is constructed by considering the influence of temperature, aging, rainfall and water level on the slope deformation, and an aging component of the monitoring point displacement is separated, and the method comprises the following steps:
according to the slope deformation monitoring sequence { y } 1 ,y 2 ,y 3 …y n Considering slope aging deformation, environmental temperature, rainfall and water level influence factors, taking slope deformation as dependent variables, taking aging deformation, environmental temperature, rainfall and water level as independent variables, and establishing a mathematical model of a rock slope deformation sequence through statistical analysis:
Y(t)＝T(t)+θ(t)+J(t)+H(t)+C
wherein Y (T) is a statistical estimation value of slope deformation at time T, T (T) is an ambient temperature component, θ (T) is aging, J (T) is a rainfall component, H (T) is a water level component, and C is a constant term to be determined;
and separating out the aging component of deformation according to the established mathematical model:
θ(t)＝Y(t)-T(t)-J(t)-H(t)+C。
3. the deformation monitoring-based rock slope stability safety and reliability prediction method according to claim 1, wherein the method is characterized in that: in the S5, according to the slope stability safety coefficient sequence { K } s1 ,K s2 ,K s3 …K sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n And constructing a rock slope stability safety coefficient prediction model by taking the stability safety coefficient as a dependent variable and taking the aging deformation sequence as an independent variable through statistical analysis, wherein the method comprises the following steps of:
slope stability safety coefficient sequence { K ] obtained by step S4 s1 ,K s2 ,K s3 …K sn And constructing a mathematical model of the rock slope stability safety coefficient by taking deformation aging component data as an independent variable and the slope stability safety coefficient as a dependent variable:
K S (t)＝F 1 [θ(t)]+C
wherein K is S (t) is the statistical estimation value of the slope stability safety coefficient at time t, C is the undetermined constant term, F 1 [θ(t)]As the ageing component, F 1 [θ(t)]The method comprises the following steps:
wherein a is i For undetermined coefficient, y i Time-effect component sequence in deformation monitoring value; n is the number of deformation sequences on the dangerous sliding surface.
4. The deformation monitoring-based rock slope stability safety and reliability prediction method according to claim 1, wherein the method is characterized in that: in the S7, according to the slope stability reliability sequence { beta } s1 ,β s2 ,β s3 …β sn Time-varying deformation sequence of side slope { theta } 1 ,θ 2 ,θ 3 …θ n Establishing a rock slope stability safety coefficient prediction model by taking stability and reliability as dependent variables and taking aging deformation as independent variables,comprising the following steps:
slope stability reliability sequence { beta }, obtained by step S6 s1 ,β s2 ,β s3 …β sn And constructing a mathematical model of the stability and reliability of the rock slope by using deformation aging component data as an independent variable and the stability and reliability of the slope as a dependent variable through statistical analysis:
β S (t)＝F 2 [θ(t)]+C
wherein beta is S (t) is the statistical estimation value of the stable and reliable index of the side slope at time t, C is a constant term to be determined, F 2 [θ(t)]As the ageing component, F 2 [θ(t)]The method comprises the following steps:
wherein b i For undetermined coefficient, y i Time-effect component sequence in deformation monitoring value; n is the number of deformation sequences on the dangerous sliding surface.
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