CN110162932B - Calculation method for automatically monitoring slope stability based on finite element division - Google Patents
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Abstract
The invention provides a computing method for automatically monitoring slope stability based on finite element division, which comprises the steps of dividing a slope into a plurality of blocks, carrying out finite element division on the slope, and determining the weight coefficient of each grid; then determining monitoring point grids according to the difference of the weight coefficient of each grid, and arranging monitoring equipment at the positions of the monitoring point grids; calculating the block stability coefficient of the grid by using data monitored by the monitoring equipment; calculating an influence relation factor of the block stability of one grid on the stability of the whole slope according to the weight coefficient, and taking the influence relation factor as a safety coefficient of the grid relative to the whole slope; and finally, calculating the average value of a plurality of safety factors to determine the safety state of the side slope. Through the mode that divides the slope whole into limited grid, set up monitoring facilities in key grid position in order to monitor the calculation to the stability of whole slope, reduced the quantity that monitoring facilities set up in order to practice thrift the cost, do not also influence the monitoring accuracy to whole slope.
Description
Technical Field
The invention relates to the technical field of slope stability monitoring, in particular to a computing method for automatically monitoring slope stability based on finite element division.
Background
The area of a mountain area in the land area of China accounts for 69 percent of the total area, and in the implementation process of projects such as railways, highways, water conservancy, electric power and the like, along with excavation of a large number of mountains and the action of non-human factors such as earthquakes, rainfall and the like, accidents of slope collapse and landslide frequently occur, and a large amount of life and property loss can be caused.
At present, a plurality of slope problems are combined with traditional geological theory, numerical simulation, field or indoor test and fuzzy mathematic intelligent methods, dynamic monitoring is carried out on the deformation stability of the slope, a plurality of effective slope monitoring and stability analysis and evaluation technologies and methods are explored, and a relatively complete slope disease safety monitoring system and a deformation dynamic trend prediction method are researched by analyzing slope deformation monitoring data. The contents of the slope safety monitoring work comprise site exploration, point setting monitoring, design optimization, safety management and the like, because the quantity of slope projects is large, not only is a large amount of manpower and material resources required to be invested in the site exploration, but also the workload of the point setting monitoring is large, the slope monitoring relates to multiple aspects of exploration, involvement, construction, management and the like, and the acquired monitoring data is various. In dynamic information such as stress, deformation and the like obtained from slope monitoring, the roughness of the obtained monitoring data is often larger due to uncertainty of rock and soil mass, non-standard installation monitoring instruments, complex installation environment and the like.
Patent CN105139585B discloses an intelligent early warning and forecasting method for dangerous cases of soil slopes, which comprises the following steps: firstly, setting a rainfall monitoring station on site, and burying a soil permeameter and a displacement meter; secondly, acquiring rainfall working conditions of the side slope, soil permeability and displacement data in real time and transmitting the data to a remote client; thirdly, data formatting treatment; fourthly, calculating the weight of the data of rainfall working condition, soil permeability, slope body displacement and the like which influence the safety coefficient of the side slope; fifthly, determining the rainfall condition of each period of the side slope, the relation between the permeability coefficient and deformation of the soil of the side slope, the displacement and the safety coefficient, and predicting the occurrence time of soil slope damage. The method obtains the instability time from the rainfall working condition (the rainfall intensity and the rainfall change along with the time), the parameters of the displacement of the slope body and the relationship between the parameters and the safety coefficient of the side slope, further processes the obtained instability time, has dynamic property different from the prior method according to the relationship between the rainfall and the landslide and other angles, can obtain more accurate instability time, and further improves the early warning and forecasting precision of the soil slope instability damage disaster.
The above patents have several problems: firstly, monitor the side slope as a whole, a large amount of monitoring facilities need be laid to this kind of mode, and monitoring cost is higher. And secondly, even if the side slope is divided into cells, the relation of one block body relative to the whole side slope is not considered, the problem of relevance between adjacent block bodies is not considered, and the monitoring accuracy is low.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides the calculation method for automatically monitoring the slope stability based on the finite element division, which can reduce the laying number of monitoring equipment, save the cost and improve the monitoring accuracy.
The invention provides a computing method for automatically monitoring slope stability based on finite element division, which comprises the following steps,
s1, dividing the side slope into a plurality of blocks, carrying out finite division on the side slope, and determining the weight coefficient of each grid;
s2, determining monitoring point grids according to different weight coefficients of each grid, and arranging monitoring equipment at the positions of the monitoring point grids;
s3, calculating a block stability coefficient of the grid by using data monitored by the monitoring equipment;
s4, calculating an influence relation factor of the block stability of one grid on the stability of the whole slope according to the weight coefficient, and taking the influence relation factor as a safety coefficient of the grid relative to the whole slope;
and S5, calculating an average value of the safety factors to determine the safety state of the slope.
Further, the weight coefficient of the grid in S1 is determined according to the number of finite bins and the importance index of each grid.
Further, the data monitored by the monitoring device in S3 includes the stress and displacement of the block; presetting the sliding direction of the side slope, numbering each grid from top to bottom, and deriving a normal direction stress balance relational expression, a block body normal stress, a side slope gliding force sum relational expression, block body shearing strength and block body anti-skidding force.
Further, if the monitoring device monitors that the grid has no stress change and displacement change, the stability coefficient of the grid is as follows:
wherein SfiIn order to be the anti-slip force of the grid,Tiis the total gliding force of the side slope.
Further, if the monitoring device monitors that the grid has a stress change, the stability coefficient of the grid is as follows:
wherein, taufiIs the shear strength of the grid, τiIs the sum of the shear stresses.
Further, if the monitoring device monitors that the grid has displacement change, the stability coefficient of the grid is as follows:
wherein SifThe strip slip reaches the shear displacement in the critical state, SiShear displacement monitored for the bar slider.
Further, the method also comprises the following steps:
s6, determining the correlation coefficient between grids according to the geological conditions, the underground water conditions, the induction factors, the construction environment and the data integrity among the grids;
s7, determining the correlation grade corresponding to the correlation coefficient;
and S8, determining the safety level of the peripheral grid by taking the monitoring point grid as an early warning central point and based on the correlation coefficient of the peripheral point and the early warning central point.
According to the technical scheme, the invention has the beneficial effects that:
1. the method for automatically monitoring the slope stability based on finite element division comprises the steps of dividing a slope into a plurality of blocks, carrying out finite element division on the slope, and determining the weight coefficient of each grid; then determining monitoring point grids according to the difference of the weight coefficient of each grid, and arranging monitoring equipment at the positions of the monitoring point grids; calculating the block stability coefficient of the grid by using data monitored by the monitoring equipment; calculating an influence relation factor of the block stability of one grid on the stability of the whole slope according to the weight coefficient, and taking the influence relation factor as a safety coefficient of the grid relative to the whole slope; and finally, calculating the average value of a plurality of safety factors to determine the safety state of the side slope. Through the mode that divides the slope whole into limited grid, set up monitoring facilities in key grid position in order to monitor the calculation to the stability of whole slope, reduced the quantity that monitoring facilities set up in order to practice thrift the cost, do not also influence the monitoring accuracy to whole slope.
2. According to the method for automatically monitoring the slope stability based on the finite element division, the correlation coefficient between adjacent blocks is introduced, the monitoring point grids are used as early warning central points, the safety level of the peripheral grids is determined, and the monitoring accuracy is further enhanced.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a schematic flow chart of the calculation method for automatically monitoring slope stability based on finite element division.
Fig. 2 is a schematic view of a force analysis of a block according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Referring to fig. 1, the method for automatically monitoring slope stability based on finite element division comprises the following steps,
the method comprises the following steps that firstly, a side slope is divided into a plurality of blocks, limited cells are divided on the side slope, and the weight coefficient of each grid is determined; the weight coefficient of the grid is determined according to the number of the finite lattices and the importance serial number of each grid, and the specific calculation formula is as follows:
∑γij＝1
in formula (1), γ — weight coefficient; n is the number of divided finite element cells; m is the importance ranking number, and m is less than or equal to n. The importance ranking number m is determined by ranking according to experience by experts or by ranking according to historical data by workers.
Secondly, determining monitoring point grids according to different weight coefficients of each grid, and arranging monitoring equipment at the positions of the monitoring point grids;
thirdly, calculating a block stability coefficient of the grid by using data monitored by the monitoring equipment;
in the embodiment, the effects of water, earthquake and the like are not considered, only the side slope under the static condition is considered, and the stress and the displacement of the block body are monitored; then, for any block, the stress is as shown in fig. 2, the sliding direction of the preset slope is from right to left, each grid is numbered from top to bottom as 1-n, and the inclination angles of the three blocks from left to right are respectively alphai+1、α、αi-1，WiIs dead weight, Pi-1For downward sliding force, BiIs the length of the slider, NiFor the anti-skid force, sigma is the shear stress,
is an internal angle of friction, CiIs a friction force.
The following formula is derived:
normal direction force balance relation: n is a radical ofi＝Wicosαi+Pi-1sin(αi-1-αi)
The normal direction of the block body is as follows:
the sum of the gliding force is: t isi＝Wisinαi+Pi-1cos(αi-1-αi)
The shear strength of the block is:
the sliding resistance of the block body is as follows:
(1) if the monitoring equipment monitors that the grid has no stress change and displacement change, the stability coefficient of the grid is as follows:
wherein SfiIs the slip resistance of the grid, TiIs the total gliding force of the side slope.
(2) If the monitoring equipment monitors that the grid has stress change, the stability coefficient of the grid is as follows:
wherein, taufiIs the shear strength of the grid, τiIs the sum of the shear stresses.
(3) If the monitoring equipment monitors that the grid has displacement change, the stability coefficient of the grid is as follows:
wherein SifThe strip slip reaches the shear displacement in the critical state, SiShear displacement monitored for the bar slider.
Fourthly, calculating an influence relation factor of the block stability of one grid on the stability of the whole slope according to the weight coefficient, and taking the influence relation factor as a safety coefficient of the grid relative to the whole slope;
the calculation formula of the safety coefficient Fi is as follows: fi ═ Ki × γi。
Fifthly, calculating the average value of a plurality of safety factors
Thereby determining the slope safety state.
As shown in the following table, the safety state of the slope varies depending on the value of the safety factor.
| Safe state | Instability of the film | Under-stabilization | Basic stabilization | Stabilization |
| Factor of safety | K＜1 | 1＜K＜1.05 | 1.05＜K＜1.15 | 1.15＜K |
Sixthly, determining a correlation coefficient Aij between grids according to geological conditions, underground water conditions, induction factors, construction environments and data integrity among the grids;
the specific method for determining the correlation coefficient is to make a decision according to the historical big data: storing the side slope geological conditions, the underground water conditions, the induction factors, the construction environment data and the corresponding side slope correlation coefficients into a database; and inputting the geological conditions, the underground water conditions, the induction factors and the keywords of the construction environment of the two adjacent grids to be detected into a large database, and calculating the correlation coefficient of the two adjacent grids to be detected in the large database.
Seventhly, determining the correlation grade corresponding to the correlation coefficient, wherein the corresponding relation is shown in the following table:
| level of association | Association relation | Correlation coefficient Aij |
| IV | Very high correlation | 0.75＜Aij≤1 |
| III | Height correlation | 0.5＜Aij≤0.75 |
| II | Moderate correlation | 0.25＜Aij≤0.5 |
| I | Low degree of correlation | 0＜Aij≤0.25 |
And eighthly, determining the safety level of the peripheral grid by taking the monitoring point grid as an early warning central point and based on the correlation coefficient of the peripheral point and the early warning central point.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (6)
1. The method for automatically monitoring the slope stability based on the finite element division is characterized by comprising the following steps of: comprises the following steps of (a) carrying out,
s1, dividing the side slope into a plurality of blocks, carrying out finite division on the side slope, and determining the weight coefficient of each grid;
s2, determining monitoring point grids according to different weight coefficients of each grid, and arranging monitoring equipment at the positions of the monitoring point grids;
s3, calculating a block stability coefficient of the grid by using data monitored by the monitoring equipment;
s4, calculating an influence relation factor of the block stability of one grid on the stability of the whole slope according to the weight coefficient, and taking the influence relation factor as a safety coefficient of the grid relative to the whole slope;
s5, solving an average value of a plurality of safety factors to determine the safety state of the side slope;
s6, determining the correlation coefficient between grids according to the geological conditions, the underground water conditions, the induction factors, the construction environment and the data integrity among the grids; the specific method for determining the correlation coefficient is to make a decision according to the historical big data: storing the side slope geological conditions, the underground water conditions, the induction factors, the construction environment data and the corresponding side slope correlation coefficients into a database; inputting geological conditions, underground water conditions, induction factors and keywords of a construction environment of two adjacent grids to be detected into a large database, and calculating the correlation coefficient of the two adjacent grids to be detected in the large database;
s7, determining the correlation grade corresponding to the correlation coefficient;
and S8, determining the safety level of the peripheral grid by taking the monitoring point grid as an early warning central point and based on the correlation coefficient of the peripheral point and the early warning central point.
2. The method of claim 1, wherein the method comprises the steps of: the weight coefficient of the grid in S1 is determined based on the number of finite bins and the importance index of each grid.
3. The method of claim 1, wherein the method comprises the steps of: the data monitored by the monitoring device in S3 includes the stress and displacement of the mass; presetting the sliding direction of the side slope, numbering each grid from top to bottom, and deriving a normal direction stress balance relational expression, a block body normal stress, a side slope gliding force sum relational expression, block body shearing strength and block body anti-skidding force.
4. The method of claim 3, wherein the method comprises the following steps: if the monitoring equipment monitors that the grid has no stress change and displacement change, the stability coefficient of the grid is as follows:
wherein SfiIs the slip resistance of the grid, TiIs the downslide of a side slopeThe sum of the forces.
5. The method of claim 4, wherein the method comprises the following steps: if the monitoring equipment monitors that the grid has stress change, the stability coefficient of the grid is as follows:
wherein, taufiIs the shear strength of the grid, τiIs the sum of the shear stresses.
6. The method of claim 1, wherein the method comprises the steps of: if the monitoring equipment monitors that the grid has displacement change, the stability coefficient of the grid is as follows:
wherein SifThe strip slip reaches the shear displacement in the critical state, SiShear displacement monitored for the bar slider.
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| CN111598406B (en) * | 2020-04-21 | 2023-05-30 | 长江勘测规划设计研究有限责任公司 | High-steep slope block instability risk quantitative assessment method |
| CN111881612B (en) * | 2020-08-05 | 2021-03-19 | 武汉市政工程设计研究院有限责任公司 | Two-dimensional stress field inversion method and system for different weights of normal stress and shear stress |
| CN113742827B (en) * | 2021-09-03 | 2023-05-19 | 招商局重庆交通科研设计院有限公司 | Highway slope monitoring network system construction method based on finite difference analysis |
| CN114495434B (en) * | 2022-02-08 | 2024-01-12 | 北京寒武智能科技有限公司 | Landslide hazard temporary slip prediction method |
| CN114582095A (en) * | 2022-03-16 | 2022-06-03 | 浙江电力建设工程咨询有限公司 | Remote slope safety monitoring data acquisition device and data analysis method |
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