Landslide early warning method based on linkage of evolutionary process and monitoring equipment

Abstract

The invention belongs to the technical field of geological disaster monitoring, and particularly relates to an evolutionary process and monitoring equipment linked landslide early warning method and storage equipment. Assigning a layout position weight coefficient Ai to the monitoring equipment at different layout parts according to the divided landslide types; according to the method, the equipment type weight coefficient Bi, the equipment precision weight coefficient Ci and the acquisition frequency weight coefficient Di are further assigned to the equipment assigned with the layout position weight coefficient Ai, the equipment weight Value is calculated according to the following formula, and the Value is introduced into a landslide early warning model based on the evolution process for comprehensive early warning, so that the accuracy of landslide early warning is improved, and the accuracy of landslide early warning is improved. And the phenomena of false alarm, missing alarm and the like are prevented.

Description

Technical Field

[0001] The invention belongs to the technical field of geological disaster monitoring, and in particular relates to a landslide early warning method in which an evolution process is linked with monitoring equipment. Background Art

[0002] my country is seriously threatened by geological disasters. According to statistics, there are about 300,000 potential danger points in the country, threatening about 20 million people and about 450 billion yuan of property. About 70% of geological disasters are distributed in the western region, about 70% of major geological disasters are landslides, and about 70% of catastrophic events are not in the discovered potential danger points. Real-time monitoring and early warning of landslides has always been a difficult problem, and it is also one of the hot topics studied by scholars at home and abroad.

[0003] In the prior art, landslide warning generally uses monitoring data to calculate a threshold value, and different levels of warnings are issued according to this threshold value. This method often causes false alarms due to data fluctuations. For example, when the monitoring data fluctuates, such as jumps and mutations, resulting in the calculated warning characteristic value being too large, relying solely on the threshold warning may trigger the warning module to issue the highest level of "red warning", but the landslide may still be in the uniform deformation stage, and false alarms will occur at this time. In addition, in actual monitoring and early warning work, the monitoring equipment is often affected by the outside world or the defects of the equipment itself, and obviously wrong data is collected, which causes the early warning system to issue wrong warning information, resulting in false alarms or missed alarms, such as: the steel rope of the crack meter is touched by cattle, sheep or passers-by, resulting in a sudden increase in data, or the equipment itself is not installed properly, resulting in slow deformation data, or the equipment sensor joint is loose, resulting in too much collected data, etc. At this time, the monitored object itself has not deformed, and the early warning system will cause false alarms due to wrong data. Summary of the invention

[0004] The purpose of the present invention is to provide a landslide early warning method that links an evolution process with a monitoring device, so as to solve the problem that the existing landslide early warning method has a single mechanism and is prone to false alarms due to erroneous data.

[0005] The present invention adopts the following technical solution:

[0006] A landslide early warning method that links an evolution process with a monitoring device comprises the following steps:

[0007] 1) Obtain real-time monitoring data and the monitoring equipment information to which the monitoring data belongs;

[0008] 2) Classify the landslide types according to the movement mode or deformation and damage mode, and set the monitoring equipment in different locations according to the classified landslide types. i Assignment;

[0009] 3) Assign the layout position weight coefficient A i The equipment is further subjected to equipment type weight coefficient B i , Equipment accuracy weight coefficient C i , acquisition frequency weight coefficient D i Assign a value and calculate the device weight Value according to the following formula

[0010]

[0011] 4) Based on the real-time monitoring data obtained, a landslide deformation-time curve is constructed. Taking the initial deformation rate v0 of the landslide as a reference, the deformation rate v, rate increment Δv, and improved tangent angle α are comprehensively considered to construct a comprehensive landslide early warning model based on the evolution process;

[0012] 5) Make early warning conclusions for the monitored landslides according to the comprehensive landslide early warning model based on the evolution process;

[0013] 6) A credibility threshold is preset, and the credibility of the conclusion is determined based on the equipment weight Value and the warning conclusion. If it is greater than the credibility threshold, the warning is issued. If it is less than the credibility threshold, the on-duty personnel are notified to verify and no warning is issued.

[0014] Further, in the step 2):

[0015] The landslide types classified according to the movement mode are: push-type landslide, progressive and retreating landslide, and compound landslide. The weight coefficient of the deployment position of the monitoring equipment for push-type landslide is: front edge> middle> rear edge; the weight coefficient of the deployment position of the monitoring equipment for progressive and retreating landslide is: rear edge> middle> front edge; the weight coefficient of the deployment position of the monitoring equipment for compound landslide is: middle> front edge=rear edge;

[0016] According to the deformation and failure mode, landslide types are divided into: creep-tension type, slip-tension type, tipping-tension type and plastic flow-tension type. Among them, the weight coefficient of the layout location of the creep-tension type landslide monitoring equipment is: front edge>middle>trailing edge; the weight coefficient of the layout location of the slip-tension type landslide monitoring equipment is: trailing edge>middle>front edge; the weight coefficient of the layout location of the tipping-tension type landslide monitoring equipment is: trailing edge>middle>front edge; the weight coefficient of the layout location of the plastic flow-tension type landslide monitoring equipment is: trailing edge>middle>front edge.

[0017] Further, in the step 3):

[0018] Equipment type weight coefficient Bi: For landslides, the GNSS weight coefficient is 1, the deep displacement meter weight coefficient is 0.5, and the crack meter weight coefficient is 1.5;

[0019] Device precision weight coefficient Ci: the weight coefficient for millimeter level is 1, the weight coefficient for centimeter level is 0.8, and the weight coefficient for decimeter level is 0.5;

[0020] Collection frequency weight coefficient Di: the weight coefficient for minute level is 1, the weight coefficient for hour level is 0.8, and the weight coefficient for day level is 0.5.

[0021] Furthermore, in the step 4):

[0022] If the landslide deformation rate v≈0 or v<v0, at this time the landslide curve is a stable type, and it is determined that the landslide is in the initial deformation stage;

[0023] If the landslide deformation rate v≥v0 and the rate increment Δv<0, at this time the landslide curve is a stable type, and it is determined that the landslide is in the initial deformation stage;

[0024] If the landslide deformation rate v≥v0, Δv≈0, and the improved tangent angle α≈45°, at this time the landslide curve is a stable oscillation type, and it is determined that the landslide is in the uniform deformation stage.

[0025] If the landslide deformation rate v≥v0, Δv>0, the improved tangent angle α>45° and α<80°, at this time the landslide curve is an increasing type, and it is determined that the landslide is in the initial acceleration stage of the accelerated deformation stage;

[0026] If the landslide deformation rate v≥v0, Δv>0, the improved tangent angle α≥80° and α<85°, at this time the landslide curve is an exponential type, and it is determined that the landslide is in the middle acceleration stage of the accelerated deformation stage.

[0027] If the landslide deformation rate v≥v0, Δv>0, the improved tangent angle α≥85°, at this time the landslide curve is a mutation type, and it is determined that the landslide is in the additional acceleration and approaching sliding stage of the accelerated deformation stage.

[0028] Furthermore, in the step 4):

[0029] Improved tangent angle α i The calculation formula is

[0030]

[0031] In the formula: α i Is the improved tangent angle corresponding to the monitoring time t i S(i) is the cumulative displacement of the landslide deformation within a certain unit time period; v i Is the deformation rate at the monitoring time t i ; Is the displacement rate in the uniform deformation stage, which is obtained by taking the arithmetic mean of the deformation rates in each time period of the uniform deformation stage.

[0032] The beneficial technical effects of the present invention are as follows:

[0033] Compared with the prior art, the present invention allocates different weight coefficients to the monitoring equipment corresponding to different types of landslides, and introduces this coefficient into the early warning model based on the landslide deformation evolution process, thereby forming a landslide early warning method in which the evolution process is linked with the monitoring equipment, thereby improving the accuracy of landslide early warning and preventing the occurrence of false alarms, missed alarms, etc. Taking the initial deformation rate as a reference, the improved tangent angle model is used to make a judgment on the landslide deformation evolution stage, combining the characteristics of the landslide deformation-time curve, comprehensively considering the deformation rate (v), rate increment (Δv), and improved tangent angle (α) and other quantitative early warning criteria, the comprehensive tracking monitoring and dynamic early warning of the landslide deformation evolution process are realized, which can more effectively avoid or reduce the adverse effects of landslide disasters on human economic life. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Schematic diagram of landslide classification in different movement modes, where (a) is a push-type landslide, (b) is a progressive-recession landslide, and (c) is a compound landslide.

[0035] Figure 2 Schematic diagram of landslide classification under different deformation and failure modes. DETAILED DESCRIPTION

[0036] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the scheme of the present invention is now described in detail with reference to the accompanying drawings and embodiments.

[0037] The present invention provides a landslide early warning method in which an evolution process is linked with a monitoring device, comprising the following steps:

[0038] 1) Obtain real-time monitoring data and the monitoring equipment information to which the monitoring data belongs;

[0039] 2) Classify the landslide types according to the movement mode or deformation and damage mode, and set the monitoring equipment in different locations according to the classified landslide types. i Assignment;

[0040] 3) Assign the layout position weight coefficient A i The equipment is further subjected to equipment type weight coefficient B i , Equipment accuracy weight coefficient C i , acquisition frequency weight coefficient D i Assign a value and calculate the device weight Value according to the following formula

[0041]

[0042] 4) Based on the real-time monitoring data obtained, a landslide deformation-time curve is constructed. Taking the initial deformation rate v0 of the landslide as a reference, the deformation rate v, rate increment Δv, and improved tangent angle α are comprehensively considered to construct a comprehensive landslide early warning model based on the evolution process;

[0043] 5) Make early warning conclusions for the monitored landslides according to the comprehensive landslide early warning model based on the evolution process;

[0044] 6) A credibility threshold is preset, and the credibility of the conclusion is determined based on the equipment weight Value and the warning conclusion. If it is greater than the credibility threshold, the warning is issued. If it is less than the credibility threshold, the on-duty personnel are notified to verify and no warning is issued.

[0045] Example:

[0046] According to the movement mode and deformation and failure mode, landslides can be divided into push-type landslides, progressive and retreating landslides, compound landslides, creep-fracture landslides, sliding-fracture landslides, dumping-fracture landslides, and plastic flow-fracture landslides.

[0047] According to the movement mode, landslides can be divided into push landslides, progressive and retreat landslides, and compound landslides.

[0048] like Figure 1 As shown in the figure, the rear of the push-type landslide is a strong deformation zone, and the front edge is a weak deformation zone. The monitoring focus is often the rear edge of the landslide, but the instability process of the landslide is that the rear edge deforms first and then gradually expands forward. The displacement and deformation of the front edge are the key to the overall instability warning of the landslide. Therefore, for the combined early warning of push-type landslides, the weight of the monitoring equipment should be: front edge> middle> rear edge; the front edge of the progressively retreating landslide is a strong deformation zone, and the rear edge is a weak deformation zone. The monitoring focus is often the front edge of the landslide, but the overall instability process of the landslide is a gradual retreat trend from the front edge to the rear edge. The deformation and displacement of the rear edge are the key to the overall instability warning of the landslide. Therefore, for the combined early warning of the progressively retreating landslide, the weight of the monitoring equipment should be: rear edge> middle> front edge; the front and rear edges of the compound landslide are both strong deformation zones, and there is often a locking section in the middle with weak deformation strength, but it is the key position of landslide instability and destruction. Therefore, for the combined early warning of the compound landslide, the weight of the monitoring equipment should be: middle> front edge=rear edge.

[0049] like Figure 2As shown in the figure, four modes can be divided according to the deformation and failure mode: creep-crack, slip-crack, dump-crack and plastic flow-crack. Among them, the creep-crack instability process is that the rear edge deforms first and then gradually expands forward. The displacement and deformation of the front edge are the key to the overall instability warning of the landslide. Therefore, for the creep-crack combined landslide warning, the monitoring equipment weight should be: front edge> middle> rear edge. The slip-crack instability process is a gradual retreat trend from the front edge to the rear edge. The deformation and displacement of the rear edge are the key to the overall instability warning of the landslide. Therefore, for the slip-crack combined landslide warning, the monitoring equipment weight should be: rear edge> middle> front edge. During the instability process of the toppling-tensile cracking landslide, the steep slab beam near the front edge of the slope often becomes unstable due to the destruction of the rock mass at the root of the slab beam. The subsequent slab beams will also become unstable due to the loss of support, showing a trend of retreating step by step. Therefore, for the combined early warning of the toppling-tensile cracking landslide, the weight of the monitoring equipment should be: rear edge> middle> front edge. During the instability process of the plastic flow-tensile cracking landslide, unloading rebound steep cracks are first formed in the slope body, and then plastic flow-tensile cracking deformation occurs at the front edge. The tensile cracks continue to move backwards, and the slip surface gradually penetrates. Therefore, for the combined early warning of the plastic flow-tensile cracking landslide, the weight of the monitoring equipment should be: rear edge> middle> front edge.

[0050] According to different landslide types, the monitoring equipment in different locations is assigned values. The weight setting (Ai) of the equipment in different locations is grouped in a single longitudinal section: score a single device according to 2, 4, 6, 8, 10

[0051] Push-type landslide: the weight of the front edge monitoring equipment is 10, the weight of the middle monitoring equipment is 6, and the weight of the rear edge monitoring equipment is 2;

[0052] Progressive retreat landslide: weight of front monitoring equipment is 2, weight of middle monitoring equipment is 6, weight of rear monitoring equipment is 10;

[0053] Compound landslide: weight of front edge monitoring equipment is 6, weight of middle monitoring equipment is 10, weight of rear edge monitoring equipment is 6.

[0054] Creep-slip and tensile-fracture landslide: the weight of the front edge monitoring equipment is 10, the weight of the middle monitoring equipment is 6, and the weight of the rear edge monitoring equipment is 2;

[0055] Slip-rupture landslide: Front edge monitoring equipment weight 2, middle monitoring equipment weight 6, rear edge monitoring equipment weight 10

[0056] Toppling-fracture landslide: Front edge monitoring equipment weight 2, middle monitoring equipment weight 6, rear edge monitoring equipment weight 10

[0057] Plastic flow-fracture landslide: front edge monitoring equipment weight 2, middle monitoring equipment weight 6, rear edge monitoring equipment weight 10

[0058] Equipment type weight coefficient allocation (Bi): For landslides, the GNSS weight coefficient is 1, the deep displacement meter weight coefficient is 0.5, and the crack meter weight coefficient is 1.5; the weight coefficients of other equipment are all 0.2, which can be adjusted accordingly according to actual conditions.

[0059] Equipment accuracy weight coefficient allocation (Ci): The weight coefficient for millimeter level is 1, the weight coefficient for centimeter level is 0.8, and the weight coefficient for decimeter level is 0.5;

[0060] Collection frequency weight coefficient allocation (Di): the minute-level weight coefficient is 1, the hour-level weight coefficient is 0.8, and the day-level weight coefficient is 0.5.

[0061]

[0062] As shown in Table 1, in the initial deformation stage of the landslide, the early warning model only needs to consider whether the deformation rate is greater than a certain critical value (v0). Once the deformation rate continues to be v≥v0, the rate increment index (Δv) is introduced to participate in the model calculation. When Δv is continuously greater than zero, the improved tangent angle model is introduced. The uniform deformation stage in the displacement monitoring curve is automatically extracted through the program to obtain the average deformation rate of the landslide in the uniform deformation stage, thereby calculating the improved tangent angle α. The deformation evolution stage of the landslide is divided according to the tangent angle, and then the monitoring and early warning level of the landslide is comprehensively determined.

[0063] Table 1 Early warning model based on landslide deformation evolution process

[0064]

[0065] The calculation of the improved tangent angle is as follows

[0066]

[0067] in:

[0068] again:

[0069] So improve the tangent angle α i It can be expressed as:

[0070]

[0071] Where: α i is the improved tangent angle corresponding to the monitoring time ti; t i is the monitoring time i;

[0072] Δt is the unit time period corresponding to S (usually a monitoring period, such as 1 day or 1 week);

[0073] ΔT is the change of T(i) in a unit time period.

[0074] S(i) is the cumulative displacement of the landslide deformation within a certain unit time period (generally a monitoring period, such as 1 hour, 1 day or 1 week);

[0075] v i is the deformation rate at monitoring time ti;

[0076] is the displacement rate in the constant-speed deformation stage. It is obtained by taking the arithmetic average of the deformation rates in each time period in the constant-speed deformation stage, where vj is the deformation rate in each different time period in the constant-speed deformation stage, and m is the number of monitoring times.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A landslide early warning method that links an evolution process with a monitoring device, characterized in that: It includes the following steps: 1) Obtain real-time monitoring data and the information of the monitoring equipment to which the monitoring data belongs; 2) Classify the landslide types according to the movement mode or deformation and damage mode, and set the monitoring equipment in different locations according to the classified landslide types. i Assignment; 3) Assign the layout position weight coefficient A i The equipment is further subjected to equipment type weight coefficient B i , Equipment accuracy weight coefficient C i , acquisition frequency weight coefficient D i Assign a value and calculate the device weight Value according to the following formula 4) According to the obtained real-time monitoring data, construct a landslide deformation-time curve. Taking the initial deformation rate v0 of the landslide as a reference, comprehensively consider various quantitative warning criteria such as the deformation rate v, the rate increment Δv, and the improved tangent angle α, and construct a comprehensive landslide warning model based on the evolution process; 5) Make a warning conclusion about the monitored landslide according to the comprehensive landslide warning model based on the evolution process; 6) Preset a credibility threshold, and judge the credibility of the conclusion based on the equipment weight Value and the warning conclusion. If it is greater than the credibility threshold, issue the warning. If it is less than the credibility threshold, notify the duty personnel to verify and do not issue the warning.

2. A landslide early warning method in which the evolution process is linked with the monitoring equipment according to claim 1, characterized in that: In the said step 2): The landslide types divided according to the movement mode are: translational landslide, progressive retreat landslide, and composite landslide. Among them, the weight coefficient of the layout position of the monitoring equipment for translational landslide: front edge > middle part > rear edge; the weight coefficient of the layout position of the monitoring equipment for progressive retreat landslide: rear edge > middle part > front edge; the weight coefficient of the layout position of the monitoring equipment for composite landslide: middle part > front edge = rear edge; The landslide types divided according to the deformation and failure mode are: creep-tension crack type, sliding-tension crack type, toppling-tension crack type, and plastic flow-tension crack type. Among them, the weight coefficient of the layout position of the monitoring equipment for creep-tension crack type landslide: front edge > middle part > rear edge; the weight coefficient of the layout position of the monitoring equipment for sliding-tension crack type landslide: rear edge > middle part > front edge; the weight coefficient of the layout position of the monitoring equipment for toppling-tension crack type landslide: rear edge > middle part > front edge; the weight coefficient of the layout position of the monitoring equipment for plastic flow-tension crack type landslide: rear edge > middle part > front edge.

3. A landslide early warning method in which the evolution process is linked with the monitoring equipment according to claim 1, characterized in that: In the said step 3): The weight coefficient Bi of the equipment type: the weight coefficient of GNSS is 1, the weight coefficient of the deep displacement meter is 0.5, and the weight coefficient of the crack meter is 1.5; The weight coefficient Ci of the equipment accuracy: the weight coefficient of millimeter level is 1, the weight coefficient of centimeter level is 0.8, and the weight coefficient of decimeter level is 0.5; The weight coefficient Di of the acquisition frequency: the weight coefficient of minute level is 1, the weight coefficient of hour level is 0.8, and the weight coefficient of day level is 0.

5.

4. A landslide early warning method in which the evolution process is linked with the monitoring equipment according to claim 1, characterized in that: In the said step 4): If the landslide deformation rate v≈0 or v<v0, at this time the landslide curve is of a stable type, and it is judged that the landslide is in the initial deformation stage; If the landslide deformation rate v≥v0 and the rate increment Δv<0, at this time the landslide curve is of a stable type, and it is judged that the landslide is in the initial deformation stage; If the landslide deformation rate v≥v0 and Δv≈0, the improved tangent angle α≈45°, at this time the landslide curve is of a stable oscillation type, and it is judged that the landslide is in the uniform deformation stage. If the landslide deformation rate v≥v0 and Δv>0, the improved tangent angle α>45° and α<80°, at this time the landslide curve is of an increasing type, and it is judged that the landslide is in the initial acceleration stage of the accelerated deformation stage; If the landslide deformation rate v≥v0 and Δv>0, the improved tangent angle α≥80° and α<85°, at this time the landslide curve is of an exponential type, and it is judged that the landslide is in the middle acceleration stage of the accelerated deformation stage. If the landslide deformation rate v≥v0 and Δv>0, and the improved tangent angle α≥85°, the landslide curve is a mutation type, and it is determined that the landslide is in the acceleration stage of the accelerated deformation stage, that is, the impending slip stage.

5. A landslide early warning method in which the evolution process is linked with the monitoring equipment according to claim 1, characterized in that: In the step 4): Improved tangent angle α i The calculation formula is Where: α i is the monitoring time t i The corresponding improved tangent angle; S(i) is the cumulative displacement of the landslide deformation within a certain unit time period; v i is the monitoring time t i The deformation rate; is the displacement rate in the constant-speed deformation stage, which is obtained by taking the arithmetic average of the deformation rates in each time period in the constant-speed deformation stage.

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