Early warning and monitoring method and system for karst collapse area

Abstract

The invention discloses a karst collapse area early warning and monitoring method and system, and relates to the technical field of karst collapse area early warning and monitoring, and the method comprises the steps: 1, karst cave monitoring, 2, ground subsidence monitoring, and 3, karst cave early warning and management. The internal form change index and the external form change index of the karst cave of the tourist attraction are evaluated, the risk of deformation and fracture of the karst cave is reduced, the stability of the cave is improved, then ground collapse is avoided, the collapse risk of the karst cave of the tourist attraction is analyzed, the grade of karst collapse risk areas is divided, and a processing method is matched. Safety warning and protection measures are taken for the karst cave, the problem that tourists cannot be timely and effectively guided in the sightseeing process is solved, the possibility of staying in a dangerous area is avoided, the landform of a collapse area is simulated, the problem that the range of the collapse area is not clear is avoided, and the rescue opportunity is grasped in time.

Description

Technical Field

[0001] The present invention relates to the technical field of karst cave collapse monitoring, and particularly relates to a warning and monitoring method and system for karst collapse areas. Background Art

[0002] In karst areas, karst collapse is a relatively common and serious geological disaster. Under the influence of long-term geological processes and human activities, the stability of karst caves is constantly changing and may collapse at any time. With the booming development of tourism, more and more tourist attractions are located in karst areas, and the karst caves in these scenic spots attract a large number of tourists. Once a collapse occurs, the consequences will be unimaginable. Therefore, it is extremely urgent to develop a precise and efficient warning and monitoring method and system for karst collapse areas, which can detect potential collapse risks in advance, provide a scientific basis for timely taking protective measures, and thus effectively reduce the losses caused by karst collapse.

[0003] The prior art, such as an invention patent application with the publication number of CN117371279A, discloses a method for verifying the stability of limestone at the pile tip of a cast-in-place pile foundation and the bearing capacity of the pile foundation in a karst development area, including the following steps: S1 Exploration survey and sampling; S2 Analyzing indoor tests of samples to determine the corrosion performance and physical and mechanical parameters of limestone; S3 Monitoring the groundwater level in combination with hydrogeological conditions; S4 Using data for numerical simulation to evaluate the stability of limestone; S5 Determining the pile foundation structure parameters and estimating the load according to the results, engineering design and specifications; S6 Measuring the change in the side resistance of the pile by setting up instruments and calculating the friction angle and bearing capacity to evaluate the bearing capacity of the pile foundation; S7 Setting up static load test instruments to apply load and monitoring the response and deformation characteristics to evaluate the stability of the pile foundation; S8 Analyzing the influence of limestone corrosion on the pile-soil interaction to correct the bearing capacity to determine the bearing capacity of the pile foundation. This invention combines various data collection methods, improves the reliability of the verification results, and more accurately evaluates the bearing capacity of the pile foundation by analyzing the limestone corrosion and pile-soil interaction.

[0004] In the prior art, the warning and monitoring methods and systems for karst collapse areas can meet the basic requirements, but there are also some potential defects and challenges, which are specifically reflected in the following aspects: First, the research on the internal morphology change index of karst caves in tourist attractions and the external morphology change index of karst caves in tourist attractions in the prior art is not deep enough. When monitoring the karst cave collapse area, the thickness, span and joint fissure development value of the cave roof, karst pipeline density, structural hardness of each mineral, insoluble content, permeability, elastic modulus and Poisson's ratio of each rock type outside the karst cave in the tourist attraction, and the surface slope variation coefficient in each time period have a crucial impact on the collapse change of the dangerous area, increasing the risk of karst cave deformation and rupture, resulting in the bending deformation of the cave roof, damaging the integrity of the roof, accelerating the dissolution and erosion process of the rock, forming cavities and weak parts, reducing the stability of the cave, increasing the risk of collapse, and then triggering ground collapse and geological disasters such as ground fissures, further affecting the geological stability of the scenic area.

[0005] Second, in the prior art, the attention to the collapse risk of karst caves in tourist attractions, the classification of karst collapse risk area levels, and the matching treatment methods is not high. Due to the lack of the level and regional division of the risk area, the problem that tourists may enter high-risk areas without knowing it is increased, and the risk of being trapped in the cave is increased. Due to the lack of clear safety warnings and protection measures, tourists cannot be guided in a timely and effective manner during the tour, increasing the possibility of staying in dangerous areas, thus increasing the casualty probability. Due to the lack of geomorphic simulation of the collapse area, the scope is unclear, and there is no pre-developed rescue plan for different risk level areas, resulting in difficulty for rescue personnel to quickly determine the size and distribution of the dangerous area and delaying the rescue time. Summary of the Invention

[0006] The purpose of the present invention is to provide a warning and monitoring method and system for karst collapse areas, which solves the problems in the background technology.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a warning and monitoring method for karst collapse areas, including Step 1, karst cave monitoring, Step 2, ground settlement monitoring, and Step 3, karst cave warning and management.

[0008] Step 1, karst cave monitoring: By monitoring the karst caves in the tourist attraction in real time, cave data is obtained, and then the internal morphology change index of the karst caves in the tourist attraction is evaluated.

[0009] Step 2. Ground settlement monitoring: By arranging ground settlement monitoring points in the concentrated area of karst cave landforms in the tourist scenic area, using a level and GPS equipment for monitoring, regularly measuring the ground data in the concentrated area of karst cave landforms, and analyzing the external form change index of the karst caves in the tourist scenic area.

[0010] Step 3. Cave warning and management: Based on the obtained internal form change index of the karst caves in the tourist scenic area and the external form change index of the karst caves in the tourist scenic area, analyze the collapse risk of the karst caves in the tourist scenic area, divide the karst collapse risk area levels, and match the treatment methods.

[0011] Furthermore, for the internal form change index of the karst caves in the tourist scenic area, the specific analysis method is as follows: Based on the obtained cave data, where the cave data includes cave roof data and cave wall data, and then analyze the stability index h of the cave roof and the stability index k of the cave wall of the karst caves in the tourist scenic area. Then analyze the internal form change index of the karst caves in the tourist scenic area, and its specific calculation formula is:

[0012]

[0013] Furthermore, for the stability index of the cave roof of the karst caves in the tourist scenic area, the specific analysis method is as follows: Based on the obtained cave roof data, where the cave roof data includes the thickness, span, and joint fissure development value of the cave roof of the karst caves in the tourist scenic area at each time period, and extract the thickness safety interval, safety span interval, and joint fissure development safety interval of the cave roof of the karst caves in the tourist scenic area from the database. Then analyze the stability index of the cave roof of the karst caves in the tourist scenic area, and its specific calculation formula is: s ip represents the p-th data of the cave roof of the karst caves in the tourist scenic area at the i-th time period, where i represents the number of the time period, i = 1, 2,..., l, s p ' represents the safety interval of the p-th data of the cave roof of the karst caves in the tourist scenic area, p ∈ [1, 3].

[0014] Furthermore, for the stability index of the cave wall of the karst caves in the tourist scenic area, the specific analysis method is as follows: Based on the obtained cave wall data, where the cave wall data includes: karst pipeline density, the structural hardness of each mineral, the insoluble content, and the permeability. Take the ratio of the permeability of each mineral in the cave wall of the karst caves in the tourist scenic area to the insoluble content to obtain the corrosion value of each mineral in the cave wall of the karst caves in the tourist scenic area, and extract the karst pipeline reference density, the structural reference hardness of each mineral, and the corrosion reference value of the cave wall of the karst caves in the tourist scenic area from the database. Then analyze the stability index of the cave wall of the karst caves in the tourist scenic area, and its specific calculation formula is: Among them, d represents the reference density of karst pipelines on the cave wall of the karst cave in the tourist scenic area, d' represents the density of karst pipelines on the cave wall of the karst cave in the tourist scenic area, and f t represents the reference structural hardness of the t-th mineral type on the cave wall of the karst cave in the tourist scenic area, and f t ' represents the structural hardness of the t-th mineral type on the cave wall of the karst cave in the tourist scenic area, and m t represents the reference corrosion value of the t-th mineral type on the cave wall of the karst cave in the tourist scenic area, and m t ' represents the corrosion value of the t-th mineral type on the cave wall of the karst cave in the tourist scenic area, where t represents the number of the mineral type, t = 1, 2,..., n, and n represents the number of mineral types.

[0015] Furthermore, for the external form change index of the karst cave in the tourist scenic area, its specific analysis method is as follows: Based on the obtained ground data of the karst cave geomorphic concentration area, where the ground data includes: the elastic modulus, Poisson's ratio of each rock type outside the karst cave in the tourist scenic area, and the surface slope variation coefficient of each time period, and extract the reference elastic modulus of the rock outside the karst cave in the tourist scenic area and the reference Poisson's ratio from the database, and analyze the external form change index of the karst cave in the tourist scenic area. Its specific calculation formula is: a represents the reference elastic modulus of the rock outside the karst cave in the tourist scenic area, and a w ' represents the elastic modulus of the w-th rock type outside the karst cave in the tourist scenic area, m represents the reference Poisson's ratio of the outside of the karst cave in the tourist scenic area, and m w ' represents the Poisson's ratio of the w-th rock type outside the karst cave in the tourist scenic area, and v i represents the surface slope variation coefficient of the w-th time period outside the karst cave in the tourist scenic area, w represents the number of the rock type, w = 1, 2,..., q, and q represents the number of rock types.

[0016] Furthermore, for the collapse risk of the karst cave in the tourist scenic area and the classification of the karst collapse risk area level, its specific analysis method is as follows: According to the internal form change index of the karst cave in the tourist scenic area and the external form change index of the karst cave in the tourist scenic area, if (α≥α')∧(θ≥θ'), then the karst collapse risk area is classified into the first risk level, where ∧ is a logical symbol representing and, α and θ represent the internal form change index and the external form change index of the karst cave in the tourist scenic area respectively, and α' and θ' are the preset thresholds of the internal form change index and the external form change index of the karst cave in the tourist scenic area respectively.

[0017] If (α≥α') ∨ (θ≥θ'), the karst collapse risk area is divided into the second risk level, where ∨ is a logical symbol representing "or".

[0018] If (α<α') ∧ (θ<θ'), the karst collapse risk area is divided into the third risk level.

[0019] Furthermore, for the matching processing method, the specific analysis method is as follows: When the karst collapse risk area is at the first risk level and the second risk level, it indicates a relatively high risk of karst cave collapse. Obtain the cave roof data and cave wall data from the cave data, generate a set of cave characteristic values for the karst collapse risk area, and combine it with the set of suitable cave characteristic values of the monitoring methods stored in the database for comprehensive analysis to match the suitable processing method for the karst collapse risk area as the first-level processing method. Simulate the landform and scope formed after the collapse, and perform path planning to remind the staff in the scenic area to arrange the evacuation of tourists and close the karst collapse risk area.

[0020] When the karst collapse risk area is at the third risk level, it indicates a relatively low risk of karst cave collapse. Obtain the ground data of the karst cave landform concentration area, generate a set of reinforcement characteristic values for the karst collapse risk area, and combine it with the set of suitable reinforcement characteristic values of the monitoring methods stored in the database for comprehensive analysis to match the suitable reinforcement processing method for the karst collapse risk area as the second-level processing method. Remind the staff in the scenic area to give safety warnings, place safety warning signs and protective measures, and limit the flow of tourists within each time period.

[0021] The second aspect of the present invention provides a system for implementing the above karst collapse area early warning and monitoring method, which is characterized in that it includes: A karst cave monitoring module: By monitoring the karst caves in the tourist scenic area in real time, obtain cave data, and then evaluate the internal form change index of the karst caves in the tourist scenic area.

[0022] A ground settlement monitoring module: By arranging ground settlement monitoring points in the karst cave landform concentration area of the tourist scenic area, using a level and GPS equipment for monitoring, regularly measure the ground data of the karst cave landform concentration area, and analyze the external form change index of the karst caves in the tourist scenic area.

[0023] A karst cave early warning and management module: Based on the obtained internal form change index of the karst caves in the tourist scenic area and the external form change index of the karst caves in the tourist scenic area, analyze the collapse risk of the karst caves in the tourist scenic area, divide the karst collapse risk area level, and match the processing method.

[0024] The beneficial effects of the present invention are as follows: First, in Step 1, karst cave monitoring, and Step 2, ground settlement monitoring, by real-time monitoring of karst caves in a tourist scenic area, cave data are obtained, and then the internal form change index of the karst caves in the tourist scenic area is evaluated. By arranging ground settlement monitoring points in the concentrated area of karst cave landforms in the tourist scenic area and using a level and GPS equipment for monitoring, the ground data in the concentrated area of karst cave landforms are measured regularly, and the external form change index of the karst caves in the tourist scenic area is analyzed. This reduces the risk of deformation and rupture of karst caves, avoids the occurrence of bending deformation of the roof of karst caves, improves the integrity of the roof, slows down the dissolution and erosion process of rocks, avoids the formation of cavities and weak parts, improves the stability of the cave, and further reduces the risk of collapse, thus avoiding the risk of triggering geological disasters such as ground collapse and ground fissures, and further improving the geological stability of the scenic area.

[0025] Second, in Step 3, karst cave warning and management, based on the obtained internal form change index of the karst caves in the tourist scenic area and the external form change index of the karst caves in the tourist scenic area, the collapse risk of the karst caves in the tourist scenic area is analyzed, the karst collapse risk area level is divided, and corresponding treatment methods are matched. Since the levels and areas of the risk areas are divided, the problem that tourists may enter the dangerous risk area without knowing it is avoided, and the risk of being trapped in the cave is reduced. Since clear safety warnings and protective measures are taken for karst caves, the problem that tourists cannot get timely and effective guidance during the tour is reduced, and the possibility of staying in dangerous areas is avoided, thus reducing the casualty probability. The topographic simulation of the collapsed area avoids the problem of unclear scope of the collapsed area, and then a rescue plan for different risk level areas is formulated in advance, thus reducing the problem that rescue personnel cannot determine the size and distribution of dangerous areas in time and grasping the rescue opportunity in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0027] Figure 1 It is a schematic flow chart of the implementation steps of the method of the present invention.

[0028] Figure 2 It is a schematic connection diagram of the system structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] Referring to Figure 1 as shown, the present invention provides a warning and monitoring method for karst collapse areas, including: Step 1, monitoring of karst caves, Step 2, monitoring of ground settlement, and Step 3, warning and management of karst caves.

[0031] Step 1, monitoring of karst caves: By monitoring the karst caves in the tourist scenic area in real time, cave data is obtained, and then the internal form change index of the karst caves in the tourist scenic area is evaluated.

[0032] In the above embodiment, for the internal form change index of the karst caves in the tourist scenic area, the specific analysis method is: Based on the obtained cave data, where the cave data includes cave roof data and cave wall data, and then the stability index h of the cave roof and the stability index k of the cave wall of the karst caves in the tourist scenic area are analyzed. Further, the internal form change index of the karst caves in the tourist scenic area is analyzed, and its specific calculation formula is:

[0033]

[0034] In the above embodiment, for the stability index of the cave roof of the karst caves in the tourist scenic area, the specific analysis method is: Based on the obtained cave roof data, where the cave roof data includes the thickness, span, and joint fissure development value of the cave roof of the karst caves in the tourist scenic area at each time period, and the thickness safety interval, safety span interval, and joint fissure development safety interval of the cave roof of the karst caves in the tourist scenic area are extracted from the database. Further, the stability index of the cave roof of the karst caves in the tourist scenic area is analyzed, and its specific calculation formula is: s ip represents the p-th data of the cave roof of the karst caves in the tourist scenic area at the i-th time period, where i represents the number of the time period, i = 1, 2,..., l, s p ' represents the safety interval of the p-th data of the cave roof of the karst caves in the tourist scenic area, p ∈ [1, 3].

[0035] It should be noted that the span of the cave roof at each time period of the karst cave in the tourist scenic area is obtained through 3D laser scanning technology. The span refers to the horizontal width of the chamber or tunnel supported by the cave roof and is one of the key factors affecting the stability of the roof. A larger span will cause the roof to bear a greater load and reduce its stability. For example, in some large karst caves, the span may reach dozens of meters or even hundreds of meters.

[0036] It should be noted that the thickness of the cave roof at each time period of the karst cave in the tourist scenic area is obtained through 3D laser scanning technology. The thickness is an important indicator for measuring the strength and stability of the roof. Sufficient thickness can provide better load-bearing capacity and resist the pressure from the upper rocks and soil.

[0037] It should be noted that the joint fracture development value of the cave roof at each time period of the karst cave in the tourist scenic area is obtained through 3D laser scanning technology. The joint fracture development value refers to the cracks or fracture surfaces in the rock, and its development value directly affects the integrity and stability of the roof. A roof with fewer joint fractures and good cementation has stronger integrity and higher stability; conversely, a roof with dense and penetrating joint fractures is prone to geological disasters such as collapse.

[0038] In the above embodiment, the specific analysis method for the stability index of the cave wall of the karst cave in the tourist scenic area is as follows: Based on the obtained cave wall data, where the cave wall data includes: karst pipeline density, structural hardness of each mineral, insoluble content, and permeability, the ratio of the permeability of each mineral in the cave wall of the karst cave in the tourist scenic area to the insoluble content is processed to obtain the corrosion value of each mineral in the cave wall of the karst cave in the tourist scenic area, and the reference density of karst pipelines, the reference structural hardness of each mineral, and the reference corrosion value of the cave wall of the karst cave in the tourist scenic area are extracted from the database, and then the stability index of the cave wall of the karst cave in the tourist scenic area is analyzed. The specific calculation formula is: where d represents the reference density of karst pipelines in the cave wall of the karst cave in the tourist scenic area, d' represents the density of karst pipelines in the cave wall of the karst cave in the tourist scenic area, f t represents the reference structural hardness of the t-th mineral type in the cave wall of the karst cave in the tourist scenic area, f t ' represents the structural hardness of the t-th mineral type in the cave wall of the karst cave in the tourist scenic area, m t represents the reference corrosion value of the t-th mineral type in the cave wall of the karst cave in the tourist scenic area, m t ' represents the corrosion value of the t-th mineral type in the cave wall of the karst cave in the tourist scenic area, where t represents the number of the mineral type, t = 1, 2,..., n, and n represents the number of mineral types.

[0039] It should be noted that the insoluble content of each mineral type in the cave wall of the karst cave in the tourist scenic area refers to the proportion of insoluble minerals in the rock. The insoluble content of each mineral type is obtained by a spectrometer, which is relatively mature in the prior art and is specifically represented by a value between 0 and 1.

[0040] It should be noted that the karst conduit density refers to the length or number of karst conduits per unit area, which is obtained through geological radar monitoring. Karst conduits are the main channels for groundwater flow in karst areas, and their density directly affects the collapse risk of karst caves.

[0041] Step 2: Ground settlement monitoring: By arranging ground settlement monitoring points in the concentrated area of karst cave landforms in the tourist scenic area, using a level and GPS equipment for monitoring, regularly measuring the ground data in the concentrated area of karst cave landforms, and analyzing the external form change index of the karst caves in the tourist scenic area.

[0042] In the above embodiment, the specific analysis method of the external form change index of the karst caves in the tourist scenic area is as follows: Based on the obtained ground data in the concentrated area of karst cave landforms, where the ground data includes: the elastic modulus, Poisson's ratio of each rock type outside the karst caves in the tourist scenic area, and the surface slope variation coefficient for each time period, and extracting the reference elastic modulus of the rock outside the karst caves in the tourist scenic area and the reference Poisson's ratio from the database, analyzing the external form change index of the karst caves in the tourist scenic area. The specific calculation formula is: a represents the reference elastic modulus of the rock outside the karst caves in the tourist scenic area, a w ' represents the elastic modulus of the w-th rock type outside the karst caves in the tourist scenic area, m represents the reference Poisson's ratio of the rock outside the karst caves in the tourist scenic area, m w ' represents the Poisson's ratio of the w-th rock type outside the karst caves in the tourist scenic area, v i represents the surface slope variation coefficient of the w-th time period outside the karst caves in the tourist scenic area, w represents the rock type number, w = 1, 2,..., q, and q represents the number of rock types.

[0043] It should be noted that the rock elastic modulus refers to the ease of elastic deformation of the rock when subjected to external forces. The propagation speed of sound waves in the rock detected by a sonic detector is closely related to the elastic modulus of the rock. By measuring the propagation time and distance of sound waves in the rock, calculating the sound wave speed, and then obtaining the elastic modulus of the rock. Rocks with a higher elastic modulus produce less deformation when stressed and can better maintain the flatness and stability of the ground surface.

[0044] It should be noted that Poisson's ratio refers to the ratio of lateral strain to axial strain of rock under axial stress. By arranging seismic wave transmitters and receivers outside the karst cave, seismic waves are excited and their propagation characteristics in the rock are recorded. By analyzing the propagation speed and amplitude attenuation of seismic waves, combined with information such as rock density, a relationship model between seismic wave velocity and rock elastic modulus and Poisson's ratio is established, and then the Poisson's ratio of the rock is obtained. The size of the Poisson's ratio affects the lateral deformation capacity of the rock, which is of great significance for evaluating the stability of the roof under complex stress states.

[0045] It should be noted that the coefficient of variation of surface slope is an indicator to measure the degree of change of surface slope. The larger the value, the more drastic the change of surface slope. In GIS software, based on the constructed digital terrain model, the slope analysis algorithm is used, and based on the elevation change rate of the terrain surface, the surface slope value is obtained by calculating the elevation difference and horizontal distance of the triangle vertices. The calculated surface slope value is used as the data set, and the mean surface slope and the standard deviation of the surface slope are statistically calculated. The standard deviation of the surface slope is then ratioed with the mean surface slope to obtain the coefficient of variation of the surface slope. The coefficient of variation reflects the degree of spatial discreteness of the surface slope. The larger its value, the more drastic the change of the surface slope.

[0046] In step one, karst cave monitoring, and step two, ground subsidence monitoring, the karst caves in the scenic area are monitored in real time to obtain cave data, thereby evaluating the internal morphological change index of the karst caves in the scenic area. Ground subsidence monitoring points are arranged in the karst cave landform concentration area of ​​the scenic area, and monitoring is carried out using levels and GPS equipment. Ground data of the karst cave landform concentration area is regularly measured, and the external morphological change index of the karst caves in the scenic area is analyzed. This reduces the risk of deformation and rupture of the karst caves, avoids the occurrence of bending and deformation of the roof of the karst cave, improves the integrity of the roof, slows down the dissolution and erosion process of the rock, avoids the formation of cavities and weak parts, improves the stability of the cave, thereby reducing the risk of collapse, thereby avoiding the risk of causing ground collapse and ground fissures and other geological disasters, and further improves the geological stability of the scenic area.

[0047] Step 3. Karst cave warning and management: Based on the internal morphological change index and external morphological change index of the karst caves in the tourist attractions, the collapse risk of the karst caves in the tourist attractions is analyzed, the karst collapse risk area level is divided, and the treatment method is matched.

[0048] In the above embodiments, the collapse risk of the karst caves in the tourist scenic area is evaluated, and the karst collapse risk area levels are divided. The specific analysis method is as follows: Based on the internal form change index and the external form change index of the karst caves in the tourist scenic area, if (α≥α')∧(θ≥θ'), the karst collapse risk area is classified as the first risk level, where ∧ is a logical symbol representing "and", α and θ represent the internal form change index and the external form change index of the karst caves in the tourist scenic area respectively, and α' and θ' are the preset thresholds of the internal form change index and the external form change index of the karst caves in the tourist scenic area respectively.

[0049] If (α≥α')∨(θ≥θ'), the karst collapse risk area is classified as the second risk level, where ∨ is a logical symbol representing "or".

[0050] If (α<α')∧(θ<θ'), the karst collapse risk area is classified as the third risk level.

[0051] In the above embodiments, the matching processing method has the following specific analysis method: When the karst collapse risk area is at the first and second risk levels, it indicates a relatively high risk of karst cave collapse. The cave roof data and cave wall data are obtained from the cave data to generate a set of cave characteristic values for the karst collapse risk area. Combining with the set of suitable cave characteristic values of the monitoring methods stored in the database, comprehensive analysis is carried out to match the suitable processing method for the karst collapse risk area, which is used as the first-level processing method. The landform and scope formed after the simulated collapse are analyzed, and path planning is carried out to remind the staff in the scenic area to arrange the evacuation of tourists and close the karst collapse risk area.

[0052] When the karst collapse risk area is at the third risk level, it indicates a relatively low risk of karst cave collapse. The ground data of the karst cave geomorphic concentration area is obtained to generate a set of reinforcement characteristic values for the karst collapse risk area. Combining with the set of suitable reinforcement characteristic values of the monitoring methods stored in the database, comprehensive analysis is carried out to match the suitable reinforcement processing method for the karst collapse risk area, which is used as the second-level processing method. Remind the staff in the scenic area to give safety warnings, place safety warning signs and protective measures, and limit the flow of tourists within each time period.

[0053] It should be noted that the set of cave characteristic values of the karst collapse risk area includes the thickness, span, and joint fracture development value of the cave roof at each time period of the karst caves in the tourist scenic area, the karst pipeline density, the structural hardness of each mineral, the insoluble content, and the permeability.

[0054] It should be noted that the thickness, span, development value of joint fissures, density of karst pipelines, structural hardness, insoluble content and permeability of each mineral in the cave roof at each time period of the karst cave jointly determine the treatment method of the first grade.

[0055] It should be noted that the set of reinforcement characteristic values in the karst collapse risk area includes: elastic modulus, Poisson's ratio of each rock type outside the karst cave in the tourist scenic area, and surface slope variation coefficient at each time period.

[0056] It should be noted that the elastic modulus, Poisson's ratio of each rock type outside the karst cave in the tourist scenic area and the surface slope variation coefficient at each time period jointly determine the treatment method of the second risk grade.

[0057] It should be noted that for the treatment method of the second grade, according to the elastic modulus and Poisson's ratio of the rock, reinforcement materials with corresponding mechanical properties are selected, such as concrete or steel with high strength and high elastic modulus. For rocks with low elastic modulus and high Poisson's ratio, more flexible reinforcement materials may need to be selected to adapt to the deformation characteristics of the rock. The reinforcement methods can include anchor rods, anchor cables, steel meshes, etc. The specific selection should be determined according to the actual situation of the rock and the reinforcement requirements. Before reinforcement, the rock surface should be cleaned and trimmed to ensure that the reinforcement materials can closely adhere to the rock surface. Install reinforcement materials such as anchor rods, anchor cables or steel meshes according to the design requirements to ensure that the spacing and depth of the reinforcement materials meet the requirements. During the reinforcement process, the quality of the reinforcement materials and the construction technology should be strictly controlled to ensure the reinforcement effect. Adjust the reinforcement plan according to the size of the surface slope variation coefficient. For areas with steeper surface slopes, the reinforcement measures should be strengthened, such as increasing the number and length of anchor rods and anchor cables. For areas with gentler surface slopes, the quantity and length of the reinforcement materials can be appropriately reduced to save costs.

[0058] Refer to Figure 2 As shown, the present invention provides a system for a warning and monitoring method for a karst collapse area, which is characterized in that it includes: a karst cave monitoring module: by performing real-time monitoring on the karst caves in the tourist scenic area, cave data is obtained, and then the internal form change index of the karst caves in the tourist scenic area is evaluated.

[0059] A ground settlement monitoring module: by arranging ground settlement monitoring points in the concentrated area of the karst cave landform in the tourist scenic area, monitoring is carried out using a level and GPS equipment, regularly measuring the ground data in the concentrated area of the karst cave landform in the tourist scenic area, and analyzing the external form change index of the karst caves in the tourist scenic area.

[0060] Karst Cave Warning and Management Module: Based on the obtained internal morphological change index and external morphological change index of the karst cave in the tourist scenic area, analyze the collapse risk of the karst cave in the tourist scenic area, classify the levels of the karst collapse risk areas, and match the treatment methods.

[0061] In Step 3, Karst Cave Warning and Management, based on the obtained internal morphological change index and external morphological change index of the karst cave in the tourist scenic area, analyze the collapse risk of the karst cave in the tourist scenic area, classify the levels of the karst collapse risk areas, and match the treatment methods. Since the levels and areas of the risk areas are classified, it avoids the problem that tourists may enter high-risk areas without knowing it, reduces the risk of being trapped in the cave. Since clear safety warnings and protective measures are taken for the karst cave, it reduces the problem that tourists cannot get timely and effective guidance during the tour, and avoids the possibility of staying in dangerous areas, thus reducing the casualty probability. The geomorphic simulation of the collapsed area avoids the problem of unclear scope of the collapsed area, and then pre-formulates rescue plans for different risk-level areas, further reducing the problem that rescue personnel cannot determine the size and distribution of dangerous areas in time, and grasping the rescue opportunity in time.

[0062] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A karst collapse area early warning monitoring method, characterized in that: include: Step 1: Karst cave monitoring: real-time monitoring of karst caves in tourist attractions is carried out to obtain cave data, and then the internal morphological change index of karst caves in tourist attractions is evaluated; Step 2: Ground subsidence monitoring: by arranging ground subsidence monitoring points in the concentrated areas of karst cave landforms in tourist attractions, using leveling instruments and GPS equipment for monitoring, regularly measuring ground data in the concentrated areas of karst cave landforms, and analyzing the external morphological change index of karst caves in tourist attractions; Step 3. Karst cave warning and management: Based on the internal morphological change index and external morphological change index of the karst caves in the tourist attractions, the collapse risk of the karst caves in the tourist attractions is analyzed, the karst collapse risk area level is divided, and the treatment method is matched.

2. The karst collapse area early warning monitoring method according to claim 1 is characterized in that: The specific analysis method of the internal morphological change index of the karst cave in the tourist attraction is as follows: Based on the obtained cave data, which includes cave roof data and cave wall data, the stability index h of the cave roof and the stability index k of the cave wall of the karst cave in the tourist attraction are analyzed, and the internal morphological change index of the karst cave in the tourist attraction is analyzed. The specific calculation formula is:

3. The karst collapse area early warning monitoring method according to claim 2 is characterized in that: The specific analysis method of the stability index of the cave roof of the karst cave in the tourist attraction is as follows: Based on the obtained cave roof data, the cave roof data includes the thickness, span and joint and fissure development values ​​of the cave roof in each time period of the karst cave in the tourist scenic area, and the thickness safety interval, safety span interval and joint and fissure development safety interval of the cave roof of the karst cave in the tourist scenic area are extracted from the database, and then the stability index of the cave roof of the karst cave in the tourist scenic area is analyzed, and the specific calculation formula is: s ip It represents the pth data of the cave roof in the i-th time period of the karst cave in the tourist attraction, where i represents the number of the time period, i = 1, 2, ..., l, s p ' represents the safety interval of the pth data of the cave roof of the karst cave in the tourist attraction, p∈[1,3].

4. The karst collapse area early warning monitoring method according to claim 2 is characterized in that: The specific analysis method of the stability index of the cave wall of the karst cave in the tourist attraction is as follows: Based on the obtained cave wall data, the cave wall data includes: karst pipeline density, structural hardness, insoluble content and permeability of each mineral, the permeability and insoluble content of each mineral on the cave wall of the karst cave in the tourist area are processed by ratio, and the dissolution value of each mineral on the cave wall of the karst cave in the tourist area is obtained. The karst pipeline reference density, structural reference hardness and dissolution reference value of each mineral on the cave wall of the karst cave in the tourist area are extracted from the database, and then the stability index of the cave wall of the karst cave in the tourist area is analyzed. The specific calculation formula is: Among them, d represents the reference density of karst pipes on the wall of karst caves in tourist attractions, d' represents the density of karst pipes on the wall of karst caves in tourist attractions, and f t It is represented by the structural reference hardness of the t-th mineral type of the cave wall of the karst cave in the tourist attraction, f t ' represents the structural hardness of the t-th mineral type on the wall of the karst cave in the tourist area, m t It is expressed as the reference value of the dissolution of the t-th mineral type on the wall of the karst cave in the tourist area, m t ' represents the dissolution value of the t-th mineral type on the wall of the karst cave in the tourist attraction, where t represents the number of the mineral type, t=1, 2, ..., n, and n represents the number of mineral types.

5. The karst collapse area early warning monitoring method according to claim 1 is characterized in that: The specific analysis method of the external morphological change index of the karst caves in the tourist scenic area is as follows: Based on the obtained ground data of the concentrated area of ​​karst cave landforms, the ground data includes: the elastic modulus, Poisson's ratio and surface slope variation coefficient of each rock type outside the karst caves in the tourist scenic area in each time period, and the reference elastic modulus and reference Poisson's ratio of the rock outside the karst caves in the tourist scenic area are extracted from the database to analyze the external morphological change index of the karst caves in the tourist scenic area. The specific calculation formula is: a represents the rock elasticity reference modulus outside the karst cave in the tourist area, a w ' represents the elastic modulus of the wth rock type outside the karst cave of the tourist attraction, m represents the reference Poisson's ratio outside the karst cave of the tourist attraction, m w ' represents the Poisson's ratio of the wth rock type outside the karst cave in the tourist area, v i It is represented as the coefficient of variation of the surface slope in the w-th time period outside the karst cave of the tourist attraction, w represents the number of the rock type, w=1, 2, ..., q, and q represents the number of rock types.

6. The karst collapse area early warning monitoring method according to claim 1, characterized in that: The collapse risk of karst caves in the tourist attractions is divided into karst collapse risk area levels, and the specific analysis method is as follows: According to the internal morphological change index of the karst caves in the tourist attractions and the external morphological change index of the karst caves in the tourist attractions, if (α≥α')∧(θ≥θ'), the karst collapse risk area is divided into the first risk level, where ∧ is a logical symbol, which represents and, α and θ represent the internal morphological change index and the external morphological change index of the karst caves in the tourist attractions, and α' and θ' are the preset internal morphological change index threshold and the external morphological change index threshold of the karst caves in the tourist attractions, respectively; If (α≥α')∨(θ≥θ'), the karst collapse risk area is classified as the second risk level, where ∨ is a logical symbol, indicating or; If (α<α')∧(θ<θ'), the karst collapse risk area is classified as the third risk level.

7. The karst collapse area early warning monitoring method according to claim 1 is characterized in that: The matching processing method, its specific analysis method is: When the karst collapse risk area is at the first risk level or the second risk level, it indicates that the karst cave has a high risk of collapse. The cave roof data and cave wall data are obtained from the cave data to generate a cave feature value set for the karst collapse risk area. Combined with the appropriate cave feature value set of the monitoring method stored in the database, a comprehensive analysis is performed to match the appropriate treatment method for the karst collapse risk area as the first-level treatment method, simulate the landform and range formed after the collapse, and perform path planning to remind the staff in the scenic area to arrange for the evacuation of tourists and close the karst collapse risk area. When the karst collapse risk area is at the third risk level, it indicates that the risk of karst cave collapse is relatively low. The ground data of the concentrated area of ​​karst cave landforms is obtained to generate a set of reinforcement characteristic values ​​for the karst collapse risk area. Combined with the appropriate reinforcement characteristic value set of the monitoring method stored in the database, a comprehensive analysis is conducted to match the appropriate reinforcement treatment method for the karst collapse risk area as the second-level treatment method, reminding the staff in the scenic area to provide safety tips, place safety warning signs and protective measures, and limit the flow of tourists in each time period.

8. A system for executing the karst collapse area early warning monitoring method according to any one of claims 1 to 7, characterized in that: include: Karst cave monitoring module: through real-time monitoring of karst caves in tourist attractions, cave data is obtained, and then the internal morphological change index of karst caves in tourist attractions is evaluated; Ground subsidence monitoring module: by arranging ground subsidence monitoring points in the concentrated areas of karst cave landforms in tourist attractions, using leveling instruments and GPS equipment for monitoring, regularly measuring ground data in the concentrated areas of karst cave landforms, and analyzing the external morphological change index of karst caves in tourist attractions; Karst cave early warning and management module: Based on the internal morphological change index of the karst caves in the tourist scenic area and the external morphological change index of the karst caves in the tourist scenic area, the collapse risk of the karst caves in the tourist scenic area is analyzed, the karst collapse risk area level is divided, and the treatment method is matched.

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