CN117078749B - Mountain falling stone on-line early warning and monitoring system - Google Patents
Mountain falling stone on-line early warning and monitoring system Download PDFInfo
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Abstract
The invention provides an online early warning and monitoring system for mountain falling rocks, and relates to the technical field of slump. According to the mountain falling stone online early warning and monitoring system, an initial monitoring picture is acquired, wherein the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is built based on the initial monitoring picture, then a collapse-prone point location is determined according to the first mountain three-dimensional model, a second mountain three-dimensional model is acquired based on the first mountain three-dimensional model and the collapse-prone point location, the second mountain three-dimensional model is an early warning mountain collapse-behind model, and finally a collapse area is acquired according to the second mountain three-dimensional model. The on-line early warning and monitoring system for the mountain falling rocks can calculate the slump area through the computer model, does not need to add on-site full-time guardianship personnel, and ensures personnel safety. The invention also provides an online early warning and monitoring method for the mountain falling rocks.
Description
Technical Field
The invention relates to the technical field of slump, in particular to an online early warning and monitoring system for mountain falling rocks.
Background
Some roads follow the mountain and river, and one side of the road is close to the mountain. The mountain is steep in slope, the vegetation is rare, the seasonal temperature difference change is large, part of mountain bodies are not treated by engineering measures, mountain rock is easy to loose and fall off and directly falls on a road, traffic is hindered, and potential safety hazards to roads, pedestrians and passing vehicles are particularly large, so that people are more likely to be threatened. The safety awareness of staff is affected by various factors, and once a falling stone disaster occurs, the staff places the staff in risk, and the safety of other assets on the site can be affected. At present, the treatment mode adopted by the method is still to add on-site full-time guardianship personnel, and the technical measures for guaranteeing the safety have no obvious technical innovation.
Disclosure of Invention
The embodiment of the invention provides a mountain falling stone online early warning and monitoring system and method, which aim to solve or partially solve the problems in the background technology.
In order to solve the technical problems, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides an online early warning and monitoring method for mountain falling rocks, where the method includes: acquiring an initial monitoring picture, wherein the initial monitoring picture is an early warning mountain image, and a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model; determining a slump point according to the first mountain three-dimensional model; acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the collapse prone point, wherein the second mountain three-dimensional model is a model after early warning mountain collapse; and obtaining a slump area according to the second mountain three-dimensional model.
It can be appreciated that in this step, an initial monitoring picture of the pre-warning mountain is acquired. This may be obtained by using remote sensing techniques such as satellite images or images taken by unmanned aerial vehicles. As an embodiment, we can use image processing and analysis techniques to process the resulting initial monitoring picture. The method comprises the steps of removing noise, enhancing image quality and the like so as to obtain clear early warning mountain images.
With reference to the first aspect, in some possible implementations, the acquiring an initial monitoring picture, where the initial monitoring picture is an early warning mountain image, establishing a first mountain three-dimensional model based on the initial monitoring picture, where the first mountain three-dimensional model is the early warning mountain initial model includes: acquiring a plurality of initial monitoring pictures, wherein the initial monitoring pictures are the early warning mountain images shot at different angles; determining a first positioning point according to the initial monitoring pictures, wherein the first positioning point is a point in the first mountain three-dimensional model; and acquiring the second mountain three-dimensional model based on the first positioning point.
It will be appreciated that in this step, the initial monitoring frames are spatially matched by the first positioning point. The goal of image matching is to find common feature points in multiple images to determine their location in three-dimensional space. In this embodiment, one image may be selected as the reference image. This image will serve as a basis for the first location point. One or more points with obvious characteristics are selected as first positioning points in the reference image. These points should be clearly identifiable in other images as well. Of course, in other embodiments, an image matching algorithm may also be used to find points in other images that correspond to the first location point in the reference image. This can be achieved by calculating the degree of matching between feature points. For the matching points in each image, it is corresponding to points in the first mountain three-dimensional model. This can be achieved by converting the image coordinates into model coordinates. If there are multiple matching points, coordinate transformation may be performed using a method such as triangulation. In image matching and coordinate conversion, the coordinate system between the image and the model is ensured to be consistent, and accurate parameters are used for conversion. In addition, it is also necessary to ensure high image quality, obvious feature points, and to use appropriate image processing and matching algorithms to improve the accuracy of matching.
The second aspect of the invention provides an online early warning and monitoring system for mountain falling rocks, which comprises:
the system comprises a first acquisition module, a second acquisition module and a first control module, wherein the first acquisition module is used for acquiring an initial monitoring picture, the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model;
the first determining module is used for determining a collapse-prone point position according to the first mountain three-dimensional model;
the third determining module is used for acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the easy-collapse point location, wherein the second mountain three-dimensional model is a model after the collapse of the early-warning mountain;
and the second determining module is used for acquiring a slump area according to the second mountain three-dimensional model and generating on-line alarm information according to the slump area.
With reference to the second aspect, in some embodiments, the first determining module includes:
the second acquisition module is used for acquiring satellite images, wherein the satellite images are images of the early warning mountain;
the first building module is used for building a first mountain three-dimensional model based on the satellite image and the initial monitoring picture.
With reference to the second aspect, in some embodiments, the first establishing module includes:
the third acquisition module is used for acquiring a plurality of initial monitoring pictures and a plurality of satellite images, wherein the initial monitoring pictures are the early warning mountain images shot at different angles;
the fourth determining module is used for determining a first positioning point according to the initial monitoring pictures and the satellite images, wherein the first positioning point is a point in the first mountain three-dimensional model;
the second building module is used for building the first mountain three-dimensional model based on the first positioning point.
With reference to the second aspect, in some embodiments, the fourth determining module includes:
a fifth determining module, configured to determine a target positioning point according to the plurality of initial monitoring frames, where the target positioning point is a point in the initial monitoring frames and the satellite image;
and the sixth determining module is used for determining a plurality of first positioning points according to the plurality of target positioning points, wherein the plurality of first positioning points and the plurality of target positioning points have a mapping relation.
With reference to the second aspect, in some embodiments, the method includes:
a seventh determining module, configured to form a plurality of slump sub-models according to the first mountain three-dimensional model, where a plurality of slump sub-models are stacked to form the first mountain three-dimensional model;
the first generation module is used for generating a plurality of simulated slump points on the first mountain three-dimensional model;
the fourth acquisition module is used for acquiring a plurality of simulation models according to the simulation slump points and the slump sub models, wherein the simulation models are models formed by the slump sub models after the simulation slump points simulate slump;
and the eighth determining module is used for determining slump points according to the scattering conditions of a plurality of slump sub-models in the simulation model.
With reference to the second aspect, in some embodiments, the seventh determining module includes:
the first segmentation module is used for segmenting the first mountain three-dimensional model to form a plurality of initial slump sub-models, wherein the initial slump sub-models comprise a rock model and a surface soil model;
the first marking module is used for marking the rock model and the surface soil model based on the first mountain three-dimensional model;
and a ninth determination module for determining that the rock model is the slump sub-model.
With reference to the second aspect, in some embodiments, the fourth obtaining module includes:
the fifth acquisition module is used for acquiring the whole information and acquiring the adhesion strength among the slump sub-models according to the whole information;
and the sixth acquisition module is used for acquiring a plurality of simulation models according to the adhesion strength, the simulation slump points and the slump sub models.
A third aspect of the embodiment of the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the method steps provided by the first aspect of the embodiment of the invention when executing the program stored in the memory.
A fourth aspect of the embodiments of the present invention proposes a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as proposed in the first aspect of the embodiments of the present invention.
The embodiment of the invention has the following advantages:
according to the mountain falling stone online early warning and monitoring system, an initial monitoring picture is acquired, wherein the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is built based on the initial monitoring picture, then a collapse-prone point location is determined according to the first mountain three-dimensional model, a second mountain three-dimensional model is acquired based on the first mountain three-dimensional model and the collapse-prone point location, the second mountain three-dimensional model is an early warning mountain collapse-behind model, and finally a collapse area is acquired according to the second mountain three-dimensional model. The on-line early warning and monitoring system for the mountain falling rocks can calculate the slump area through the computer model, does not need to add on-site full-time guardianship personnel, and ensures personnel safety.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an online early warning and monitoring method for mountain falling rocks in an embodiment of the invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. It will be apparent that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that an article or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such article or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in an article or apparatus that comprises the element.
Furthermore, the terms "first," "second," and the like, are used merely for distinguishing between descriptions and not for understanding as a specific or particular structure. The description of the terms "some embodiments," "other embodiments," and the like, means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this application, the schematic representations of the above terms are not necessarily for the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples described herein, as well as features of various embodiments or examples, may be combined and combined by those skilled in the art without conflict.
The invention provides an online early warning and monitoring method for mountain falling rocks, referring to fig. 1, comprising the following steps:
s101, acquiring an initial monitoring picture, wherein the initial monitoring picture is an early warning mountain image, and a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model.
It will be appreciated that various monitoring devices, such as cameras and the like, may be used. These devices can provide real-time images of the mountain for monitoring the morphology and changes of the mountain. The first mountain three-dimensional model is an initial model of the early warning mountain, and can be used as a basis for subsequent monitoring and analysis. By comparing with the follow-up monitoring picture, the change of the mountain and the early warning signal can be found in time so as to take corresponding measures.
In some embodiments, step S101 may further include the steps of:
s101-1, acquiring satellite images, wherein the satellite images are images of the early warning mountain.
It will be appreciated that the acquisition of satellite images may be achieved by satellite telemetry. The satellite remote sensing technology utilizes a satellite-mounted sensor to observe the earth surface and collect images, and can provide image data with high resolution and wide coverage area.
In order to acquire satellite images of the pre-warning mountain, it is necessary to select suitable satellites and sensors and ensure that they provide sufficient spatial and temporal resolution to meet the monitoring requirements. Some satellites, such as Landsat, sentinel, provide high quality remote sensing images that can be used for mountain monitoring.
And S101-2, establishing a first mountain three-dimensional model based on the satellite image and the initial monitoring picture.
It can be appreciated that after the satellite image is obtained, the image needs to be processed and analyzed to extract information of the pre-warning mountain. This may include image enhancement, classification, and feature extraction using remote sensing image processing software. Through these processes and analyses, images of the pre-warning mountain can be obtained and used for subsequent modeling and monitoring work.
Specifically, step S101-2 may include the steps of:
s101-2-1, acquiring a plurality of initial monitoring pictures and a plurality of satellite images, wherein the initial monitoring pictures are the early warning mountain images shot at different angles.
S101-2-2, determining a first positioning point according to the initial monitoring pictures and the satellite images, wherein the first positioning point is a point in the first mountain three-dimensional model.
It will be appreciated that in this step, the initial monitoring frames are spatially matched by the first positioning point. The goal of image matching is to find common feature points in multiple images to determine their location in three-dimensional space. In this embodiment, one image may be selected as the reference image. This image will serve as a basis for the first location point. One or more points with obvious characteristics are selected as first positioning points in the reference image. These points should be clearly identifiable in other images as well. Of course, in other embodiments, an image matching algorithm may also be used to find points in other images that correspond to the first location point in the reference image. This can be achieved by calculating the degree of matching between feature points. For the matching points in each image, it is corresponding to points in the first mountain three-dimensional model. This can be achieved by converting the image coordinates into model coordinates. If there are multiple matching points, coordinate transformation may be performed using a method such as triangulation. In image matching and coordinate conversion, the coordinate system between the image and the model is ensured to be consistent, and accurate parameters are used for conversion. In addition, it is also necessary to ensure high image quality, obvious feature points, and to use appropriate image processing and matching algorithms to improve the accuracy of matching.
S101-2-3, based on the first positioning point, establishing the first mountain three-dimensional model.
It will be appreciated that data processing and modeling is performed using three-dimensional modeling software (e.g., autoCAD, sketchUp, 3ds Max, etc.) or Geographic Information System (GIS) software. First, the collected elevation data and topography data are correlated with coordinates of a first location point. Then, based on these data, a three-dimensional model of the first mountain is generated by algorithms such as interpolation, smoothing, fitting, and the like.
Specifically, the step S101-2-2 may include the steps of:
s101-2-2-1, determining a target positioning point according to a plurality of initial monitoring pictures, wherein the target positioning point is a point in the initial monitoring pictures and the satellite image.
It can be appreciated that the position of the target mountain in each initial monitoring picture is determined and marked by a correlation algorithm. Marking tools or software may be used to mark the location of the target mountain. For the matching point in each image, it is taken as a target locating point. Since each target anchor point is located in at least two images, one of the images can be selected as a reference, and then the corresponding point in the other image is taken as the target anchor point. Of course, each targeted anchor point may also be located in multiple initial monitoring pictures.
S101-2-2-2, determining a plurality of first positioning points according to the plurality of target positioning points, wherein the plurality of first positioning points and the plurality of target positioning points have mapping relations.
A plurality of first anchor points may be determined from a plurality of target anchor points and have a mapping relationship with the target anchor points. Therefore, accurate position mapping can be established between the monitoring picture and the satellite image, and target positioning and position comparison are convenient.
S102, determining the collapse-prone point positions according to the first mountain three-dimensional model.
Specifically, in the present embodiment, step S102 includes the steps of:
s102-1: and forming a plurality of slump sub-models according to the first mountain three-dimensional model, wherein a plurality of slump sub-models are stacked to form the first mountain three-dimensional model.
It will be appreciated that one or more points of collapse of the first mountain are determined as the case may be and as desired. These collapse points may be frangible areas on the mountain, areas where potential landslides exist, or other areas with risk of slumping. A geomechanical model or other related model is used to create a corresponding slump sub-model. The models can consider the material characteristics, geological structures, slope stability and other factors of the mountain.
Specifically, as an embodiment, step S102-1 includes the steps of:
s102-1-1: dividing the first mountain three-dimensional model to form a plurality of initial slump sub-models, wherein the plurality of initial slump sub-models comprise a rock model and a surface soil model.
S102-1-2: and marking the rock model and the surface soil model based on the first mountain three-dimensional model.
S102-1-3: and determining the rock model as the slump sub-model.
It will be appreciated that it is determined how the first mountain three-dimensional model is segmented, as required. The appropriate segmentation method may be selected based on geological conditions, material characteristics, and other relevant factors. For example, the segmentation may be based on rock and soil distribution, geologic formation lines, topographical features, and the like. Therefore, the landslide process of the mountain can be more accurately simulated, the movement track of the rock and the soil is analyzed, and a foundation is provided for the research and the prediction of mountain disasters.
S102-2: and generating a plurality of simulated slump points on the first mountain three-dimensional model.
It will be appreciated that a plurality of points in the mountain where slump is simulated are determined as required. These points may be determined based on factors such as geological conditions, topographical features, rock cracks, soil stability, and the like. The landslide or collapse-prone area on the mountain can be selected as the collapse point. These points can be used for further mountain disaster analysis, prediction and simulation to assess possible disaster risk and take corresponding safeguards and countermeasures.
S102-3: and obtaining a plurality of simulation models according to the simulation slump points and the slump sub models, wherein the simulation models are models formed by the slump sub models after the simulation slump points simulate slump.
It will be appreciated that in this manner, a plurality of simulation models may be obtained, each comprising simulation results of a particular slump sub-model after slumping at a slump point. These simulation models can be used to evaluate the adhesion performance of the different slump sub-models, predict the collapse after collapse damage range and structural response, and formulate corresponding safety measures. And combining slump sub-models used by the plurality of simulated slump points to generate a plurality of simulation models. These simulation models may represent different slump scenarios and possible disaster effects.
To circumvent the impact of geologic structures on slump models, in some embodiments, step S102-3 further comprises the steps of:
s102-3-1: and obtaining the whole information, and obtaining the adhesion strength among the slump sub-models according to the whole information.
Specifically, the whole information is acquired, and the vulnerability information can be acquired first, and the whole information is determined according to the vulnerability information. It will be appreciated that the vulnerability information may be rock joints, rock parting planes, etc. Further analysis and evaluation of the generated plurality of simulation models is performed. Simulation model analysis may be performed using specialized simulation software and tools. In the analysis process, considering the adhesion strength between the slump sub-models, different mountain disaster risks can be evaluated, and possible slump modes and disaster influences can be predicted.
S102-3-2: and obtaining a plurality of simulation models according to the adhesion strength, the simulation slump points and the slump sub models.
It will be appreciated that the whole piece of information is information of the connection between the plurality of slump sub-models. By creating a corresponding simulation model. Each slump sub-model represents a possible slump pattern that can be designed and created based on different geological, soil types, groundwater, etc. In the simulation model, the adhesion strength and other relevant parameters such as the viscosity of the soil, friction, cohesion, etc. will be considered.
S102-4: and determining slump points according to the scattering conditions of a plurality of slump sub-models in the simulation model.
It will be appreciated that the slump points are determined based on the distribution of the slump models. In general, a site is considered a slump point if it exhibits landslide in multiple slump sub-models.
And S103, acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the collapse-prone point, wherein the second mountain three-dimensional model is a model after collapse of the early-warning mountain.
It can be appreciated that the model of the second mountain is validated based on the slump simulation results of the first mountain and the determined slump points. The slump simulation result of the first mountain can be applied to the model of the second mountain to observe whether the slump effect conforming to the actual situation can be simulated.
S104, acquiring a slump area according to the second mountain three-dimensional model, and generating on-line alarm information according to the slump area.
It will be appreciated that the definition of the slump region is performed on a three-dimensional model of the second mountain according to a defined definition method. The extent and shape of the slump region may be determined based on the results of the model analysis. Generating a slump region map according to the delimited slump region. The extent of the slump area may be marked on a map or model using GIS software or drawing tools to more intuitively reveal the location and extent of the slump area.
The level of the alert is determined based on the size, depth, and possibly extent of damage to the slump area, such as emergency, severe, general, etc. Generating on-line alarm information according to the slump area and providing the on-line alarm information to related departments and the public in time so as to take corresponding emergency measures and reduce possible damages.
The invention provides an online early warning and monitoring system for mountain falling rocks, which comprises the steps of firstly, acquiring an initial monitoring picture, wherein the initial monitoring picture is an early warning mountain image, establishing a first mountain three-dimensional model based on the initial monitoring picture, then determining a collapse-prone point position according to the first mountain three-dimensional model, then acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the collapse-prone point position, wherein the second mountain three-dimensional model is an early warning mountain collapse-later model, and finally acquiring a collapse area according to the second mountain three-dimensional model. According to the mountain falling stone online early warning and monitoring method provided by the invention, the slump area can be calculated through the computer model, and the on-site full-time guardianship personnel are not required to be additionally arranged, so that the personnel safety is ensured.
The second aspect of the invention provides an online early warning and monitoring system for mountain falling rocks, which comprises:
the system comprises a first acquisition module, a second acquisition module and a first control module, wherein the first acquisition module is used for acquiring an initial monitoring picture, the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model;
the first determining module is used for determining a collapse-prone point position according to the first mountain three-dimensional model;
the third determining module is used for acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the easy-collapse point location, wherein the second mountain three-dimensional model is a model after the collapse of the early-warning mountain;
and the second determining module is used for acquiring a slump area according to the second mountain three-dimensional model and generating on-line alarm information according to the slump area.
With reference to the second aspect, in some embodiments, the first determining module includes:
the second acquisition module is used for acquiring satellite images, wherein the satellite images are images of the early warning mountain;
the first building module is used for building a first mountain three-dimensional model based on the satellite image and the initial monitoring picture.
With reference to the second aspect, in some embodiments, the first establishing module includes:
the third acquisition module is used for acquiring a plurality of initial monitoring pictures and a plurality of satellite images, wherein the initial monitoring pictures are the early warning mountain images shot at different angles;
the fourth determining module is used for determining a first positioning point according to the initial monitoring pictures and the satellite images, wherein the first positioning point is a point in the first mountain three-dimensional model;
the second building module is used for building the first mountain three-dimensional model based on the first positioning point.
With reference to the second aspect, in some embodiments, the fourth determining module includes:
a fifth determining module, configured to determine a target positioning point according to the plurality of initial monitoring frames, where the target positioning point is a point in the initial monitoring frames and the satellite image;
and the sixth determining module is used for determining a plurality of first positioning points according to the plurality of target positioning points, wherein the plurality of first positioning points and the plurality of target positioning points have a mapping relation.
With reference to the second aspect, in some embodiments, the method includes:
a seventh determining module, configured to form a plurality of slump sub-models according to the first mountain three-dimensional model, where a plurality of slump sub-models are stacked to form the first mountain three-dimensional model;
the first generation module is used for generating a plurality of simulated slump points on the first mountain three-dimensional model;
the fourth acquisition module is used for acquiring a plurality of simulation models according to the simulation slump points and the slump sub models, wherein the simulation models are models formed by the slump sub models after the simulation slump points simulate slump;
and the eighth determining module is used for determining slump points according to the scattering conditions of a plurality of slump sub-models in the simulation model.
With reference to the second aspect, in some embodiments, the seventh determining module includes:
the first segmentation module is used for segmenting the first mountain three-dimensional model to form a plurality of initial slump sub-models, wherein the initial slump sub-models comprise a rock model and a surface soil model;
the first marking module is used for marking the rock model and the surface soil model based on the first mountain three-dimensional model;
and a ninth determination module for determining that the rock model is the slump sub-model.
With reference to the second aspect, in some embodiments, the fourth obtaining module includes:
the fifth acquisition module is used for acquiring the whole information and acquiring the adhesion strength among the slump sub-models according to the whole information;
and the sixth acquisition module is used for acquiring a plurality of simulation models according to the adhesion strength, the simulation slump points and the slump sub models.
Based on the same inventive concept, the embodiments of the present application further provide an electronic device, including:
at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the mountain falling rock on-line early warning and monitoring method.
In addition, in order to achieve the above objective, an embodiment of the present application further provides a computer readable storage medium storing a computer program, where the computer program when executed by a processor implements the mountain falling stone online early warning and monitoring method of the embodiment of the present application.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (apparatus), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. "and/or" means either or both of which may be selected. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
The mountain falling stone on-line early warning and monitoring method and device provided by the invention are described in detail, and specific examples are applied to explain the principle and the implementation mode of the invention, and the description of the examples is only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (4)
1. Mountain falling rocks on-line early warning monitoring system, characterized in that, the system includes: the system comprises a first acquisition module, a second acquisition module and a first control module, wherein the first acquisition module is used for acquiring an initial monitoring picture, the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model; the first determining module is used for determining a collapse-prone point position according to the first mountain three-dimensional model; the second determining module is used for acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the easy-collapse point location, wherein the second mountain three-dimensional model is a model after the collapse of the early-warning mountain; the third determining module is used for acquiring a slump area according to the second mountain three-dimensional model and generating on-line alarm information according to the slump area;
the first determining module includes: the second acquisition module is used for acquiring satellite images, wherein the satellite images are images of the early warning mountain; the first building module is used for building a first mountain three-dimensional model based on the satellite image and the initial monitoring picture;
the first establishing module includes: the third acquisition module is used for acquiring a plurality of initial monitoring pictures and a plurality of satellite images, wherein the initial monitoring pictures are the early warning mountain images shot at different angles; the fourth determining module is used for determining a first positioning point according to the initial monitoring pictures and the satellite images, wherein the first positioning point is a point in the first mountain three-dimensional model; the second building module is used for building the first mountain three-dimensional model based on the first positioning point;
the fourth determination module includes: a fifth determining module, configured to determine a target positioning point according to the plurality of initial monitoring frames, where the target positioning point is a point in the initial monitoring frames and the satellite image; the sixth determining module is used for determining a plurality of first positioning points according to a plurality of target positioning points, wherein the plurality of first positioning points and the plurality of target positioning points have a mapping relation;
the first determining module includes: a seventh determining module, configured to form a plurality of slump sub-models according to the first mountain three-dimensional model, where a plurality of slump sub-models are stacked to form the first mountain three-dimensional model; the first generation module is used for generating a plurality of simulated slump points on the first mountain three-dimensional model; the fourth acquisition module is used for acquiring a plurality of simulation models according to the simulation slump points and the slump sub models, wherein the simulation models are models formed by the slump sub models after the simulation slump points simulate slump; and the eighth determining module is used for determining slump points according to the scattering conditions of a plurality of slump sub-models in the simulation model.
2. The mountain falling rock online early warning and monitoring system according to claim 1, wherein the seventh determining module comprises: the first segmentation module is used for segmenting the first mountain three-dimensional model to form a plurality of initial slump sub-models, wherein the initial slump sub-models comprise a rock model and a surface soil model; the first marking module is used for marking the rock model and the surface soil model based on the first mountain three-dimensional model; and a ninth determination module for determining that the rock model is the slump sub-model.
3. The mountain falling stone online early warning and monitoring system according to claim 2, wherein the fourth acquisition module comprises: the fifth acquisition module is used for acquiring the whole information and acquiring the adhesion strength among the slump sub-models according to the whole information; and the sixth acquisition module is used for acquiring a plurality of simulation models according to the adhesion strength, the simulation slump points and the slump sub models.
4. The mountain falling stone online early warning and monitoring method is characterized by comprising the following steps of: acquiring an initial monitoring picture, wherein the initial monitoring picture is an early warning mountain image, and a first mountain three-dimensional model is built based on the initial monitoring picture; determining a slump point according to the first mountain three-dimensional model; acquiring a second mountain three-dimensional model based on the first mountain three-dimensional model and the collapse prone point, wherein the second mountain three-dimensional model is a model after early warning mountain collapse; acquiring a slump area according to the second mountain three-dimensional model, and generating on-line alarm information according to the slump area;
acquiring an initial monitoring picture, wherein the initial monitoring picture is an early warning mountain image, a first mountain three-dimensional model is established based on the initial monitoring picture, and the first mountain three-dimensional model is the early warning mountain initial model, and the method comprises the following steps: acquiring satellite images, wherein the satellite images are images of the early warning mountain; establishing a first mountain three-dimensional model based on the satellite image and the initial monitoring picture;
based on the satellite image and the initial monitoring picture, a first mountain three-dimensional model is established, which comprises the following steps: acquiring a plurality of initial monitoring pictures and a plurality of satellite images, wherein the initial monitoring pictures are the early warning mountain images shot at different angles; determining a first positioning point according to the initial monitoring pictures and the satellite images, wherein the first positioning point is a point in the first mountain three-dimensional model; establishing the first mountain three-dimensional model based on the first positioning point;
determining a target positioning point according to the initial monitoring pictures, wherein the target positioning point is a point in the initial monitoring pictures and the satellite image; determining a plurality of first positioning points according to the plurality of target positioning points, wherein the plurality of first positioning points and the plurality of target positioning points have mapping relations;
forming a plurality of slump sub-models according to the first mountain three-dimensional model, wherein a plurality of slump sub-models are stacked to form the first mountain three-dimensional model; the first mountain three-dimensional model generates a plurality of simulated slump points; obtaining a plurality of simulation models according to the simulation slump points and the slump sub models, wherein the simulation models are models formed by the slump sub models after the simulation slump points simulate slump; and determining slump points according to the scattering conditions of a plurality of slump sub-models in the simulation model.
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