Underground disease risk assessment method and device, electronic equipment and medium

Abstract

The invention relates to the technical field of road disease treatment, and discloses an underground disease risk assessment method and device, electronic equipment and a medium. The method comprises the following steps: acquiring a digital twinborn body pre-constructed for a target area; extracting to-be-processed disease body data and to-be-processed disease body environment data of the to-be-evaluated underground disease body from the digital twin body; and performing risk assessment on the to-be-assessed underground disease body according to the to-be-processed disease body data and the to-be-processed disease body environment data to obtain an assessment result. According to the method, the evaluation efficiency can be remarkably improved, and errors possibly generated when a large amount of data is manually collected and processed are greatly reduced, so that the accuracy and reliability of a final evaluation result are powerfully ensured.

Description

Technical Field

[0001] The present disclosure relates to the technical field of road damage control, and in particular to a method, device, electronic equipment and medium for assessing the risk of underground damage bodies. Background Art

[0002] Underground diseased bodies, that is, undesirable geological bodies such as cavities, voids, loose bodies, water-rich bodies, etc. that exist below the ground edge, if not discovered and properly handled in time, may lead to serious consequences such as road collapse, underground pipeline rupture, and building foundation settlement, which will greatly affect the normal operation and sustainable development of the city.

[0003] At present, manual methods are often used to assess the risk of underground disease bodies. However, this assessment method is not only inefficient, but also difficult to ensure the accuracy of the final assessment results due to the large amount of data and calculations involved in the assessment process. Therefore, it is urgent to develop an accurate and efficient underground disease body risk assessment method. Summary of the invention

[0004] In view of the above situation, the embodiments of the present disclosure provide a method, device, electronic device and medium for assessing the risk of underground diseased bodies, aiming to solve the above problems or at least partially solve the above problems.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for assessing the risk of underground diseased bodies, the method comprising: Get pre-built digital twins for target areas; Extracting the disease body data to be processed and the disease body environment data to be processed of the underground disease body to be evaluated from the digital twin; According to the data of the diseased body to be processed and the environmental data of the diseased body to be processed, a risk assessment is performed on the underground diseased body to be assessed to obtain an assessment result.

[0006] In a second aspect, the present disclosure also provides an underground disease body risk assessment device, the device comprising: An acquisition module, used to acquire a pre-built digital twin for a target area; An extraction module, used to extract the diseased body data to be processed and the environmental data of the diseased body to be processed of the underground diseased body to be evaluated from the digital twin; The evaluation module is used to perform risk evaluation on the underground diseased body to be evaluated according to the diseased body data to be processed and the environmental data of the diseased body to be processed to obtain an evaluation result.

[0007] In a third aspect, an embodiment of the present disclosure further provides an electronic device, comprising: a processor; and a memory arranged to store computer executable instructions, wherein when the executable instructions are executed, the processor executes the steps of the above-mentioned underground disease body risk assessment method.

[0008] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes the steps of the above-mentioned underground disease body risk assessment method.

[0009] By means of the above-mentioned technical scheme, the underground pest body risk assessment method, device, electronic device and medium provided by the embodiments of the present disclosure, the method first obtains a pre-constructed digital twin for the target area, and the digital twin comprehensively and accurately integrates the relevant data of each underground pest body in the target area and the surrounding environment data of the pest body. The pest body data to be processed and the environmental data of the pest body to be processed of the underground pest body to be assessed are extracted from the digital twin, and a risk assessment is performed on the underground pest body to be assessed based on these data to obtain an assessment result. It can be seen that compared with the prior art, the technical scheme provided by the embodiments of the present disclosure can significantly improve the assessment efficiency, while greatly reducing the errors that may occur when manually collecting and processing large amounts of data, thereby effectively ensuring the accuracy and reliability of the final assessment results.

[0010] The above description is only an overview of the technical solution of the present disclosure. In order to more clearly understand the technical means of the present disclosure, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present disclosure more obvious and easy to understand, the specific implementation methods of the present disclosure are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings: Figure 1 A schematic diagram of the process of the underground disease body risk assessment method provided by the embodiment of the present disclosure is shown; Figure 2 A schematic diagram of a digital twin platform provided by an embodiment of the present disclosure is shown; Figure 3 A schematic diagram of an underground disease body and a geological environment model provided by an embodiment of the present disclosure is shown; Figure 4 A schematic diagram of the structure of an underground disease body risk assessment device provided by an embodiment of the present disclosure is shown; Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the technical solutions of the present disclosure will be clearly and completely described below in combination with the specific embodiments of the present disclosure and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0013] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0014] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such usage is interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to".

[0015] As mentioned above, the prior art often uses manual methods to assess the risk of underground disease bodies. However, this assessment method is not only inefficient, but also difficult to ensure the accuracy of the final assessment results due to the large amount of data and calculation involved in the assessment process. Based on this, the present invention proposes a method, device, electronic device and medium for assessing the risk of underground disease bodies. The present disclosure is described in detail below through specific embodiments.

[0016] To facilitate understanding of this embodiment, a method for assessing the risk of underground pests disclosed in the embodiment of the present disclosure is first introduced in detail. The execution subject of the method for assessing the risk of underground pests provided in the embodiment of the present disclosure is generally a computer device with certain computing capabilities, and the computer device includes, for example: a terminal device or a server or other processing device, and the terminal device may be a user equipment (UE), a mobile device, a user terminal, a terminal, a personal digital assistant (PDA), a handheld device, a computing device, etc. In some possible implementations, the method for assessing the risk of underground pests may be implemented by a processor calling a computer-readable instruction stored in a memory.

[0017] Figure 1The schematic diagram of the process of the underground disease body risk assessment method provided by the embodiment of the present disclosure is shown. Figure 1 It can be seen that the embodiment of the present disclosure at least includes steps S101-S103: S101: Obtain a pre-built digital twin for a target area.

[0018] Digital twin technology refers to a method of describing and modeling the characteristics, behaviors, operation processes and performance of physical objects in the real world by comprehensively utilizing technologies such as sensors, the Internet of Things, virtual reality, and artificial intelligence. This embodiment is implemented based on the existing digital twin platform.

[0019] S102: Extracting the disease body data to be processed and the disease body environment data to be processed of the underground disease body to be evaluated from the digital twin.

[0020] S103: Perform risk assessment on the underground diseased body to be assessed based on the diseased body data to be processed and the environmental data of the diseased body to be processed to obtain an assessment result.

[0021] The disclosed embodiment first obtains a digital twin pre-built for the target area, which comprehensively and accurately integrates the relevant data of underground pests in the target area and the surrounding environment data of the pests. The pest data to be processed and the environmental data of the pests to be processed of the underground pests to be evaluated are extracted from the digital twin, and a risk assessment is performed on the underground pests to be evaluated based on these data to obtain an evaluation result. It can be seen that compared with the prior art, the technical solution provided by the disclosed embodiment can significantly improve the evaluation efficiency, while greatly reducing the errors that may occur when manually collecting and processing large amounts of data, thereby effectively ensuring the accuracy and reliability of the final evaluation results.

[0022] Further, in order to better illustrate the process of the underground disease body risk assessment method, as a refinement and extension of the above embodiment, the embodiment of the present invention provides several optional embodiments, but is not limited thereto, which are specifically as follows: In some embodiments, the digital twin is generated according to the following method: Obtaining the disease body data and disease body environment data of each underground disease body in the target area; wherein the disease body data includes: the disease body projection area, and at least one of the disease body height and the disease body type; the disease body environment data includes at least one of the following: span ratio data, road status data, relative position data between the disease body and the pipeline, pipeline material data, service life data, underground structure-disease body spatial relationship data, ground facility-underground disease body spatial relationship data, geotechnical body condition data, minimum distance data between underground structure or ground facility or construction boundary and underground disease body boundary, surface load data, water environment condition data, building type data, facility type data, underground pipeline type data; A target building information model is constructed according to the disease body data and the disease body environment data of each of the underground diseased bodies; and the digital twin is constructed according to the target building information model.

[0023] In this embodiment, the road status data is used to indicate the degree of damage to the road above the underground diseased body. The relative position data of the diseased body and the pipeline is the minimum horizontal distance between the boundary of the underground diseased body and the boundary of the pipeline. The spatial relationship data of underground structure-disease body is the ratio of the minimum distance between the boundary of the underground structure and the boundary of the underground diseased body to the maximum span of the underground diseased body. The spatial relationship data of ground facilities-underground diseased body is the ratio of the minimum distance between the boundary of the ground facilities and the boundary of the underground diseased body to the maximum span of the underground diseased body. The water environment condition data includes the existence of water bodies around the underground diseased body, drainage and water accumulation, etc.

[0024] During implementation, the projected area and height of the damaged body can be obtained, for example, by using detection radar equipment. For the type of damaged body, for example, it can be obtained by using detection radar equipment (MALA, etc.), combined with geological survey methods and geological data processing software. For the span ratio data, for example, the thickness information of the underground damaged body and the covering layer above it can be detected by detection radar equipment, and then obtained by division operation. For the road status data, for example, it can be obtained by using road inspection equipment to capture the road conditions, and then using algorithms to identify the degree of damage such as cracks, deformations, potholes, etc. on the road surface; it can also be obtained by observing and recording the degree of damage to the road with the naked eye on site. For the relative position data of the damaged body and the pipeline, for example, the location of the underground damaged body and the pipeline can be detected by using detection radar, and then the spatial position analysis can be obtained by using supporting software, such as geological data processing software (GeoBIM, EVS, GoCAD, etc.) and BIM software (Revit, Bentley). For the material and service life of the pipeline, for example, it can be obtained by querying the design and construction data of the pipeline or obtaining it from the pipeline management department, or it can be obtained by manually checking the pipeline identification signs on site. For the spatial relationship data between underground structures and diseased bodies, for example, the boundary position and maximum span of the underground diseased body can be obtained by using a three-dimensional detection radar, and the boundary position of the ground facilities can be measured and located by using a total station or other measuring instruments; then the data obtained by the radar and the total station can be imported into the BIM software (Building Information Modeling Software) or other spatial analysis software to measure and calculate the distance and span, thereby obtaining the spatial relationship data between underground structures and diseased bodies. For the spatial relationship data between ground facilities and underground diseased bodies, for example, the boundary and maximum span of the underground diseased body can be obtained by using a three-dimensional detection radar, and the boundary position of the underground structure can be obtained by using a total station or other measuring instruments; then the measurement data can be imported into the spatial analysis software for calculation to obtain the spatial relationship data between ground facilities and underground diseased bodies. For the rock and soil condition data, for example, core samples can be obtained through a core drill, and relevant physical property data can be obtained by using geophysical exploration equipment (such as resistivity meters and seismic wave exploration instruments), and then these data can be imported into the geotechnical engineering survey software for analysis and processing. For surface load data, for example, pressure sensors can be installed on the surface to collect pressure data in real time through the data acquisition system; it can also be estimated based on information such as road design standards and traffic flow. For water environment condition data, for example, it can be obtained through human eye observation. For building types and facility types, for example, they can be obtained through on-site observation or querying relevant planning and design data, or they can be identified and judged using satellite remote sensing images. For underground pipeline types, for example, they can be obtained by querying the design and construction data of the pipeline or from the pipeline management department, and pipeline detectors can be used for detection and confirmation.

[0025] After obtaining the disease body data and disease body environment data of each underground disease body, the disease body data and disease body environment data of each underground disease body can be input and corresponding parameters can be set according to the operating specifications of the selected BIM software to construct a building information model that can accurately reflect the underground disease body and its surrounding environment in the target area.

[0026] Finally, the target building information model is imported into the digital twin platform. As a data aggregation center, the platform integrates real-time data collected by IoT devices such as three-dimensional detection radar through a specific data interface protocol, thereby integrating and processing static building information and dynamic real-time data, thereby constructing a complete digital twin that changes synchronously with the real target area.

[0027] Figure 2 A schematic diagram of a digital twin platform provided by an embodiment of the present disclosure is shown. Figure 3 The schematic diagram of the underground disease body and geological environment model provided by the embodiment of the present disclosure is shown. It can be seen that Figure 2 The digital twins of the digital twin platform include three types of underground disease bodies: ground subsidence disease body, foundation pit deformation disease body and landslide disease body. Figure 3 The ground subsidence disease body, foundation pit deformation disease body and landslide disease body in the geological environment model are displayed.

[0028] In some embodiments, the evaluation result includes at least one of the following: data on the probability of occurrence of a diseased body and data on the degree of impact of the occurrence of the diseased body; wherein the data on the probability of occurrence of the diseased body is calculated using the following data: data on the diseased body to be processed including the projected area of ​​the diseased body, the height of the diseased body and the type of the diseased body, and environmental data on the diseased body to be processed including at least one of the following: data on the span ratio, road status data, relative position data between the diseased body and the pipeline, pipeline material data, service life data, spatial relationship data between underground structures and diseased bodies, spatial relationship data between ground facilities and underground diseased bodies, geotechnical body condition data, minimum distance data between underground structures or ground facilities or construction boundaries and underground diseased body boundaries, surface load data, and water environment condition data; the data on the degree of impact of the occurrence of the diseased body is calculated using the following data: data on the diseased body to be processed including the projected area of ​​the diseased body, and environmental data on the diseased body to be processed including at least one of the following: data on building type, the surface load data, facility type data, and underground pipeline type data.

[0029] In this embodiment, the type of the evaluation result may be the pest occurrence possibility data, or the pest occurrence impact degree data, or may include the pest occurrence possibility data and the pest occurrence impact degree data.

[0030] During implementation, for the data on the possibility of occurrence of the defective body, for example, the preset evaluation basis can be used to process the projection area of ​​the defective body, the height and type of the defective body, the span ratio data, the road status data, the relative position data of the defective body and the pipeline, the pipeline material data, the service life data, the geotechnical condition data, and the surface load data to obtain the corresponding index values, and then the index values ​​are integrated to obtain the corresponding index values.

[0031] In some embodiments, the probability data of occurrence of the pest is calculated according to the following method: Calculate the scale index value of the underground diseased body according to the projected area of ​​the diseased body and the height of the diseased body; The neighboring facility index value is calculated based on the span ratio data, the road status data, the relative position data between the damaged object and the pipeline, the pipeline material data, the service life data, the underground structure-damaged object spatial relationship data, and the ground facility-underground damaged object spatial relationship data; Calculate the environmental factor index value according to the rock and soil condition data, the minimum distance data, the surface load data, and the water environment condition data; The occurrence possibility data of the diseased body is calculated based on the diseased body type, the underground diseased body scale index value, the neighboring facility index value, and the environmental factor index value.

[0032] During implementation, first calculate the underground disease body scale index value, adjacent facility index value, and environmental factor index value based on the disease body data to be treated and the environmental data of the disease body to be treated.

[0033] The scale index value of the underground diseased body can be calculated based on the projected area and height of the diseased body. Specifically, first, the corresponding relationship between the preset area and the index value is used to determine the area index value of the diseased body according to the projected area of ​​the diseased body; and the corresponding relationship between the preset height and the index value is used to determine the height index value of the diseased body according to the height of the diseased body. Here, the corresponding relationship between the preset area and the index value, and the corresponding relationship between the preset height and the index value can be set according to actual needs, and this embodiment does not limit this. Then, the scale index value of the underground diseased body is calculated based on the area index value of the diseased body, the area weight, the height index value of the diseased body, and the height weight. Here, the area weight and the height weight can be set according to actual needs, and this embodiment does not limit this. Exemplarily, the area weight is 0.7 and the height weight is 0.3.

[0034] For the index values ​​of adjacent facilities, the road data index values, underground pipeline index values, underground structure index values ​​and ground facility index values ​​can be calculated respectively according to the span ratio data, road status data, relative position data of the defective body and the pipeline, pipeline material data, service life data, underground structure data and ground facility data, and these index values ​​can be integrated to obtain the adjacent facility index values.

[0035] For the road data index value, the preset span ratio and index value correspondence relationship can be used to determine the span ratio index value according to the span ratio data; the preset road status condition and index value correspondence relationship can be used to determine the road status index value according to the road status data. Here, the preset span ratio and index value correspondence relationship, the preset road status condition and index value correspondence relationship can be set according to actual needs, and this embodiment does not limit this. Exemplarily, the preset road status condition and index value correspondence relationship can be: if the road status condition is that the road surface has obvious deformation and subsidence, the road status index value is 95; if the road status condition is that the road surface has obvious cracks and potholes, the road status index value is 85; if the road status condition is that the road surface is cracked and slightly deformed, the road status index value is 75; if the road status condition is that the road surface is intact, the road status index value is 65. Then, the road data index value is calculated using the span ratio index value, the span ratio index weight, the road status index value, and the road status index weight. Here, the span ratio index weight and the road status index weight can be set according to actual needs, and this embodiment does not limit this. Exemplarily, the weight of the span ratio index is 0.8, and the weight of the road condition index is 0.2.

[0036] For the index value of underground pipelines, the relative position index value of the diseased body and the pipeline can be determined based on the relative position data of the diseased body and the pipeline by using the preset corresponding relationship between the relative position of the diseased body and the pipeline and the index value; the pipeline vulnerability index value can be determined based on the pipeline material data by using the preset corresponding relationship between the pipeline material and the index value; the service life index value can be determined based on the service life data by using the preset corresponding relationship between the service life and the index value. Here, the preset corresponding relationship between the relative position of the diseased body and the pipeline and the index value, the preset corresponding relationship between the pipeline material and the index value, and the preset corresponding relationship between the service life and the index value can be set according to actual needs, and this embodiment does not limit this. Then, the relative position index value of the diseased body and the pipeline, the pipeline vulnerability index value, the service life index value, the relative position index weight of the diseased body and the pipeline, the pipeline vulnerability index weight, and the service life index weight are used to calculate the underground pipeline index value. Here, the relative position index weight of the diseased body and the pipeline, the pipeline vulnerability index weight, and the service life index weight can be set according to actual needs, and this embodiment does not limit this. For example, the weight of the relative position index between the diseased body and the pipeline is 0.5, the weight of the pipeline vulnerability index is 0.4, and the weight of the service life index is 0.1.

[0037] For the index value of underground structures and the index value of ground facilities, the underground structure index value can be determined based on the underground structure-damage body spatial relationship and the index value correspondence relationship, and the ground facility index value can be determined based on the ground facility-underground damage body spatial relationship data by using the ground facility-underground damage body spatial relationship and the index value correspondence relationship. Here, the underground structure-damage body spatial relationship and the index value correspondence relationship, and the ground facility-underground damage body spatial relationship and the index value correspondence relationship can be set according to actual needs, and this embodiment does not limit this.

[0038] Finally, the neighboring facility index value is calculated using the road data index value, the underground pipeline index value, the underground structure index value, and the ground facility index value. For example, the neighboring facility index value can be calculated using the following formula:

[0039] in, represents the neighboring facility index, Indicates road data index value, underground pipeline index value, underground structure index value or ground facility index value.

[0040] The index value of environmental factors can be calculated based on the rock and soil condition data, the minimum distance data between the underground structure or ground facility or construction boundary and the underground disease body boundary, the surface load data, and the water environment condition data. Specifically, the rock and soil condition index value is first determined based on the rock and soil condition data using the preset correspondence between rock and soil conditions and index values; the construction interference index value is determined based on the minimum distance data between the underground structure, ground facility or construction boundary and the underground disease body boundary using the preset correspondence between distance and index values; the surface load index value is determined based on the surface load data using the preset correspondence between surface load conditions and index values; the water environment condition index value is determined based on the water environment condition data using the preset correspondence between water environment conditions and index values.

[0041] Here, the preset rock and soil conditions and the corresponding relationship between the index value, the preset distance and the corresponding relationship between the index value, the preset surface load conditions and the corresponding relationship between the index value, and the preset water environment conditions and the corresponding relationship between the index value can be set according to actual needs, and the embodiments of the present disclosure are not limited to this. Exemplarily, the preset rock and soil conditions and the corresponding relationship between the index value are: if the rock and soil conditions are loose fill, silt and sand, the rock and soil condition index value is 90; if the rock and soil conditions are medium dense fill, silt and sand, loose gravel, clay, the rock and soil condition index value is 70; if the rock and soil conditions are dense fill, silt and sand, the rock and soil condition index value is 45; if the rock and soil conditions are medium dense to dense gravel, the rock and soil condition index value is 15. The preset correspondence between the surface load condition and the index value is: if the surface load condition is an area with frequent motor vehicle and heavy-loaded vehicle traffic, the surface load index value is 85; if the surface load condition is a bicycle lane or an area with fewer motor vehicles, the surface load index value is 60; if the surface load condition is a sidewalk or square, the surface load index value is 25. The preset correspondence between the water environment condition and the index value is: if the water environment condition is that the diseased body is within 30m around a water body such as a river or lake, or is prone to serious waterlogging, the water environment condition index value is 90; if the water environment condition is that the drainage condition is general and waterlogging is prone to occur, the water environment condition index value is 65; if the water environment condition is that the drainage condition is good and waterlogging is not likely to occur, the water environment condition index value is 25.

[0042] Then, the environmental factor index value can be calculated based on the rock and soil condition index value, the rock and soil condition index weight, the construction interference index value, the construction interference index weight, the surface load index value, the surface load index weight, the water environment condition index value, and the water environment condition index weight. Here, the sum of the rock and soil condition index weight, the construction interference index weight, the surface load index weight, and the water environment condition index weight is 1, which can be set according to actual needs, and the embodiments of the present disclosure are not limited to this.

[0043] After obtaining the underground disease body scale index value, the adjacent facility index value, and the environmental factor index value, the disease body occurrence possibility data can be calculated based on these three data and the disease body type. Specifically, the disease body type coefficient can be determined based on the disease body type and the preset type-coefficient correspondence. Here, the preset type-coefficient correspondence can be set according to actual needs. Exemplarily, if the disease body type is hollow, the disease body type coefficient is 1; if the disease body type is a cavity, the disease body type coefficient is 1; if the disease body type is a severely loose body, the disease body type coefficient is 0.9; if the disease body type is a water-rich body, the disease body type coefficient is 0.7; if the disease body type is a generally loose body, the disease body type coefficient is 0.5. Then, the disease body occurrence possibility data is calculated using the following formula:

[0044] Among them, P A Indicates the underground disease body scale index value, P B represents the neighboring facility index value, P C represents the environmental factor index value, K represents the underground disease body type coefficient, W A represents the weight of underground disease body scale index, W B represents the weight of neighboring facility index, W C Represents the weight of environmental factor indicators, where W A , W B , W C It can be set according to actual needs.

[0045] For the data on the degree of impact of the diseased body, for example, the preset evaluation basis can be used to process the projected area of ​​the diseased body, building type data, surface load data, and facility type data to obtain corresponding index values, and then the index values ​​can be integrated to obtain the data on the degree of impact of the diseased body.

[0046] In some embodiments, the diseased body occurrence impact degree data is calculated according to the following method: Using the preset first corresponding relationship, according to the projection area of ​​the diseased body, determining the index value of the range of the underground diseased body; Determine a building distribution index value according to at least one of the building type data, the facility type data, and the underground pipeline type data by using a preset second corresponding relationship; Determine a population density index value according to the building type data and the surface load data by using a preset third corresponding relationship; Determine the property density index value and the social impact index value according to the building type data by using the preset fourth corresponding relationship and the preset fifth corresponding relationship respectively; The data on the degree of impact of the occurrence of the diseased body are calculated based on the underground diseased body range index value, the building distribution index value, the population density index value, the property density index value, and the social impact index value.

[0047] In this embodiment, the underground disease body range index value, building distribution index value, population density index value, property density index value, and social impact index value are first calculated based on the disease body data to be processed and the disease body environment data to be processed.

[0048] The underground disease body range index value can be determined according to the preset first corresponding relationship and the disease body projection area. Here, the preset first corresponding relationship can be set according to actual needs, and this embodiment does not limit this. Exemplarily, the preset first corresponding relationship is: if the disease body projection area is greater than or equal to 15, the underground disease body range index value is 95; if the disease body projection area is greater than or equal to 10 and less than 15, the underground disease body range index value is 85; if the disease body projection area is greater than or equal to 3 and less than 10, the underground disease body range index value is 75; if the disease body projection area is less than 3, the underground disease body range index value is 65.

[0049] The building distribution index value can be determined according to a preset second corresponding relationship and at least one of building type data, facility type data, and underground pipeline type data. Here, the preset second corresponding relationship can be set according to actual needs, and this embodiment does not limit this.

[0050] Exemplarily, the preset second corresponding relationship is: if there are gas or more dangerous industrial pipelines, or important facilities or buildings such as high-rise buildings, subways, underground buildings, etc. within 5 meters, the building distribution index value is 95; if there are important facilities such as heat or less dangerous industrial pipelines, or multi-story buildings within 5 meters, the building distribution index value is 80; if there are water supply, drainage or high-voltage power pipelines within 5 meters, the building distribution index value is 60; if there are telecommunication pipelines or other facilities within 5 meters, the building distribution index value is 40.

[0051] The population density index value can be determined according to the preset third corresponding relationship, the building type, and the surface load data. Here, the preset third corresponding relationship can be set according to actual needs, and this embodiment does not limit this.

[0052] Exemplarily, the preset third corresponding relationship is: if there are important public buildings or places where people gather, such as large shopping malls, stadiums, performance venues, large squares, schools, etc. within 100 meters around the underground disease body to be evaluated, or there are bus stations, subway stations, etc. within 50 meters around the underground disease body to be evaluated, then the population density index value is 90; if there are small and medium-sized shopping malls, office spaces, residential buildings and other places with a large number of people within 100 meters around the underground disease body to be evaluated, or the traffic volume and pedestrian flow on the road where the underground disease body is located are greater than the preset threshold, then the population density index value is 70.

[0053] The property density index value can be determined according to the preset fourth corresponding relationship and the building type data. Here, the preset fourth corresponding relationship can be set according to actual needs, and this embodiment does not limit this.

[0054] Exemplarily, the fourth corresponding relationship is preset as follows: if there are financial institutions, large shopping malls, corporate headquarters, hazardous chemical facilities and other places with dense properties or extremely high risks within 100m around the underground disease body to be assessed, the property density index value is 95; if there are small and medium-sized shopping malls, residential buildings, office spaces, high-risk facilities and other places with high property density within 100m around the underground disease body to be assessed, the property density index value is 70; if there are residential houses, low-risk facilities, etc. within 100m around the underground disease body to be assessed, the property density index value is 50; if there are grasslands, farmlands, barren mountains, etc. within 100m around the underground disease body to be assessed, the property density index value is 30.

[0055] The social impact index value can be determined according to the preset fifth corresponding relationship and the building type data. Here, the preset fifth corresponding relationship can be set according to actual needs, and this embodiment does not limit this.

[0056] Exemplarily, the fifth corresponding relationship is preset as follows: if there are important places within 200m around the underground disease body to be evaluated, including but not limited to national, provincial and municipal landmark buildings, famous scenic spots, shopping malls and other landmark places, the social impact index value is 90; if there are important places within 200m~500m around the underground disease body to be evaluated, including but not limited to national, provincial and municipal landmark buildings, famous scenic spots, shopping malls and other landmark places, the social impact index value is 55.

[0057] Finally, the impact degree data of the occurrence of the disease body is calculated based on the underground disease body range index value, building distribution index value, population density index value, property density index value, and social impact index value. Specifically, the impact degree data of the occurrence of the disease body can be calculated according to the following formula:

[0058] Among them, C1 represents the underground disease body range index value, C2 represents the building distribution index value, C3 represents the population density index value, C4 represents the property density index value, C5 represents the social impact index value, W1 represents the underground disease body range index weight, W2 represents the building distribution index weight, W3 represents the population density index weight, W4 represents the property density index weight, W5 represents the social impact index weight, W1+W2+W3+W4+W5=1, which can be set according to actual needs.

[0059] In some embodiments, if the evaluation result includes the probability data of the occurrence of the pest and the impact degree data of the occurrence of the pest; the method further includes: Determining the first level according to the preset risk occurrence possibility level correspondence relationship and the disease occurrence possibility data; Determining the second level according to the preset risk impact level correspondence relationship and the disease body occurrence impact level data; The risk level of the underground disease body is determined according to the preset underground disease body risk level classification rules, the first level, and the second level.

[0060] When the evaluation results include multiple types, this embodiment can integrate the evaluation results of each type to obtain the underground disease body risk level that reflects the overall risk status of the underground disease body to be evaluated. During implementation, the preset risk occurrence possibility level correspondence relationship, the preset risk impact level correspondence relationship, and the preset underground disease body risk level classification rules are not limited in this disclosed embodiment and can be set according to actual needs.

[0061] This embodiment determines the first level according to the data of the probability of occurrence of the disease body according to the preset corresponding relationship or rule; determines the second level according to the data of the degree of impact of the disease body occurrence; and finally, the underground disease body risk level is obtained according to the first level and the second level. It can be seen that this embodiment realizes the standardization of the overall risk assessment of underground disease bodies, avoids the subjectivity and errors of manual assessment, and improves the accuracy and efficiency of the assessment.

[0062] For example, the correspondence between the preset risk occurrence possibility levels is shown in Table 1. The correspondence between the preset risk impact degree levels is shown in Table 2. The preset underground disease body risk level classification rules are shown in Table 3.

[0063] Table 1 Correspondence between preset risk occurrence probability levels

[0064] Table 2 Correspondence between preset risk impact levels

[0065] Table 3 Preset risk classification rules for underground disease bodies

[0066] In some embodiments, if there are multiple underground pest bodies to be evaluated, the method further includes: sorting each of the underground pest bodies to be evaluated according to the risk level of each of the underground pest bodies to obtain a pest body processing order; and determining a control strategy for each of the underground pest bodies to be evaluated according to a preset risk strategy correspondence relationship and the risk level of each of the underground pest bodies.

[0067] In this embodiment, there are multiple underground disease bodies to be evaluated, and the processing priority of each underground disease body to be evaluated can be sorted according to the risk level of the underground disease body to obtain a sorting result. For example, if the risk level of the underground disease body is higher, the risk brought by the underground disease body is greater, and the underground disease bodies to be evaluated can be sorted in descending order of risk level to obtain a sorting result.

[0068] The preset risk strategy correspondence is also used to determine the corresponding control strategy according to the risk level of each underground pest body. Here, the preset risk strategy correspondence can be set according to actual needs, and this disclosure does not limit this. Exemplarily, the preset risk strategy correspondence is shown in Table 4 below.

[0069] Table 4 Correspondence between preset risk strategies

[0070] This embodiment ranks multiple underground disease bodies to be evaluated according to risk levels to determine the treatment order, and provides a control strategy for each disease body based on a preset scientific risk strategy correspondence, so as to clarify the priority of disease body treatment, reasonably allocate resources, and take precise measures for different risks to effectively prevent and control risks and ensure the safety and stability of the project or region.

[0071] Those skilled in the art will appreciate that, in the above method of the specific implementation manner, the writing order of the steps does not mean a strict execution order, but does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0072] It should be noted that, in practical applications, all the above possible implementation methods can be combined in any way to form possible embodiments of the present disclosure, which will not be described one by one here. The information (including but not limited to device information, user information, etc.) and data (including but not limited to data used for analysis, storage and display, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. The software tools or components appearing in the embodiments of the present disclosure are only examples and do not represent actual use.

[0073] Based on the same concept, the embodiment of the present disclosure also provides an underground disease body risk assessment device, Figure 4 FIG. 1 shows a schematic diagram of the structure of an underground disease body risk assessment device provided by an embodiment of the present disclosure, see FIG. Figure 4 As shown, the underground disease body risk assessment device 400 provided by the embodiment of the present disclosure includes: An acquisition module 401 is used to acquire a pre-built digital twin for a target area; An extraction module 402 is used to extract the diseased body data to be processed and the environmental data of the diseased body to be processed of the underground diseased body to be evaluated from the digital twin; The evaluation module 403 is used to perform risk evaluation on the underground diseased body to be evaluated according to the diseased body data to be processed and the environmental data of the diseased body to be processed to obtain an evaluation result.

[0074] In a possible implementation manner, the device further includes a construction module, which is used to: obtain disease body data and disease body environment data of each underground disease body in the target area; wherein the disease body data includes: a projected area of ​​the disease body, and at least one of a height of the disease body and a type of the disease body; the disease body environment data includes at least one of the following: span ratio data, road status data, relative position data between the disease body and the pipeline, pipeline material data, service life data, underground structure-disease body spatial relationship data, ground facility-underground disease body spatial relationship data, geotechnical body condition data, minimum distance data between underground structures or ground facilities or construction boundaries and underground disease body boundaries, surface load data, water environment condition data, building type data, facility type data, underground pipeline type data; construct a target building information model according to the disease body data and disease body environment data of each of the underground disease bodies; and construct the digital twin according to the target building information model.

[0075] In a possible implementation manner, in the above-mentioned device, the evaluation result includes at least one of the following: data on the possibility of occurrence of the diseased body and data on the degree of impact of the diseased body; the evaluation module 403 is used to calculate the possibility of occurrence of the diseased body using the following data: data on the diseased body to be processed including the projected area of ​​the diseased body, the height of the diseased body and the type of the diseased body, and data on the relative position of the diseased body and the pipeline, data on the material of the pipeline, data on the service life, spatial relationship data between underground structures and diseased bodies, and data on the relationship between ground facilities and underground diseases. The evaluation module 403 is further used for: obtaining the damage body occurrence impact degree data by using the following data: the damage body data to be processed including the projected area of ​​the damage body, and the damage body environmental data to be processed including at least one of the building type data, the surface load data, the facility type data, and the underground pipeline type data.

[0076] In a possible implementation manner, in the above-mentioned device, the evaluation module 403 is used to: calculate the underground disease body scale index value according to the projected area of ​​the disease body and the height of the disease body; calculate the adjacent facility index value according to the cover-span ratio data, the road status data, the relative position data between the disease body and the pipeline, the pipeline material data, the service life data, the underground structure-disease body spatial relationship data, and the ground facility-underground disease body spatial relationship data; calculate the environmental factor index value according to the rock and soil condition data, the minimum distance data, the surface load data, and the water environment condition data; calculate the occurrence possibility data of the disease body according to the disease body type, the underground disease body scale index value, the adjacent facility index value, and the environmental factor index value.

[0077] In a possible implementation manner, in the above-mentioned device, the evaluation module 403 is further used to: determine the underground diseased body range index value according to the projection area of ​​the diseased body by using a preset first corresponding relationship; determine the building distribution index value according to at least one of the building type data, the facility type data, and the underground pipeline type data by using a preset second corresponding relationship; determine the population density index value according to the building type data and the surface load data by using a preset third corresponding relationship; determine the property density index value and the social impact index value according to the building type data by using a preset fourth corresponding relationship and a preset fifth corresponding relationship respectively; and calculate the diseased body occurrence impact degree data according to the underground diseased body range index value, the building distribution index value, the population density index value, the property density index value, and the social impact index value.

[0078] In a possible implementation, if the evaluation result includes the probability data of the occurrence of the pest body and the impact data of the occurrence of the pest body; the device also includes an overall evaluation module, which is used to determine the first level according to the preset correspondence between the risk probability levels and the probability data of the occurrence of the pest body; determine the second level according to the preset correspondence between the risk impact level levels and the impact data of the occurrence of the pest body; and determine the risk level of the underground pest body according to the preset underground pest body risk level classification rules, the first level, and the second level.

[0079] In a possible implementation manner, if there are multiple underground pest bodies to be evaluated, the device also includes a decision-making module, which is used to sort each of the underground pest bodies to be evaluated according to the risk level of each of the underground pest bodies to obtain a pest body processing order; and determine the control strategy for each of the underground pest bodies to be evaluated according to the preset risk strategy correspondence relationship and the risk level of each of the underground pest bodies.

[0080] It should be noted that any of the above-mentioned underground pest body risk assessment devices can implement the above-mentioned underground pest body risk assessment method one by one, which will not be described in detail here.

[0081] Figure 5 FIG. 1 shows a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Figure 5 As shown, at the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage, etc. Of course, the electronic device may also include hardware required for other services.

[0082] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0083] The memory is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0084] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming an underground disease body risk assessment device at the logical level. The processor executes the program stored in the memory and is specifically used to execute the above method.

[0085] The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present disclosure may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present disclosure may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0086] The electronic device can execute the underground pest body risk assessment method provided by multiple embodiments of the present disclosure, and realize the underground pest body risk assessment device in Figure 4 The functions of the illustrated embodiments will not be described in detail in the embodiments of the present disclosure.

[0087] The embodiments of the present disclosure also provide a computer-readable storage medium, which stores one or more programs, and the one or more programs include instructions. When the instructions are executed by an electronic device including multiple application programs, the electronic device can execute the underground disease body risk assessment method provided by multiple embodiments of the present disclosure.

[0088] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0092] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0093] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0094] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0095] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity or device including the element.

[0096] It should be understood by those skilled in the art that the embodiments of the present disclosure may be provided as methods, systems or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The above are only embodiments of the present disclosure and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the scope of the claims of the present disclosure.

Claims

1. A method for assessing the risk of underground disease bodies, characterized in that: The method comprises: Get pre-built digital twins for target areas; Extracting the disease body data to be processed and the disease body environment data to be processed of the underground disease body to be evaluated from the digital twin; According to the data of the diseased body to be processed and the environmental data of the diseased body to be processed, a risk assessment is performed on the underground diseased body to be assessed to obtain an assessment result.

2. The method according to claim 1, characterized in that The digital twin is generated according to the following method: Obtaining the disease body data and disease body environment data of each underground disease body in the target area; wherein the disease body data includes: the disease body projection area, and at least one of the disease body height and the disease body type; the disease body environment data includes at least one of the following: span ratio data, road status data, relative position data between the disease body and the pipeline, pipeline material data, service life data, underground structure-disease body spatial relationship data, ground facility-underground disease body spatial relationship data, geotechnical body condition data, minimum distance data between underground structure or ground facility or construction boundary and underground disease body boundary, surface load data, water environment condition data, building type data, facility type data, underground pipeline type data; Constructing a target building information model according to the disease body data and the disease body environment data of each of the underground disease bodies; The digital twin is constructed according to the target building information model.

3. The method according to claim 1, characterized in that The evaluation results include at least one of the following: data on the probability of occurrence of pests and data on the degree of impact of the occurrence of pests; The occurrence possibility data of the diseased body is calculated using the following data: data of the diseased body to be processed, including the projected area of ​​the diseased body, the height of the diseased body and the type of the diseased body, and environmental data of the diseased body to be processed, including at least one of the following: span ratio data, road status data, relative position data between the diseased body and the pipeline, pipeline material data, service life data, spatial relationship data between underground structures and diseased bodies, spatial relationship data between ground facilities and underground diseased bodies, geotechnical body condition data, minimum distance data between underground structures or ground facilities or construction boundaries and underground diseased body boundaries, surface load data, and water environment condition data; The data on the degree of impact of the diseased body is calculated using the following data: data on the diseased body to be processed including the projection area of ​​the diseased body, and environmental data on the diseased body to be processed including at least one of building type data, surface load data, facility type data, and underground pipeline type data.

4. The method according to claim 3, characterized in that The probability data of the occurrence of the disease body is calculated according to the following method: Calculate the scale index value of the underground diseased body according to the projected area of ​​the diseased body and the height of the diseased body; The neighboring facility index value is calculated based on the span ratio data, the road status data, the relative position data between the damaged object and the pipeline, the pipeline material data, the service life data, the underground structure-damaged object spatial relationship data, and the ground facility-underground damaged object spatial relationship data; Calculate the environmental factor index value according to the rock and soil condition data, the minimum distance data, the surface load data, and the water environment condition data; The occurrence possibility data of the diseased body is calculated based on the diseased body type, the underground diseased body scale index value, the neighboring facility index value, and the environmental factor index value.

5. The method according to claim 3, characterized in that: The data on the degree of impact of the diseased organism is calculated according to the following method: Using the preset first corresponding relationship, according to the projection area of ​​the diseased body, determining the index value of the range of the underground diseased body; Determine a building distribution index value according to at least one of the building type data, the facility type data, and the underground pipeline type data by using a preset second corresponding relationship; Determine a population density index value according to the building type data and the surface load data by using a preset third corresponding relationship; Determine the property density index value and the social impact index value according to the building type data by using the preset fourth corresponding relationship and the preset fifth corresponding relationship respectively; The data on the degree of impact of the occurrence of the diseased body are calculated based on the underground diseased body range index value, the building distribution index value, the population density index value, the property density index value, and the social impact index value.

6. The method according to any one of claims 3 to 5, characterized in that: If the evaluation result includes the probability data of the occurrence of the pest and the impact degree data of the occurrence of the pest; the method further includes: Determining the first level according to the preset risk occurrence possibility level correspondence relationship and the disease occurrence possibility data; Determining the second level according to the preset risk impact level correspondence relationship and the disease body occurrence impact level data; The risk level of the underground disease body is determined according to the preset underground disease body risk level classification rules, the first level, and the second level.

7. The method according to claim 6, characterized in that If there are multiple underground disease bodies to be evaluated, the method further includes: According to the risk level of each underground pest body, the underground pest bodies to be evaluated are sorted to obtain a treatment order for the pest bodies; According to the preset risk strategy correspondence relationship and the risk level of each underground disease body, the control strategy of each underground disease body to be evaluated is determined.

8. An underground disease risk assessment device, characterized in that: The device comprises: An acquisition module, used to acquire a pre-built digital twin for a target area; An extraction module, used to extract the disease body data to be processed and the environmental data of the disease body to be processed of the underground disease body to be evaluated from the digital twin; The evaluation module is used to perform risk evaluation on the underground diseased body to be evaluated according to the diseased body data to be processed and the environmental data of the diseased body to be processed to obtain an evaluation result.

9. An electronic device, comprising: processor; as well as A memory arranged to store computer executable instructions, wherein the executable instructions, when executed, cause the processor to perform the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing one or more programs, characterized in that: When the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device executes the steps of the method as claimed in any one of claims 1 to 7.

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