A natural disaster risk early warning system for high-speed sections

Abstract

The present invention discloses a natural disaster risk early warning system for a highway section. The system comprises: an information collection module, which is used for collecting the coordinated information of the highway section in real time through Beidou satellites, unmanned aerial vehicles and ground sensing terminals; an environmental analysis module, which is used for analyzing the coordinated information to obtain environmental dynamic data and geological dynamic data of the highway section; a risk identification module, which is used for inputting the environmental dynamic data and geological dynamic data into a preset recognition model for training and outputting a risk coefficient, and judging the risk level according to the size of the risk coefficient; a risk early warning module, which is used for outputting corresponding early warning strategies to a traffic control center and a geological bureau according to the risk level; a risk control module, which is used for carrying out traffic control and geological risk prevention and control measures for the highway section according to the early warning strategy; the present invention improves the recognition efficiency of natural disaster risk early warning by improving the natural disaster early warning system of the highway section.

Description

Technical Field

[0001] The present invention relates to the field of risk warning systems, and in particular to a natural disaster risk warning system for a highway section. Background Art

[0002] Expressways are an important part of my country's comprehensive transportation system. After years of strong promotion by the country, expressway construction has made great achievements. Expressways are the main arteries connecting provinces and cities, and have a strong driving effect on economic development along the lines.

[0003] However, as the operation time goes by, the natural environment of the operating section is in a state of constant change, which makes the risk of natural disasters after the completion of the expressway increasingly greater, and it is more difficult to achieve the effective operation goal of fast, safe and smooth expressway. Correspondingly, the possibility of causing economic losses increases, resulting in increasingly prominent problems of insufficient operational risk management efforts and capabilities.

[0004] In order to improve the economic benefits of highway operations, the existing intelligent monitoring equipment and monitoring technology are used to realize real-time monitoring and analysis of various factors that may cause natural disasters. Usually, a natural disaster early warning system is established on highway sections. However, the existing natural disaster early warning system is still imperfect. It is necessary to combine the data of the climate department, earthquake detection department, environmental department, traffic management department and geological bureau for statistics and then comprehensive analysis. It takes a lot of time to transmit risk information related signals and analyze some influencing data. It requires communication and coordination among various departments, but the actual operation is relatively cumbersome. Therefore, generally only qualitative analysis and on-site monitoring are used to carry out post-disaster measures after natural disasters are detected. Relatively speaking, the early warning control system is imperfect, and the role of early identification of natural disaster risks and control of early warning is not obvious. Summary of the invention

[0005] The purpose of the present invention is to provide a natural disaster risk warning system for high-speed sections to solve the following technical problems:

[0006] How to improve the natural disaster early warning system on expressway sections and improve the efficiency of identifying natural disaster risk early warnings.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A natural disaster risk early warning system for a highway section, the system comprising:

[0009] The information collection module is used to collect collaborative information of expressway sections in real time through Beidou satellites, drones and ground sensing terminals;

[0010] The information collection module includes a collaboration unit;

[0011] Beidou satellites are used to obtain vector information of expressway sections; vector information includes positioning information, navigation image information and time information;

[0012] Drones are used to obtain high-definition images of highway sections in real time, and to obtain geological signal data of the surrounding environment through high-definition image monitoring;

[0013] The ground sensing terminal is used to monitor and obtain earthquake intensity signal data and soil temperature and humidity data based on sensors deployed along the highway section;

[0014] Environmental analysis module, used to analyze collaborative information to obtain environmental dynamic data and geological dynamic data of high-speed road sections;

[0015] The risk identification module is used to input environmental dynamic data and geological dynamic data into a preset identification model to train and output a risk coefficient, and to determine the risk level according to the size of the risk coefficient;

[0016] The risk warning module is used to output corresponding warning strategies to the traffic control center and the geological bureau according to the risk level;

[0017] The risk control module is used to carry out traffic control and geological risk prevention and control measures on expressway sections according to early warning strategies.

[0018] Preferably, the information acquisition module acquires collaborative information by collaboratively analyzing vector information, geological signal data, seismic intensity signal data, and soil temperature and humidity data through a collaborative unit:

[0019] Determine the time information in the vector data, and select the geological signal data vector set, earthquake intensity signal data vector set, and soil temperature and humidity data vector set that meet the target time period for the expressway section;

[0020] The geological signal data vector set, the earthquake intensity signal data vector set and the soil temperature and humidity data vector set are input into ArcGIS as basic data to obtain the vector intervals of all current data vector sets;

[0021] The collaborative information and its analysis report are derived according to the spatial distribution characteristics of the data view of the vector interval of each data vector set.

[0022] Preferably, the environmental analysis module acquires environmental dynamic data and geological dynamic data based on the spatial analysis model in the following manners:

[0023] Input the collaborative information into the spatial analysis model to obtain the spatial distribution characteristic area of ​​each data vector set;

[0024] According to the characteristic area changes of geological signals and earthquake intensity signals in the continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. ;

[0025] And according to the characteristic area changes of geological signals and the characteristic area changes of soil temperature and humidity in the same continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. .

[0026] Preferably, the risk identification module includes:

[0027] By formula Calculate the risk factor of the highway section ,in is the total number of monitoring times in a continuous time period, ∈ ; is the first preset weight coefficient, is a second preset weight coefficient; For the The geological dynamic data parameters monitored by the secondary monitoring; For the The environmental dynamic data parameters monitored at this time; For the Standard values ​​of geological dynamic data parameters for the second monitoring; For the Standard values ​​of environmental dynamic data parameters monitored this time.

[0028] Preferably, the risk factor The preset risk factor threshold range To compare:

[0029] like < , then the natural disaster risk rate of the current expressway section is judged to be low, and it is determined to be the third-level risk level;

[0030] like ≤ ≤ , then the natural disaster risk rate of the current expressway section is judged to be medium, and it is determined to be the second-level risk level;

[0031] like > , it is judged that the natural disaster risk rate of the current expressway section is high and is determined to be a level one risk level.

[0032] Preferably, the early warning strategy includes:

[0033] The warning mark is made according to the output risk level: the third-level risk level is recorded as "0", the second-level risk level is recorded as "1", and the first-level risk level is recorded as "2";

[0034] Set the monitoring frequency and monitoring warning response interval duration corresponding to each level of marked data;

[0035] The risk level is positively correlated with the monitoring frequency and the duration of the monitoring warning response interval.

[0036] Preferably, the risk control module includes:

[0037] Adjust the traffic control monitoring frequency and the monitoring warning response interval duration according to the warning strategy;

[0038] And start and suspend risk prevention operations according to early warning strategies, and choose to activate emergency plans to reduce or avoid the occurrence of risk events.

[0039] Preferably, it also includes an early warning display terminal for displaying graphic information of early warning signals and early warning strategy feedback.

[0040] Beneficial effects of the present invention:

[0041] (1) The present invention determines the time information in the vector data, and uses the vector information obtained from the Beidou satellite as the basic data based on the selected geological signal data vector set, earthquake intensity signal data vector set and soil temperature and humidity data vector set; by importing the basic data into the geographic information system software ArcGIS, the spatial distribution range and characteristics of various types of data are obtained, and the collaborative information and its analysis report are derived according to the spatial distribution characteristics of the data view of the vector interval of each data vector set. The collaborative information is derived by comprehensively considering the time information and the spatial distribution characteristics, and a detailed analysis report is generated based on the collaborative information to provide data support for risk identification.

[0042] (2) The present invention uses an environmental analysis module to analyze collaborative information to obtain environmental dynamic data and geological dynamic data of the expressway section; based on the collaborative information collected by the information acquisition module, in-depth analysis is performed to obtain environmental dynamic data and geological dynamic data of the expressway section, providing basic data for subsequent risk identification; current environmental dynamic data and geological dynamic data are obtained to achieve early identification of the specific conditions of the expressway section, ensuring that the environmental analysis module can comprehensively analyze geological and environmental dynamic data from both spatial and temporal dimensions, providing more comprehensive and accurate data support for subsequent risk identification; and it can effectively capture precursor signals of natural disasters and improve the response speed and accuracy of the early warning system.

[0043] (3) The present invention sets up a risk identification module, which is used to input environmental dynamic data and geological dynamic data into a preset identification model for training to output a risk coefficient, and judge the risk level according to the size of the risk coefficient; input environmental dynamic data and geological dynamic data into a preset identification model, train through a machine learning algorithm, output a risk coefficient, and judge the risk level according to the size of the risk coefficient, thereby realizing a quantitative assessment of potential natural disaster risks.

[0044] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0046] Figure 1 This is a module diagram of a natural disaster risk early warning system for a highway section of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] In order to improve the economic benefits of highway operations, the existing intelligent monitoring equipment and monitoring technology are used to realize real-time monitoring and analysis of various factors that may cause natural disasters. Usually, a natural disaster early warning system is established on highway sections. However, the existing natural disaster early warning system is still imperfect. It is necessary to combine the data of the climate department, earthquake detection department, environmental department, traffic management department and geological bureau for statistics and then comprehensive analysis. It takes a lot of time to transmit risk information related signals and analyze some influencing data. It requires communication and coordination among various departments, but the actual operation is relatively cumbersome. Therefore, generally only qualitative analysis and on-site monitoring are used to carry out post-disaster measures after natural disasters are detected. Relatively speaking, the early warning control system is imperfect, and the role of early identification of natural disaster risks and control of early warning is not obvious.

[0049] To solve the above technical problems, please refer to Figure 1 As shown, the present invention is a natural disaster risk early warning system for a highway section, the system comprising:

[0050] The information collection module is used to collect collaborative information of expressway sections in real time through Beidou satellites, drones and ground sensing terminals;

[0051] The information collection module includes a collaboration unit;

[0052] Beidou satellites are used to obtain vector information of expressway sections; vector information includes positioning information, navigation image information and time information;

[0053] Drones are used to obtain high-definition images of highway sections in real time, and to obtain geological signal data of the surrounding environment through high-definition image monitoring;

[0054] The ground sensing terminal is used to monitor and obtain earthquake intensity signal data and soil temperature and humidity data based on sensors deployed along the highway section;

[0055] Environmental analysis module, used to analyze collaborative information to obtain environmental dynamic data and geological dynamic data of high-speed road sections;

[0056] The risk identification module is used to input environmental dynamic data and geological dynamic data into a preset identification model to train and output a risk coefficient, and to determine the risk level according to the size of the risk coefficient;

[0057] The risk warning module is used to output corresponding warning strategies to the traffic control center and the geological bureau according to the risk level;

[0058] The risk control module is used to carry out traffic control and geological risk prevention and control measures on expressway sections according to early warning strategies.

[0059] In the above technical scheme, in order to solve the adverse effects of various unclear natural disaster factors on the road conditions of expressway sections directly or indirectly, this design mainly considers the earthquake signals and the surrounding climate environment, mainly the impact of temperature and humidity in the surrounding climate environment on the smooth passage of road conditions, and then through real-time monitoring and analysis, it is found that there are potential hidden dangers that may affect safe transportation, and early warning prompts are given to avoid possible natural disasters; and emergency risk avoidance measures such as vehicle evacuation and traffic planning adjustment are guided, so as to ensure traffic safety and personnel safety on expressway sections.

[0060] Specifically, the natural disaster risk warning system for highway sections designed in this invention mainly includes five modules: information collection module, environmental analysis module, risk identification module, risk warning module and risk control module, which can realize early warning and timely and effective control of natural disasters on highway sections, and provide strong support for traffic safety and geological disaster management.

[0061] First, an information collection module is set up to collect coordinated information of expressway sections in real time through Beidou satellites, drones and ground sensing terminals; the effect of "sky-ground-man" coordinated operation is achieved through Beidou satellites, drones and ground sensing terminals. The specific collection equipment includes:

[0062] Beidou satellites are used to obtain vector information of expressway sections. The vector information includes positioning information, navigation image information and time information. The acquisition of vector information ensures accurate positioning.

[0063] Drones are used to obtain high-definition images of highway sections in real time, and geological signal data of the surrounding environment is obtained through high-definition image monitoring. Abnormal natural disasters mainly manifest themselves in abnormal conditions such as landslides and ground cracks. Drone technology can be used to obtain abnormal road conditions on highway sections in real time and intuitively. In actual use, a display can also be set up for observation.

[0064] The ground sensing terminal is used to monitor and obtain earthquake intensity signal data and soil temperature and humidity data based on sensors deployed along the expressway section; to reflect changes in ground conditions in real time, and to obtain data on factors directly affecting driving on the expressway.

[0065] A collaborative unit is set up in the information collection module; by setting up the collaborative unit, the information collected by Beidou satellites, drones and ground sensing terminals is integrated and processed collaboratively.

[0066] Specifically, as an implementation mode of the present invention, the information acquisition module acquires collaborative information by collaboratively analyzing vector information, geological signal data, seismic intensity signal data, and soil temperature and humidity data through a collaborative unit:

[0067] Determine the time information in the vector data, and select the geological signal data vector set, earthquake intensity signal data vector set, and soil temperature and humidity data vector set that meet the target time period for the expressway section;

[0068] The geological signal data vector set, the earthquake intensity signal data vector set and the soil temperature and humidity data vector set are input into ArcGIS as basic data to obtain the vector intervals of all current data vector sets;

[0069] The collaborative information and its analysis report are derived according to the spatial distribution characteristics of the data view of the vector interval of each data vector set.

[0070] In the above technical scheme, in this embodiment, first, the time information in the vector data is determined, and the time information is extracted from the vector information obtained from the Beidou satellite, and the extracted time information is used as the basis for data screening. The screened data include: a geological signal data vector set, a seismic intensity signal data vector set and a soil temperature and humidity data vector set that meet the target time period of the highway section; by screening out the geological signal data, seismic intensity signal data and soil temperature and humidity data related to the highway section within the target time period, a vector set is formed, thereby ensuring the timeliness and relevance of the analysis data.

[0071] Then, based on the vector sets of the above data types, the screened geological signal data vector set, earthquake intensity signal data vector set and soil temperature and humidity data vector set are used as basic data; by importing the basic data into the geographic information system software ArcGIS, the powerful spatial data analysis capabilities of the software are used to obtain the vector interval of each data vector set, that is, to obtain the spatial distribution range and characteristics of each type of data.

[0072] Finally, based on the spatial distribution characteristics of the data view of the vector interval of each data vector set, the collaborative information and its analysis report are derived. The spatial distribution characteristics of the data view are mainly based on the vector interval of each data vector set, analyzing the characteristics of the data in spatial distribution, such as concentrated areas, abnormal points, etc.; taking into account the time information and spatial distribution characteristics, the collaborative information is derived, that is, the interaction and correlation information between different data types, and based on the collaborative information, a detailed analysis report is generated to provide data support for risk identification.

[0073] Secondly, an environmental analysis module is set up to analyze collaborative information to obtain environmental dynamic data and geological dynamic data of expressway sections; based on the collaborative information collected by the information acquisition module, in-depth analysis is carried out to obtain environmental dynamic data and geological dynamic data of expressway sections, providing basic data for subsequent risk identification.

[0074] Specifically, as an implementation mode of the present invention, the environmental analysis module acquires environmental dynamic data and geological dynamic data based on the spatial analysis model in the following manner:

[0075] Input the collaborative information into the spatial analysis model to obtain the spatial distribution characteristic area of ​​each data vector set;

[0076] According to the characteristic area changes of geological signals and earthquake intensity signals in the continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. ;

[0077] And according to the characteristic area changes of geological signals and the characteristic area changes of soil temperature and humidity in the same continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. .

[0078] In the above technical solution, this embodiment obtains current environmental dynamic data and geological dynamic data through the environmental analysis module to realize early identification of the specific conditions of the expressway section, ensuring that the environmental analysis module can comprehensively analyze geological and environmental dynamic data from two dimensions of space and time, and provide more comprehensive and accurate data support for subsequent risk identification; this dynamic data acquisition method based on the spatial analysis model can effectively capture the precursor signals of natural disasters and improve the response speed and accuracy of the early warning system.

[0079] Specifically, first, the collaborative information is input into the spatial analysis model to obtain the spatial distribution characteristic area of ​​each data vector set; through the acquisition of the spatial distribution characteristic area, the collaborative information is input into the spatial analysis model, and the model uses geographic information system (GIS) technology to analyze the spatial distribution characteristics of each data vector set, including geological signals, earthquake intensity, soil temperature and humidity, and calculates the spatial distribution characteristic area of ​​each data type at a specific time point.

[0080] Then, according to the characteristic area changes of geological signals and earthquake intensity signals in the continuous time period in the collaborative information, the set of area differences at the corresponding time points is obtained. , to monitor the changes in the characteristic area of ​​geological signals, record the area value at each time point, and obtain the changes in the characteristic area of ​​geological signals; specifically, by comparing the characteristic area of ​​geological signals and the characteristic area of ​​earthquake intensity signals at different time points, the area difference is calculated to form a collection of geological dynamic data, which intuitively reflects the dynamic change trend of geological status and seismic activity in space.

[0081] Finally, similarly, according to the characteristic area changes of geological signals and the characteristic area changes of soil temperature and humidity in the same continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. Based on the above comparison results, an environmental dynamic data set of area differences at corresponding time points is obtained, which reveals the potential influence of soil temperature and humidity in environmental factors on the changes of geological signals, and intuitively reflects the dynamic change trend of geological status and surrounding environment over time, which is helpful to evaluate the impact of environmental changes on geological stability.

[0082] By constructing the corresponding control set above, it is ensured that the changes in the characteristic area of ​​the recorded earthquake intensity signal are obtained within the same continuous time period, and the data set is obtained. , and obtain the changes in the characteristic area of ​​the recorded environmental temperature and humidity signals, and obtain the data set .

[0083] Third, a risk identification module is set up to input environmental dynamic data and geological dynamic data into a preset identification model for training to output a risk coefficient, and to judge the risk level according to the size of the risk coefficient; the environmental dynamic data and geological dynamic data are input into a preset identification model, trained through a machine learning algorithm, and the risk coefficient is output, and the risk level is judged according to the size of the risk coefficient, thereby realizing a quantitative assessment of potential natural disaster risks.

[0084] Specifically, as an implementation of the present invention, the risk identification module includes:

[0085] By formula Calculate the risk factor of the highway section ,in is the total number of monitoring times in a continuous time period, ∈ ; is the first preset weight coefficient, is a second preset weight coefficient; For the The geological dynamic data parameters monitored by the secondary monitoring; For the The environmental dynamic data parameters monitored at this time; For the Standard values ​​of geological dynamic data parameters for the secondary monitoring; For the Standard values ​​of environmental dynamic data parameters monitored this time.

[0086] In the above technical solution, the present embodiment uses a calculation formula to calculate the occurrence rate of the characteristics of the relevant data based on the geological dynamic information and the environmental dynamic information, judges the risk of natural disasters, and then reflects the impact on the normal passage of the expressway section. Specifically, the risk coefficient The size of the specific analysis is carried out to achieve the comprehensive risk assessment goal of the expressway section; specifically, through the formula Calculate the risk factor of the highway section , where the first preset weight coefficient The weight of the overall highway section traffic obstruction is set based on the geological dynamic data parameters under monitoring, and this setting size can be obtained through simulation analysis by specific data software or qualitative comparison; the second preset weight coefficient It is set based on the proportion of the degree of obstruction to the traffic of the entire expressway section according to the environmental dynamic data parameters in the monitoring. Similarly, this setting size can be obtained by simulation analysis through specific data software or qualitative comparison. The details are not described in detail here.

[0087] It is necessary to further explain that the standard value , All of them are obtained through machine simulation based on historical experience and will not be elaborated here.

[0088] As an embodiment of the present invention, the risk factor The preset risk factor threshold range To compare:

[0089] like < , then the natural disaster risk rate of the current expressway section is judged to be low, and it is determined to be the third-level risk level;

[0090] like ≤ ≤ , then the natural disaster risk rate of the current expressway section is judged to be medium, and it is determined to be the second-level risk level;

[0091] like > , it is judged that the natural disaster risk rate of the current expressway section is high and is determined to be a level one risk level.

[0092] In the above technical solution, in this embodiment, the risk coefficient is The preset risk factor threshold range By comparing the size, the risk coefficient can be further analyzed to determine the probability of natural disasters occurring on the current highway section. The risk coefficient range can be used to intuitively reflect the risk coefficient, and the preset risk coefficient threshold interval can be used to determine the probability of natural disasters occurring on the current highway section. The specific judgment process is as follows: < , then the natural disaster risk rate of the current expressway section is judged to be low and is determined to be the third-level risk level; if ≤ ≤ , then the natural disaster risk rate of the current expressway section is judged to be medium, and it is determined to be a second-level risk level; if > , it is judged that the natural disaster risk rate of the current expressway section is high and is determined to be a level one risk level.

[0093] Fourth, the risk warning module is used to output corresponding warning strategies to the traffic control center and the geological bureau according to the risk level; formulate corresponding warning strategies according to the risk level, and output warning information to the traffic control center and the geological bureau in a timely manner to ensure that relevant departments can respond in time and take necessary preventive measures.

[0094] Specifically, as an implementation mode of the present invention, the designed early warning strategy includes:

[0095] The warning mark is made according to the output risk level: the third-level risk level is recorded as "0", the second-level risk level is recorded as "1", and the first-level risk level is recorded as "2";

[0096] Set the monitoring frequency and monitoring warning response interval duration corresponding to each level of marked data;

[0097] The risk level is positively correlated with the monitoring frequency and the duration of the monitoring warning response interval.

[0098] In the above technical solution, the specific early warning strategy in this embodiment is as follows:

[0099] Risk level warning mark:

[0100] Level 3 risk level: marked as "0", indicating that the risk is low, but still needs to be monitored.

[0101] Level 2 risk level: Marked as "1", indicating that there is a medium risk and the monitoring frequency needs to be increased.

[0102] Level 1 risk: marked as "2", indicating the highest risk, requiring immediate early warning measures;

[0103] Set monitoring frequency:

[0104] The setting of monitoring frequency is positively correlated with the risk level, that is, the higher the risk level, the more frequent the monitoring frequency; the following is an example in this embodiment:

[0105] Risk level three: Under the “0” mark, the monitoring frequency can be set to once every 12 hours to maintain basic monitoring.

[0106] Level 2 risk level: Under the “1” mark, the monitoring frequency is increased to once every 6 hours to capture potential changes more promptly.

[0107] Level 1 risk: Under the “2” mark, the monitoring frequency should be increased to once every 1-2 hours to ensure real-time monitoring of risk dynamics.

[0108] Set the monitoring warning response interval duration:

[0109] The monitoring warning response interval duration is also positively correlated with the risk level, that is, the higher the risk level, the faster the response speed is required. The following is an example in this embodiment:

[0110] Risk level three: The monitoring warning response interval under the “0” mark can be set to within 20-24 hours.

[0111] Level 2 risk: The monitoring and warning response interval marked “1” should be shortened to 10-12 hours to improve response efficiency.

[0112] Level 1 risk: The monitoring warning response interval marked with “2” should be controlled within 2-4 hours to ensure that quick action can be taken to reduce potential losses.

[0113] Through the implementation of the early warning strategy, differentiated monitoring and response measures can be taken according to different risk levels, which not only ensures the effective use of resources, but also improves the overall response speed and efficiency of the early warning system, which is of great significance for ensuring the safe operation of expressway sections.

[0114] Fifth, the risk control module is used to carry out traffic control and geological risk prevention and control measures on expressway sections according to the early warning strategy; based on the early warning strategy, traffic control is implemented on expressway sections, such as temporary road closures, speed limits, etc. At the same time, geological risk prevention and control measures are taken, such as strengthening the roadbed, setting up anti-landslide projects, etc., to minimize the impact of natural disasters on expressway sections.

[0115] As an implementation mode of the present invention, the risk control module includes:

[0116] Adjust the traffic control monitoring frequency and the monitoring warning response interval duration according to the warning strategy;

[0117] And start and suspend risk prevention operations according to early warning strategies, and choose to activate emergency plans to reduce or avoid the occurrence of risk events.

[0118] In the above technical solution, the traffic control monitoring frequency adjustment in this embodiment includes adjusting the frequency of traffic control monitoring according to the monitoring frequency set in the early warning strategy; maintaining a lower frequency of monitoring at a low risk level to reduce resource consumption; and increasing the monitoring frequency at a high risk level to ensure that potential traffic safety hazards can be discovered in a timely manner. The adjustment of the monitoring and early warning response interval duration shortens the monitoring and early warning response interval duration at a high risk level to ensure that once an abnormal situation is discovered, a quick response can be made to implement necessary traffic control or geological risk prevention and control measures. By converting it into an actual control plan, it is ensured that at different risk levels, appropriate traffic control and geological risk prevention and control measures can be taken on expressway sections, thereby ensuring the safe operation of the expressway network and providing a safer and more reliable environment for public travel.

[0119] As an embodiment of the present invention, it also includes an early warning display terminal for displaying graphic information of early warning signals and early warning strategy feedback;

[0120] The early warning display terminal usually includes: real-time display of early warning signals, chart information feedback terminal, early warning strategy feedback display terminal, interactive operation interface, historical data query and analysis interface; it is responsible for displaying early warning signals and early warning strategies to decision makers and relevant personnel in an intuitive and easy-to-understand manner.

[0121] The functions of the early warning display terminal mainly include:

[0122] Real-time display of warning signals is usually set up at traffic intersections, checkpoints and diversion stations. Warning signals are displayed in eye-catching colors and icons. For example, red light indicates the first level risk level, yellow light indicates the second level risk level, and green light indicates the third level risk level, ensuring the timeliness and visual impact of information, and facilitating rapid identification of current risk conditions.

[0123] Graphic information feedback terminals are usually located in traffic control centers and regional geological bureau centers. They provide a wealth of graphic information, such as line graphs, bar graphs, heat maps, etc., to show the trend of risk levels over time, the risk distribution in different regions, the adjustment of monitoring frequency and warning response interval duration, etc., to help decision makers fully understand the working status and effectiveness of the early warning system.

[0124] The early warning strategy feedback display terminal ensures that decision makers can grasp the implementation effect of system response measures in real time by displaying the implementation status of the early warning strategy, including the adjustment of traffic control monitoring frequency, the change of monitoring warning response interval duration, the start and pause status of risk prevention operations, and the activation of emergency plans.

[0125] The interactive operation interface allows users to manually adjust the early warning strategy according to actual conditions, such as temporarily increasing the monitoring frequency, manually starting risk prevention operations, etc., which enhances the flexibility and adaptability of the system.

[0126] The historical data query and analysis interface has the historical data query function, which can view the warning signal records and warning strategy execution status in the past period of time, support data export and analysis, and provide data support for system optimization and strategy adjustment.

[0127] The early warning display terminal can not only ensure the timely transmission of early warning information and the transparent implementation of early warning strategies, but also provide decision makers with the data and analysis required for decision support. It is an important tool for achieving efficient and accurate risk early warning and control.

[0128] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0129] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0130] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this application, they shall all fall within the protection scope of the present invention.

Claims

1. A natural disaster risk early warning system for high-speed sections, characterized in that: The system comprises: The information collection module is used to collect collaborative information of expressway sections in real time through Beidou satellites, drones and ground sensing terminals; The information collection module includes a collaboration unit; The Beidou satellite is used to obtain vector information of the expressway section; the vector information includes positioning information, navigation image information and time information; The drone is used to obtain high-definition images of the highway section in real time, and obtain geological signal data of the surrounding environment through high-definition image monitoring; The ground sensing terminal is used to monitor and obtain earthquake intensity signal data and soil temperature and humidity data based on sensors deployed along the expressway section; Environmental analysis module, used to analyze collaborative information to obtain environmental dynamic data and geological dynamic data of high-speed road sections; The risk identification module is used to input environmental dynamic data and geological dynamic data into a preset identification model to train and output a risk coefficient, and to determine the risk level according to the size of the risk coefficient; The risk warning module is used to output corresponding warning strategies to the traffic control center and the geological bureau according to the risk level; The risk control module is used to implement traffic control and geological risk prevention and control measures on highway sections according to early warning strategies; The information acquisition module acquires collaborative information by collaboratively analyzing vector information, geological signal data, seismic intensity signal data, and soil temperature and humidity data through collaborative units: Determine the time information in the vector data, and select the geological signal data vector set, earthquake intensity signal data vector set, and soil temperature and humidity data vector set that meet the target time period for the expressway section; The geological signal data vector set, the earthquake intensity signal data vector set and the soil temperature and humidity data vector set are input into ArcGIS as basic data to obtain the vector intervals of all current data vector sets; Deriving collaborative information and analysis reports thereof according to spatial distribution characteristics of data views of vector intervals of each data vector set; The environmental analysis module acquires environmental dynamic data and geological dynamic data based on the spatial analysis model in the following ways: Input the collaborative information into the spatial analysis model to obtain the spatial distribution characteristic area of ​​each data vector set; According to the characteristic area changes of geological signals and earthquake intensity signals in the continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. ; And according to the characteristic area changes of geological signals and the characteristic area changes of soil temperature and humidity in the same continuous time period in the collaborative information, a set of area differences at corresponding time points is obtained. ; The risk identification module includes: By formula Calculate the risk factor of the highway section ,in is the total number of monitoring times in a continuous time period, ∈ ; is the first preset weight coefficient, is a second preset weight coefficient; For the The geological dynamic data parameters monitored by the secondary monitoring; For the The environmental dynamic data parameters monitored at this time; For the Standard values ​​of geological dynamic data parameters for the second monitoring; For the Standard values ​​of environmental dynamic data parameters monitored at this time; The risk factor The preset risk factor threshold range To compare: like < , then the natural disaster risk rate of the current expressway section is judged to be low, and it is determined to be the third-level risk level; like ≤ ≤ , then the natural disaster risk rate of the current expressway section is judged to be medium, and it is determined to be the second-level risk level; like > , then the natural disaster risk rate of the current expressway section is judged to be high, and it is determined to be the first-level risk level; The early warning strategy includes: The warning mark is made according to the output risk level: the third-level risk level is recorded as "0", the second-level risk level is recorded as "1", and the first-level risk level is recorded as "2"; Set the monitoring frequency and monitoring warning response interval duration corresponding to each level of marked data; The risk level is positively correlated with the monitoring frequency and the duration of the monitoring warning response interval.

2. A natural disaster risk early warning system for high-speed sections according to claim 1, characterized in that: The risk control module includes: Adjust the traffic control monitoring frequency and the monitoring warning response interval duration according to the warning strategy; And start and suspend risk prevention operations according to early warning strategies, and choose to activate emergency plans to reduce or avoid the occurrence of risk events.

3. A natural disaster risk early warning system for high-speed sections according to claim 1, characterized in that: It also includes an early warning display terminal for displaying graphic information of early warning signals and early warning strategy feedback.

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