Method, device and computer-readable storage medium for monitoring ice condensation hazards at high-altitude tunnel entrances

Abstract

The present invention relates to the field of disaster monitoring technology, and specifically discloses a method, device, and computer-readable storage medium for monitoring ice condensation disasters at high-altitude tunnel entrances. The method comprises: determining ice condensation-related parameters at high-altitude tunnel entrances; analyzing the ice condensation-related parameters to determine ice condensation core parameters; deploying a mobile monitoring device at the high-altitude tunnel entrance, and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the mobile monitoring device and the ice condensation core parameters; performing a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field; and generating disaster monitoring results based on the reconstructed meteorological field. By combining the actual physical characteristics of high-altitude tunnel entrances, analyzing their ice condensation mechanisms, and conducting ice condensation monitoring and early warning based on the ice condensation core parameters, the real-time, accuracy, and comprehensiveness of ice condensation monitoring are improved, meeting the actual needs of enterprises.

Description

Technical Field

[0001] The present invention relates to the field of disaster monitoring technology, and in particular to a method, device and computer-readable storage medium for monitoring ice condensation disasters at high-altitude tunnel entrances. Background Art

[0002] With the continuous development of the domestic economy, people have higher and higher requirements for the convenience of transportation. In order to improve the convenience of transportation, especially for transportation in plateaus, mountainous areas and other areas, corresponding tunnels need to be opened to greatly improve traffic efficiency and shorten travel time.

[0003] Tunnels constructed in plateau areas differ significantly from those in more common areas. High-altitude tunnel portals face complex meteorological conditions, including extremely low temperatures (below -30°C), strong winds (instantaneous wind speeds >15m / s), low air pressure (altitudes >4000m), and dramatic fluctuations in sunlight (diurnal temperature differences >30°C). These factors contribute to diverse and highly coupled ice-causing hazards. Traditional monitoring methods struggle to accurately capture critical conditions, and prevention and control measures often fail due to data loss.

[0004] On the other hand, when ice is detected at a tunnel entrance, spraying a salt solution to melt it is typically done. However, this method relies on chemical de-icing agents, which corrodes equipment and pollutes the environment over time. Technicians have also considered other single-use de-icing methods, such as heating lines with direct current to melt ice. However, these methods require manual wiring and are unsuitable for non-conductive structures (such as tunnel linings), making them unsuitable for practical applications. Summary of the Invention

[0005] In order to overcome the above-mentioned technical problems existing in the prior art, the embodiments of the present invention provide a method, device and computer-readable storage medium for monitoring ice condensation disasters at high-altitude tunnel entrances. By combining the actual physical characteristics of high-altitude tunnel entrances, the ice condensation mechanism is analyzed, and ice condensation monitoring and early warning are carried out around the core parameters of ice condensation, thereby improving the real-time, accuracy and comprehensiveness of ice condensation monitoring and meeting the actual needs of enterprises.

[0006] In order to achieve the above-mentioned objectives, an embodiment of the present invention provides a method for monitoring ice condensation disasters at high-altitude tunnel entrances, the method comprising: determining ice condensation-related parameters at high-altitude tunnel entrances; analyzing the ice condensation-related parameters to determine ice condensation core parameters; deploying a mobile monitoring device at the high-altitude tunnel entrance, and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the ice condensation core parameters by the mobile monitoring device; performing a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field; and generating disaster monitoring results based on the reconstructed meteorological field.

[0007] Preferably, the analyzing the ice condensation related parameters and determining the ice condensation core parameters include: establishing an ice condensation analysis model; performing single parameter testing and coupling effect testing on the ice condensation related parameters based on the ice condensation analysis model to obtain a first test result; determining preliminary core parameters based on the first test result; performing a simulated field test based on the preliminary core parameters to obtain a second test result; and determining the ice condensation core parameters based on the second test result.

[0008] Preferably, the method also includes: before deploying the mobile monitoring device, obtaining environmental data of the high-altitude tunnel entrance; determining limit data based on the environmental data and a preset safety threshold, and obtaining parameter accuracy corresponding to the ice core parameters; determining an initial configuration scheme of the mobile monitoring device, the initial configuration scheme including sensor configuration data, sensor configuration position, physical strength design information, and internal environment maintenance information; adjusting the sensor configuration data based on the limit data and the parameter accuracy to obtain an adjusted sensor; obtaining environmental requirement information of the adjusted sensor, optimizing the internal environment maintenance information based on the environmental requirement information to obtain optimized environment maintenance information; adjusting the sensor configuration position based on the optimized environment maintenance information to obtain an adjusted position; optimizing the physical strength design information based on the limit data to obtain optimized strength design information; and manufacturing the mobile monitoring device based on the adjusted sensor, the optimized environment maintenance information, the adjusted position, and the optimized strength design information.

[0009] Preferably, the obtaining of real-time monitoring data of the high-altitude tunnel entrance includes: determining a contribution rate of each parameter in the ice condensation core parameters; obtaining current real-time monitoring data, analyzing the ice condensation generation rate of the high-altitude tunnel entrance according to the current real-time monitoring data and the contribution rate, and generating an ice condensation rate analysis result; obtaining an initial monitoring frequency, and adjusting the initial monitoring frequency in real time based on the ice condensation rate analysis result to obtain an adjusted monitoring frequency; and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the adjusted monitoring frequency.

[0010] Preferably, the real-time monitoring data includes temperature data, humidity data, wind speed data, air pressure data, wind direction data, light intensity data, rainfall / snowfall data and ice thickness data, and the three-dimensional meteorological field reconstruction operation is performed based on the real-time monitoring data to generate a reconstructed meteorological field, including: performing a preprocessing operation on the real-time monitoring data to obtain preprocessed data; generating a three-dimensional distribution cloud map of the wind speed field based on the preprocessed wind speed data and wind direction data; generating a three-dimensional distribution cloud map of the temperature field based on the preprocessed temperature data and light intensity data; generating a three-dimensional distribution cloud map of the humidity field based on the preprocessed humidity data and rainfall / snowfall data; obtaining pollutant concentration, and determining real-time freezing point data based on the pollutant concentration and the preprocessed air pressure data; generating a reconstructed meteorological field based on the three-dimensional distribution cloud map of the temperature field, the three-dimensional distribution cloud map of the humidity field, the three-dimensional distribution cloud map of the wind speed field, the preprocessed real-time freezing point data and the preprocessed ice thickness data.

[0011] Preferably, generating disaster monitoring results based on the reconstructed meteorological field includes: determining the overwind speed area and underwind speed area of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the wind speed field; determining the low temperature duration and temperature difference range of each area of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the temperature field; determining the humidity change information of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the temperature field, the ice layer thickness data and the three-dimensional distribution cloud map of the humidity field; generating disaster monitoring results based on the overwind speed area, the underwind speed area, the low temperature duration, the temperature difference range, and the humidity change information.

[0012] Preferably, the method further includes: after obtaining the disaster monitoring results, generating preliminary icing prediction information for the high-altitude tunnel entrance based on the low temperature duration, the temperature difference range, and the humidity change information; optimizing the preliminary icing prediction information based on the overwind speed area and the underwind speed area to generate optimized icing prediction information; obtaining the current high-altitude position and determining the temperature stratification corresponding to the high-altitude position; adjusting the optimized icing prediction information based on the temperature stratification to obtain adjusted prediction information; and outputting corresponding warning information based on the adjusted prediction information.

[0013] Preferably, the mobile monitoring device also includes a microwave heating device and a mechanical de-icing arm, and the method also includes: after generating the early warning information, determining the icing disaster stage of the high-altitude tunnel entrance based on the adjusted prediction information; if the icing disaster stage is a prevention stage, starting the hot air circulation system of the high-altitude tunnel entrance; if the icing disaster stage is a warning stage, applying an ice-repellent coating to the high-altitude tunnel entrance; if the icing disaster stage is a high-risk stage, controlling the microwave heating device to perform a directional microwave heating operation, and controlling the mechanical de-icing arm to perform an active coordinated de-icing operation.

[0014] Correspondingly, the present invention also provides an ice condensation disaster monitoring device for high-altitude tunnel entrances, which is applied to the method provided according to an embodiment of the present invention. The device includes: a parameter determination unit, used to determine the ice condensation-related parameters of the high-altitude tunnel entrance; an analysis unit, used to analyze the ice condensation-related parameters and determine the ice condensation core parameters; a data acquisition unit, used to deploy a mobile monitoring device at the high-altitude tunnel entrance, and obtain real-time monitoring data of the high-altitude tunnel entrance based on the mobile monitoring device according to the ice condensation core parameters; a meteorological field reconstruction unit, used to perform a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field; and a monitoring unit, used to generate disaster monitoring results based on the reconstructed meteorological field.

[0015] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the method provided by an embodiment of the present invention when the program is executed by a processor.

[0016] The technical solution provided by the present invention has at least the following technical effects:

[0017] By analyzing the ice formation mechanism at high-altitude tunnel entrances, the core parameters that have a significant impact on ice formation are determined. On this basis, monitoring data corresponding to the core parameters are collected in real time through mobile monitoring devices that can operate stably and reliably in extreme high-altitude environments. Disaster monitoring and analysis are carried out using the reconstructed three-dimensional meteorological field, thereby generating real-time, accurate and reliable disaster monitoring results.

[0018] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0020] Figure 1This is a flowchart of a specific implementation of the method for monitoring ice condensation disasters at high-altitude tunnel entrances provided by an embodiment of the present invention;

[0021] Figure 2 It is a structural schematic diagram of an ice condensation disaster monitoring device for a high-altitude tunnel entrance provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0023] The terms "system" and "network" in the embodiments of the present invention can be used interchangeably. "Multiple" refers to two or more. In view of this, "multiple" can also be understood as "at least two" in the embodiments of the present invention. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / ", unless otherwise specified, generally indicates that the previous and next associated objects are in an "or" relationship. In addition, it should be understood that in the description of the embodiments of the present invention, words such as "first" and "second" are only used to distinguish the purpose of description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0024] See Figure 1 An embodiment of the present invention provides a method for monitoring ice condensation disasters at high-altitude tunnel entrances, the method comprising:

[0025] S10: Determine ice condensation related parameters at high altitude tunnel portals;

[0026] S20: Analyze the ice condensation related parameters to determine the ice condensation core parameters;

[0027] S30: deploying a mobile monitoring device at a high-altitude tunnel entrance, and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the ice core parameters by the mobile monitoring device;

[0028] S40: performing a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field;

[0029] S50: Generate disaster monitoring results based on the reconstructed meteorological field.

[0030] In one possible implementation, the ice condensation-related parameters of high-altitude tunnel portals are first determined. These ice condensation-related parameters can be preliminarily determined by technicians based on theoretical knowledge, actual observations, and research. All parameters related to the ice condensation mechanism at high-altitude tunnel portals may exist. Based on these parameters, there may be a large number of redundant parameters or low-contribution parameters, which will have a significant impact on subsequent analysis and calculations and greatly increase the workload. Therefore, it is also necessary to combine the analysis of the ice condensation-related parameters and screen them to determine the core ice condensation parameters.

[0031] In an embodiment of the present invention, the analysis of the ice condensation-related parameters to determine the ice condensation core parameters includes: establishing an ice condensation analysis model; performing single parameter testing and coupling effect testing on the ice condensation-related parameters based on the ice condensation analysis model to obtain a first test result; determining preliminary core parameters based on the first test result; performing a simulated field test based on the preliminary core parameters to obtain a second test result; and determining the ice condensation core parameters based on the second test result.

[0032] In one possible implementation, numerical simulation is combined with field tests to reveal the influence of low-pressure environments on freezing point temperature (for every 10 kPa decrease in pressure, the freezing point rises by 0.6 to 1.2°C), and the coupling effects of strong winds and sunlight on ice adhesion and melting rate, so as to comprehensively determine the precise core parameters of ice condensation. Specifically, an ice condensation analysis model is first established. In an embodiment of the present invention, a multiple regression analysis method is used to establish the ice condensation analysis model, which is characterized, for example, as follows.

[0033]

[0034]

[0035]

[0036] Among them, Tice and Tice' are the freezing point temperatures at different observation points, P and P' are the air pressures at different observation points, v and v' are the wind speeds at different observation points, and I and I' are the light intensities at different observation points. is the model error term, which is determined based on specific observation data. After creating the above-mentioned ice condensation analysis model, it can be run on a host computer or computer, and numerical simulation analysis can be performed to determine the more important ice condensation parameters. For example, by performing a single parameter test on each ice condensation-related parameter to determine the impact of each parameter on ice condensation; then further coupling effect tests are performed on the mutual synergy of multiple parameters to determine the coupling effect of different parameters on the ice condensation effect; and the more important ice condensation parameters are preliminarily determined. For example, the more important core parameters preliminarily determined include but are not limited to temperature, humidity, air pressure, wind speed, wind direction, light intensity, rainfall / snow amount, ice thickness and other parameters.

[0037] The preliminary core parameters are then further tested using field tests. For example, an environment similar to a high-altitude tunnel entrance can be simulated, and different environmental parameters can be simulated using relevant equipment to verify the actual effects of the preliminary core parameters. Secondary test results are obtained, and the core ice formation parameters are determined based on these second test results. For example, by simply varying the air pressure (±10kPa) and observing the freezing point variation (0.6-1.2°C), it was found that its contribution reached 40%. Furthermore, under the combined effects of strong winds (20m / s) and high light (800W / m²), ice adhesion decreased by 60% and the melting rate increased to 1.8 times that of a single parameter. In this embodiment of the present invention, eight parameters are determined as the core ice formation parameters: temperature, humidity, air pressure, wind speed, wind direction, light intensity, rainfall / snow amount, and ice thickness.

[0038] After determining the core ice condensation parameters, a mobile monitoring device is deployed at the high-altitude tunnel entrance. The mobile monitoring device uses the core ice condensation parameters to obtain real-time monitoring data from the high-altitude tunnel entrance. Because high-altitude tunnel entrances are located in areas of low pressure, extreme cold, and high winds, conventional monitoring devices cannot meet actual needs. For example, in some scenarios, the temperature at high-altitude tunnel entrances may drop below -40°C, causing many sensors to be unable to accurately monitor environmental data or significantly reducing sensing accuracy, making them unable to meet actual needs.

[0039] In order to solve the above technical problems, it is necessary to design and manufacture the specific structure and configuration of the mobile monitoring device based on the actual scene characteristics of high-altitude tunnel entrances to meet the actual needs of extreme scenarios.

[0040] In an embodiment of the present invention, the method also includes: before deploying the mobile monitoring device, obtaining environmental data of the high-altitude tunnel entrance; determining limit data based on the environmental data and a preset safety threshold, and obtaining parameter accuracy corresponding to the ice core parameters; determining an initial configuration scheme of the mobile monitoring device, the initial configuration scheme including sensor configuration data, sensor configuration position, physical strength design information, and internal environment maintenance information; adjusting the sensor configuration data based on the limit data and the parameter accuracy to obtain an adjusted sensor; obtaining environmental requirement information of the adjusted sensor, optimizing the internal environment maintenance information based on the environmental requirement information to obtain optimized environment maintenance information; adjusting the sensor configuration position based on the optimized environment maintenance information to obtain an adjusted position; optimizing the physical strength design information based on the limit data to obtain optimized strength design information; and manufacturing the mobile monitoring device based on the adjusted sensor, the optimized environment maintenance information, the adjusted position, and the optimized strength design information.

[0041] In one possible implementation, environmental data for a high-altitude tunnel entrance is first acquired. Based on this environmental data and a preset safety threshold, limit data is determined to obtain the parameter accuracy corresponding to the core parameters of ice condensation. For example, environmental data for a high-altitude tunnel entrance indicates that the annual temperature in this area is generally between 30°C and -40°C, with fluctuations of ±20% in some extreme cases. Therefore, based on the above information, the preset safety threshold is set at ±30%, and the environmental data is determined to be between 39°C and -52°C. Based on this, sensors that meet the corresponding adaptability are selected. At the same time, the parameter accuracy corresponding to the core parameters of ice condensation is obtained. For example, a humidity sensor with a sensing accuracy of ±0.1°C, a barometer with a sensing accuracy of 0.1hPa, an ultrasonic anemometer with a range of 0-30m / s, a photon sensor with a spectral range of 400-700nm, and a laser ice thickness meter with an accuracy of ±1mm are required. Based on these constraints, sensors are selected to meet the actual application requirements of extreme scenarios.

[0042] On this basis, an initial configuration plan of the mobile monitoring device is obtained. The initial configuration plan is the initial design plan of the mobile monitoring device, including but not limited to sensor configuration data, sensor configuration position, physical strength design information (the physical strength impact that the shell can withstand), internal environment maintenance information (the environmental conditions that can be maintained internally, such as the temperature range within which the interior can be maintained by a heating device, etc.) and other information.

[0043] Then, the sensor configuration data is adjusted according to the above-mentioned limit numbers and parameter accuracy, that is, optimization selection is performed to obtain the adjusted sensor; since the adjusted sensor may still not be able to directly face extreme environments, it is also necessary to obtain its environmental requirement information, and optimize the internal environment maintenance information according to the environmental requirement information to obtain the optimized environment maintenance information, that is, it is necessary to ensure that the mobile monitoring device can provide it with the minimum environmental capacity to meet its normal operation. The sensor locations are then adjusted based on the optimized environmental maintenance information to obtain adjusted locations. For example, because the sidewall temperature cannot be maintained within a high range in extremely low-temperature environments, a sensor originally located on the sidewall is adjusted to a central position to ensure its operating environment remains within a reasonable range. Finally, the physical strength design information is optimized based on the extreme data to obtain optimized strength design information. Because high-altitude tunnel entrances may be subject to unexpected events such as landslides and falling ice, which could damage the mobile monitoring device, and because high-altitude tunnel entrances present difficult maintenance challenges, the physical strength of the housing is adaptively optimized to further improve its natural bearing capacity and maximize its operational stability. For example, in this embodiment of the present invention, the mobile monitoring device utilizes an aviation aluminum-magnesium alloy housing with a built-in constant-temperature heating module (operating temperature -40°C to 60°C) and an IP68 protection rating. Finally, the optimized mobile monitoring device is manufactured based on the above information.

[0044] In an embodiment of the present invention, various parameters of the mobile monitoring device are adaptively optimized and designed according to the actual environmental characteristics of the high-altitude tunnel entrance, so that it can meet the safety requirements and high-precision monitoring requirements in extreme environments, thereby ensuring the stability and accuracy of subsequent data collection.

[0045] After manufacturing the above-mentioned mobile monitoring device, it is configured. For example, in an embodiment of the present invention, it is necessary to collect real-time, comprehensive, and accurate data on the three-dimensional space of the arch, sidewall, and road surface of a high-altitude tunnel entrance. At the same time, the operating costs of the enterprise need to be considered. Therefore, three mobile monitoring robots can be arranged within a 50m range of the longitudinal entrance. Dynamic inspections can be achieved through rails or wheeled chassis, and a linkage control system can be constructed from four aspects: spatial layout optimization, dynamic task allocation, communication and path planning, and abnormal working condition response. Specifically, its layout configuration scheme is as follows:

[0046] Vault: One robot uses a suspended track + rotating pan / tilt head to cover a 20m×50m area at the top (vertical height 5-25m).

[0047] Side walls: Two robots use a wheeled chassis + retractable robotic arms, responsible for the left and right side walls respectively (covering a height of 0-20m and a vertical coverage of 50m on each side).

[0048] Road surface: The sidewall robot chassis extends to the ground and simultaneously scans for cracks or water accumulation on the road surface (coverage width ±2m).

[0049] These multiple robots use LiDAR and UWB positioning to calculate the robot spacing in real time, ensuring that the longitudinal spacing between adjacent robots is ≥10m (to avoid signal interference and inspection blind spots). For example, if robot A is located at 0m in the longitudinal direction, robot B and robot C are deployed at 15m and 35m, respectively, forming a "front-middle-back" echelon. Tasks are then decoupled within the areas to be monitored. For example, a 50m longitudinal area can be divided into five 10m sub-areas, with each robot assigned a primary inspection zone based on its number (A / B / C) (e.g., robot A covers 0-10m, robot B covers 10-20m, etc.).

[0050] During monitoring missions, task priorities are assigned. For example, based on the actual ice formation process at high-altitude tunnel entrances, a full-coverage scan of the vault is performed every 10 minutes (using lidar and infrared thermal imaging). Sidewalls and road surfaces are scanned every 5 minutes (using high-definition cameras and ultrasonic thickness measurement). Because battery consumption may vary between robots (e.g., due to varying slopes, planned paths, battery capacities, and battery quality), area boundaries are dynamically adjusted based on the remaining battery power and task progress of the robots (e.g., if robot A is low on battery, 20% of its tasks will be transferred to robot B). This balances their capabilities and ensures reliable monitoring of all areas.

[0051] During monitoring, the robots share a local map (built using SLAM technology). When an obstacle (such as a fallen rock) is detected, the master control node replans the path. For example, the blocked robot pauses, while adjacent robots adjust their speed (e.g., slow down by 50%) and take a detour. In case of conflicting paths, a priority queue is used (those with lower battery power have priority). Each robot is also optimized for energy consumption to ensure maximum performance. Specifically, the Dijkstra algorithm is used to calculate the shortest path based on the robot's current position and the task point, avoiding areas with steep slopes (wheeled chassis increase energy consumption by 30%).

[0052] In actual applications, robots may encounter unexpected events while operating at high-altitude tunnel entrances. To ensure operational safety and to promptly adjust monitoring plans, intelligent responses are required. For example, in the first embodiment, if a rockfall or ice drop occurs at the top of the tunnel entrance, if the robot's LiDAR detects an obstacle greater than 0.1 m³, the following mechanisms are triggered: an alarm signal is uploaded to the monitoring center via 5G; robots A, B, and C simultaneously initiate high-frequency scanning (up to 1 Hz) to generate a 3D model of the obstacle; the master control node calculates the optimal obstacle avoidance path and notifies the following vehicles / personnel to slow down (via an audible and visual alarm).

[0053] In the second embodiment, water seepage occurs, which may cause serious damage to the use of the robot. Therefore, once the humidity sensor triggers an alarm, the robot B / C is immediately controlled to expand the detection range to the adjacent 10m area, quickly locate the source of the water seepage, and feedback the corresponding detection information to assist technical personnel in taking corresponding response measures in a timely manner, ensure the safety of the robot's use, and promptly adjust the monitoring strategy to ensure the reliability and accuracy of data collection in the entire high-altitude tunnel entrance.

[0054] When collecting data in real time, the meteorological environment inside the high-altitude tunnel entrance may change significantly. Therefore, in order to ensure the real-time and reliability of the robot's data collection, the robot needs to perform adaptive optimization control to ensure the accuracy of the data.

[0055] In an embodiment of the present invention, obtaining real-time monitoring data of the high-altitude tunnel entrance includes: determining the contribution rate of each parameter in the ice condensation core parameters; obtaining current real-time monitoring data, analyzing the ice condensation generation speed of the high-altitude tunnel entrance based on the current real-time monitoring data and the contribution rate, and generating an ice condensation speed analysis result; obtaining an initial monitoring frequency, and adjusting the initial monitoring frequency in real time based on the ice condensation speed analysis result to obtain an adjusted monitoring frequency; and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the adjusted monitoring frequency.

[0056] In one possible implementation, the contribution rate of each core parameter in the ice formation parameters is first determined. Current real-time monitoring data is then obtained. Based on this real-time monitoring data, the current meteorological conditions at the high-altitude tunnel entrance can be assessed. Specifically, the ice formation rate at the high-altitude tunnel entrance is analyzed based on the real-time monitoring data (i.e., the current meteorological conditions) and the contribution rate, generating an ice formation rate analysis result. For example, if a current wind speed > 5 m / s is detected, further analysis indicates an increase in the ice formation rate, and a high-frequency monitoring mode can be switched. For example, by default, the robot collects data using an initial monitoring frequency. If an increase in the ice formation rate is determined, the initial monitoring frequency is adjusted in real time based on the ice formation rate analysis result to obtain an adjusted monitoring frequency. Real-time monitoring data for the high-altitude tunnel entrance is then acquired based on this adjusted monitoring frequency, effectively improving the real-time, accuracy, and reliability of data monitoring at the high-altitude tunnel entrance.

[0057] After obtaining the original real-time monitoring data, in order to achieve accurate and convenient analysis of the high-altitude tunnel entrance, a three-dimensional meteorological reconstruction is performed on it. Specifically, in an embodiment of the present invention, the real-time monitoring data includes temperature data, humidity data, wind speed data, air pressure data, wind direction data, light intensity data, rainfall / snowfall data, and ice thickness data. The three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field includes: performing a preprocessing operation on the real-time monitoring data to obtain preprocessed data; generating a three-dimensional distribution cloud map of the wind speed field based on the preprocessed wind speed data and wind direction data; generating a three-dimensional distribution cloud map of the temperature field based on the preprocessed temperature data and light intensity data; generating a three-dimensional distribution cloud map of the humidity field based on the preprocessed humidity data and rainfall / snowfall data; obtaining pollutant concentrations, and determining real-time freezing point data based on the pollutant concentrations and the preprocessed air pressure data; and generating a reconstructed meteorological field based on the three-dimensional distribution cloud map of the temperature field, the three-dimensional distribution cloud map of the humidity field, the three-dimensional distribution cloud map of the wind speed field, the preprocessed real-time freezing point data, and the preprocessed ice thickness data.

[0058] In one possible implementation, the real-time monitoring data is first preprocessed, for example, using Kalman filtering and spatiotemporal interpolation techniques to eliminate sensor noise and complete locally missing data. A three-dimensional wind speed distribution cloud map is then generated based on the preprocessed wind speed and direction data. Specifically, the preprocessed wind speed and direction data are converted into corresponding three-dimensional spatial distribution data. The wind direction data is then converted into vector components of wind speed (u, v, w), where the horizontal component is: u = -wind speed × sin(wind direction angle), v = -wind speed × cos(wind direction angle). The vertical component w is typically small or zero (unless there is special vertical motion data). This data is then input into visualization software to generate a three-dimensional wind speed distribution cloud map.

[0059] A 3D temperature distribution cloud map is then generated based on the preprocessed temperature and light intensity data. For example, this is done by aligning the coordinate system and resolution of the preprocessed temperature and light intensity data and then inputting them into visualization software. A 3D humidity distribution cloud map can also be generated based on the preprocessed humidity and rainfall / snowfall data using the same principle.

[0060] Because varying air pressures and the concentration of contaminants on the ice surface (e.g., residual deicing agents) can affect the freezing point, and thus the subsequent degree and course of ice formation, real-time freezing point data is determined based on preprocessed air pressure data. This allows for subsequent analysis to determine the synergistic effect of freezing point data and various core ice formation parameters on ice formation at high-altitude tunnel entrances. Finally, a reconstructed meteorological field is generated based on the aforementioned segmented cloud maps, real-time freezing point data, and preprocessed ice thickness data.

[0061] In an embodiment of the present invention, by combining the actual physical mechanism of the ice condensation process at a high-altitude tunnel entrance, a three-dimensional distribution cloud map of the wind speed field is generated according to the synergistic effect of wind speed and wind direction in the ice condensation process; a three-dimensional distribution cloud map of the temperature field is generated according to the synergistic effect of temperature and light intensity in the ice condensation process; and a three-dimensional distribution cloud map of the humidity field is generated according to the synergistic effect of humidity and rainfall / snow amount in the ice condensation process. At the same time, the three-dimensional meteorological field is reconstructed in combination with real-time freezing point data and ice thickness data, thereby achieving accurate reproduction of the ice condensation mechanism and being able to output accurate ice condensation data of all monitored areas at the high-altitude tunnel entrance in real time, providing data support for subsequent further processing.

[0062] In an embodiment of the present invention, generating disaster monitoring results based on the reconstructed meteorological field includes: determining the overwind speed area and underwind speed area of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the wind speed field; determining the low temperature duration and temperature difference range of each area of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the temperature field; determining the humidity change information of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the temperature field, the ice layer thickness data and the three-dimensional distribution cloud map of the humidity field; generating disaster monitoring results based on the overwind speed area, the underwind speed area, the low temperature duration, the temperature difference range, and the humidity change information.

[0063] In one possible implementation, the over-wind speed area and under-wind speed area of the high-altitude tunnel entrance are determined based on the three-dimensional distribution cloud map of the wind speed field. Based on the above-mentioned over-wind speed area and under-wind speed area, the shaded side wall of the high-altitude tunnel entrance, low-lying areas on the road surface and other areas can be determined, and the high-risk areas for ice condensation can be further identified; the low temperature duration and temperature difference range of each area of the high-altitude tunnel entrance are determined based on the three-dimensional distribution cloud map of the temperature field, so that the "black ice" risk area of the high-altitude tunnel entrance can be analyzed, and the high-risk areas for ice condensation can be further determined therein; the humidity change information of the high-altitude tunnel entrance is determined based on the three-dimensional distribution cloud map of the temperature field, the ice layer thickness data and the three-dimensional distribution cloud map of the humidity field, and the degree of its influence on the ice condensation process is further evaluated. Finally, disaster monitoring results are generated based on the above information.

[0064] For example, a disaster threshold model is created to assess the disaster level of high-altitude tunnel entrances. For example, an Icing Risk Index (IRI or IRI') is defined as follows:

[0065]

[0066]

[0067] Among them, T freezing point is the dynamic freezing point temperature after correcting the air pressure. is the weighting factor, RH is the relative humidity, P is the current air pressure, and P0 is the standard sea level pressure. P / P0 describes how close the air is to saturation. A larger P / P0 value indicates closer to saturation and a higher icing risk. P0 / P describes the effect of air pressure on saturation vapor pressure. At higher altitudes, where air pressure is lower (P decreases), a larger P0 / P ratio may increase the icing risk.

[0068] Based on the above-mentioned monitored data and analysis results, IRI can accurately assess the current ice condensation level at the high-altitude tunnel entrance, so that technical personnel can make subsequent prevention and control work arrangements.

[0069] In an embodiment of the present invention, the method further includes: after obtaining the disaster monitoring results, generating preliminary icing prediction information for the high-altitude tunnel entrance based on the low temperature duration, the temperature difference range, and the humidity change information; optimizing the preliminary icing prediction information based on the overwind speed area and the underwind speed area to generate optimized icing prediction information; obtaining the current high-altitude position and determining the temperature stratification corresponding to the high-altitude position; adjusting the optimized icing prediction information based on the temperature stratification to obtain adjusted prediction information; and outputting corresponding warning information based on the adjusted prediction information.

[0070] In one possible implementation, after obtaining disaster monitoring results, preliminary ice condensation prediction information for the high-altitude tunnel entrance is further generated based on the low-temperature duration, the temperature difference range, and the humidity change information. Specifically, the ice condensation situation at the high-altitude tunnel entrance is first predicted based on the basic environmental data of the high-altitude tunnel entrance to generate preliminary ice condensation prediction information. This preliminary ice condensation prediction information is then optimized based on the excessive wind speed region and the insufficient wind speed region to generate optimized ice condensation prediction information. Specifically, excessive wind speed regions significantly increase convection between the surface of objects and the air, accelerating cooling and ice formation, resulting in a stronger ice condensation effect in these regions than in normal wind speed regions. In insufficient wind speed regions, moisture is enriched, and the synergistic effect of moisture and low temperature increases the ice formation effect, leading to an enhanced ice condensation effect.

[0071] In the actual application process, due to the high altitude of the tunnel entrance, which is in a relatively high environment. Different from the ordinary environment, the high altitude area may be in a specific temperature stratification (such as an inversion layer), which leads to the formation of additional freezing rain and further exacerbates the rapid accumulation of ice (such as icing on transmission lines). Therefore, in the embodiments of the present invention, the current high altitude position is further obtained, and the corresponding temperature stratification is determined. If the current temperature stratification is an inversion layer, the optimized icing prediction information is further adjusted to obtain the adjusted prediction information. Finally, icing analysis is performed on the accurately optimized prediction information, and the corresponding warning information is output according to the analysis result. For example, in one embodiment, the prediction information is mapped to the above-mentioned icing risk index, and it is determined that the IRI of the current high altitude tunnel entrance is 0.7, which belongs to the high-risk level. Therefore, the warning information is immediately fed back, and the technical personnel are required to go to the site immediately for deicing operations to ensure traffic safety.

[0072] In the embodiments of the present invention, the mobile monitoring device further includes a microwave heating device and a mechanical deicing arm. The method further includes: after generating the warning information, determining the icing disaster-causing stage of the high altitude tunnel entrance based on the adjusted prediction information; if the icing disaster-causing stage is the prevention stage, starting the hot air circulation system of the high altitude tunnel entrance; if the icing disaster-causing stage is the warning stage, applying an ice-repellent coating at the high altitude tunnel entrance; if the icing disaster-causing stage is the high-risk stage, controlling the microwave heating device to perform directional microwave heating operations and controlling the mechanical deicing arm to perform active deicing operations.

[0073] In a possible implementation manner, different icing disaster-causing stages are defined according to the size of IRI as follows: IRI≤0.3 (safe), 0.3<IRI≤0.6 (warning), IRI>0.6 (high-risk). Therefore, in this embodiment, after generating the warning information, the icing disaster-causing stage of the high altitude tunnel entrance is determined according to the adjusted prediction information. For example, if it is found that the current high altitude tunnel entrance will reach the warning level within the next 12 hours, technical personnel are immediately dispatched to apply an ice-repellent coating (such as a fluorosilicon nanomaterial) at the high altitude tunnel entrance. If it is found that the current high altitude tunnel entrance is in the high-risk stage, the mobile monitoring device is immediately controlled to go to the corresponding area, and the microwave heating device is used to perform directional microwave heating operations to perform directional microwave removal of the ice in a specific area. At the same time, the mechanical deicing arm is controlled to perform active collaborative deicing operations to effectively improve the deicing efficiency and deicing effect and ensure the traffic safety of the high altitude tunnel entrance.

[0074] Please refer to Figure 2 , based on the same inventive concept, the embodiments of the present invention provide an icing disaster monitoring device for a high altitude tunnel entrance, which is applied to the method described in the embodiments of the present invention. The device includes:

[0075] A parameter determination unit for determining ice condensation-related parameters at high-altitude tunnel portals;

[0076] An analysis unit, configured to analyze the ice condensation related parameters and determine the ice condensation core parameters;

[0077] A data acquisition unit is configured to deploy a mobile monitoring device at a high-altitude tunnel entrance, and obtain real-time monitoring data of the high-altitude tunnel entrance based on the ice core parameters using the mobile monitoring device;

[0078] A meteorological field reconstruction unit, configured to perform a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field;

[0079] A monitoring unit is used to generate disaster monitoring results based on the reconstructed meteorological field.

[0080] Furthermore, an embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which implements the method described in the embodiment of the present invention when the program is executed by a processor.

[0081] The above describes in detail the optional implementation methods of the embodiments of the present invention in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above implementation methods. Within the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the scope of protection of the embodiments of the present invention.

[0082] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0083] Those skilled in the art will understand that all or part of the steps in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a program. The program is stored in a storage medium and includes a number of instructions for causing a single-chip microcomputer, chip, or processor to execute all or part of the steps in the methods described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0084] In addition, various implementations of the embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A method for monitoring ice condensation hazards at high-altitude tunnel entrances, characterized in that: The method comprises: Determine ice condensation-related parameters at high-altitude tunnel portals; Analyzing the ice condensation related parameters to determine the ice condensation core parameters; Deploying a mobile monitoring device at a high-altitude tunnel entrance, and obtaining real-time monitoring data of the high-altitude tunnel entrance based on the ice core parameters by the mobile monitoring device; Performing a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field; generating disaster monitoring results based on the reconstructed meteorological field; The analyzing the ice condensation related parameters to determine the ice condensation core parameters includes: Establish an ice condensation analysis model; performing a single parameter test and a coupling effect test on the ice condensation-related parameters based on the ice condensation analysis model to obtain a first test result; determining preliminary core parameters based on the first test results; Performing a simulated field test based on the preliminary core parameters to obtain a second test result; determining ice core parameters based on the second test result; The obtaining of real-time monitoring data of the high-altitude tunnel entrance includes: Determining the contribution rate of each parameter in the ice condensation core parameters; Acquire current real-time monitoring data, analyze the ice formation rate at the high-altitude tunnel entrance according to the current real-time monitoring data and the contribution rate, and generate an ice formation rate analysis result; Acquiring an initial monitoring frequency, and adjusting the initial monitoring frequency in real time based on the ice condensation velocity analysis result to obtain an adjusted monitoring frequency; Acquire real-time monitoring data of the high-altitude tunnel entrance based on the adjusted monitoring frequency; The real-time monitoring data includes temperature data, humidity data, wind speed data, air pressure data, wind direction data, light intensity data, rainfall / snowfall data, and ice thickness data. The performing of a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field includes: Performing a preprocessing operation on the real-time monitoring data to obtain preprocessed data; Generate a three-dimensional distribution cloud map of the wind speed field based on the pre-processed wind speed data and wind direction data; Generate a three-dimensional temperature field distribution cloud map based on the pre-processed temperature data and light intensity data; Generate a three-dimensional humidity distribution cloud map based on the pre-processed humidity data and rainfall / snowfall data; obtaining a pollutant concentration, and determining real-time freezing point data based on the pollutant concentration and preprocessed air pressure data; A reconstructed meteorological field is generated based on the three-dimensional temperature field distribution cloud map, the three-dimensional humidity field distribution cloud map, the three-dimensional wind speed field distribution cloud map, the preprocessed real-time freezing point data, and the preprocessed ice thickness data.

2. The method according to claim 1, characterized in that The method further comprises: Before deploying the mobile monitoring device, obtaining environmental data of the high-altitude tunnel entrance; Determining limit data based on the environmental data and a preset safety threshold, and obtaining parameter accuracy corresponding to the ice condensation core parameter; Determining an initial configuration plan for the mobile monitoring device, the initial configuration plan including sensor configuration data, sensor configuration location, physical strength design information, and internal environment maintenance information; Adjusting the sensor configuration data based on the limit data and the parameter accuracy to obtain an adjusted sensor; Acquiring environmental requirement information of the adjusted sensor, optimizing the internal environment maintenance information based on the environmental requirement information, and obtaining optimized environment maintenance information; Adjusting the sensor configuration position based on the optimized environment maintenance information to obtain an adjusted position; Optimizing the physical strength design information based on the limit data to obtain optimized strength design information; The mobile monitoring device is manufactured based on the adjusted sensor, the optimized environment maintenance information, the adjusted position, and the optimized strength design information.

3. The method according to claim 1, characterized in that Generating disaster monitoring results based on the reconstructed meteorological field includes: Determine the over-wind speed area and under-wind speed area of the high-altitude tunnel entrance based on the three-dimensional distribution cloud map of the wind speed field; Determine the low temperature duration and temperature difference range of each area of the high-altitude tunnel entrance based on the three-dimensional temperature field distribution cloud map; Determining humidity change information of the high-altitude tunnel entrance based on the temperature field three-dimensional distribution cloud map, the ice layer thickness data, and the humidity field three-dimensional distribution cloud map; A disaster monitoring result is generated based on the excessive wind speed area, the insufficient wind speed area, the low temperature duration, the temperature difference range, and the humidity change information.

4. The method according to claim 3, characterized in that The method further comprises: After obtaining the disaster monitoring result, generating preliminary ice condensation prediction information for the high-altitude tunnel entrance based on the low temperature duration, the temperature difference range, and the humidity change information; Optimizing the preliminary icing prediction information based on the overwind speed area and the underwind speed area to generate optimized icing prediction information; Obtaining a current high altitude location and determining a temperature stratification corresponding to the high altitude location; adjusting the optimized ice condensation prediction information based on the temperature stratification to obtain adjusted prediction information; Output corresponding warning information based on the adjusted forecast information.

5. The method according to claim 4, characterized in that The mobile monitoring device further includes a microwave heating device and a mechanical deicing arm, and the method further includes: After generating the warning information, determining the ice accretion disaster stage of the high-altitude tunnel entrance based on the adjusted prediction information; If the ice condensation disaster stage is a prevention stage, starting the hot air circulation system at the high-altitude tunnel entrance; If the ice condensation disaster stage is the early warning stage, an ice-repellent coating is applied to the high-altitude tunnel entrance; If the ice condensation disaster stage is a high-risk stage, the microwave heating device is controlled to perform a directional microwave heating operation, and the mechanical deicing arm is controlled to perform an active coordinated deicing operation.

6. A device for monitoring ice condensation disasters at high-altitude tunnel entrances, characterized in that: Applied to the method according to any one of claims 1 to 5, the device comprises: A parameter determination unit for determining ice condensation-related parameters at high-altitude tunnel portals; An analysis unit, configured to analyze the ice condensation related parameters and determine the ice condensation core parameters; A data acquisition unit is configured to deploy a mobile monitoring device at a high-altitude tunnel entrance, and obtain real-time monitoring data of the high-altitude tunnel entrance based on the ice core parameters using the mobile monitoring device; A meteorological field reconstruction unit, configured to perform a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field; A monitoring unit, configured to generate disaster monitoring results based on the reconstructed meteorological field; The obtaining of real-time monitoring data of the high-altitude tunnel entrance includes: Determining the contribution rate of each parameter in the ice condensation core parameters; Acquire current real-time monitoring data, analyze the ice formation rate at the high-altitude tunnel entrance according to the current real-time monitoring data and the contribution rate, and generate an ice formation rate analysis result; Acquiring an initial monitoring frequency, and adjusting the initial monitoring frequency in real time based on the ice condensation velocity analysis result to obtain an adjusted monitoring frequency; Acquire real-time monitoring data of the high-altitude tunnel entrance based on the adjusted monitoring frequency; The real-time monitoring data includes temperature data, humidity data, wind speed data, air pressure data, wind direction data, light intensity data, rainfall / snowfall data, and ice thickness data. The performing of a three-dimensional meteorological field reconstruction operation based on the real-time monitoring data to generate a reconstructed meteorological field includes: Performing a preprocessing operation on the real-time monitoring data to obtain preprocessed data; Generate a three-dimensional distribution cloud map of the wind speed field based on the pre-processed wind speed data and wind direction data; Generate a three-dimensional temperature field distribution cloud map based on the pre-processed temperature data and light intensity data; Generate a three-dimensional humidity distribution cloud map based on the pre-processed humidity data and rainfall / snowfall data; obtaining a pollutant concentration, and determining real-time freezing point data based on the pollutant concentration and preprocessed air pressure data; A reconstructed meteorological field is generated based on the three-dimensional temperature field distribution cloud map, the three-dimensional humidity field distribution cloud map, the three-dimensional wind speed field distribution cloud map, the preprocessed real-time freezing point data, and the preprocessed ice thickness data.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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