A disaster analysis method and system for two-lane highway traffic tunnels

Abstract

The present invention discloses a disaster analysis method and system for a two-lane highway traffic tunnel, which is applied to the field of intelligent disaster prevention technology. The method includes: when a fire disaster occurs in the target tunnel, obtaining the location and temperature data of a known fire source; inputting multiple temperature data into a single fire source temperature model to calculate multiple first vault maximum temperatures, and determining whether there is an unknown fire source; inputting multiple temperature data and fire source distances into a dual fire source temperature model to calculate multiple second vault maximum temperature groups; selecting the fire source distance corresponding to the second vault maximum temperature group with the smallest standard deviation as the predicted fire source distance and calibrating the location of the unknown fire source. Through the above technical solution, the present invention can determine the spread of a fire while relying solely on temperature sensors, thereby clarifying the possible risks of the fire point and the direction of the fire spread, thereby providing strong support for subsequent firefighting operations.

Description

Technical Field

[0001] The present invention relates to the field of intelligent disaster prevention technology, and in particular to a disaster analysis method and system for a dual-lane highway traffic tunnel. Background Art

[0002] Because highway tunnels are long, narrow, and enclosed, fires can easily spread rapidly along the tunnel's length. However, when a vehicle catches fire inside a tunnel, as flames and smoke rise, cameras deployed within the tunnel lose their ability to detect the fire's origin. The unknown origin and source of the fire significantly impact subsequent firefighting operations. Therefore, a solution is needed to quickly and easily detect the source of fires in highway tunnels.

[0003] In the prior art, Chinese patent application number 202410334910.7 discloses a binocular vision-based method for locating the source of a tunnel fire. This method, which belongs to the field of fire source location, includes: installing a binocular camera inside the tunnel, visually aligning the binocular camera based on the tunnel environment, and then capturing images to obtain tunnel image data; performing image correction and normalization on the tunnel image data to obtain a processed data set; constructing a convolutional neural network model to obtain fire source feature points; and mapping the fire source feature points into a three-dimensional coordinate system based on the binocular camera parameters to obtain the fire source coordinates. However, it is obvious that this method is difficult to locate the fire point in the presence of smoke interference. Summary of the Invention

[0004] In order to at least overcome the above-mentioned deficiencies in the prior art, the present application aims to provide a method and system for analyzing disasters in a two-lane highway traffic tunnel.

[0005] In a first aspect, the present application provides a two-lane highway traffic tunnel disaster analysis method, comprising:

[0006] When a fire disaster occurs in the target tunnel, the location of the known fire source and the temperature data detected by multiple temperature sensors arranged longitudinally in the tunnel are obtained;

[0007] Inputting the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and determining that an unknown fire source exists when a standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data;

[0008] Randomly selecting a plurality of possible fire source distances, and inputting the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in the second dome maximum temperature group corresponds to a temperature data;

[0009] Calculating the standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and selecting the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance;

[0010] The position of the unknown fire source is calibrated according to the predicted fire source distance and the position of the known fire source.

[0011] Furthermore, both the single fire source temperature model and the dual fire source temperature model adopt a double exponential fitting model:

[0012] ;

[0013] ;

[0014] Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the dome, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted.

[0015] Furthermore, the generation of the single fire source temperature model includes:

[0016] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0017] Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations;

[0018] The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

[0019] Furthermore, the generation of the dual fire source temperature model includes converting the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula:

[0020] ;

[0021] ;

[0022] ;

[0023] ;

[0024] Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source;

[0025] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0026] Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances;

[0027] The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

[0028] Furthermore, calibrating the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source includes:

[0029] Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance;

[0030] The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source;

[0031] The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

[0032] In a second aspect, the present application also provides a two-lane highway traffic tunnel disaster analysis system, comprising:

[0033] an acquisition unit configured to acquire, when a fire disaster occurs in a target tunnel, a location of a known fire source and temperature data detected by a plurality of temperature sensors arranged longitudinally in the tunnel;

[0034] a calculation unit configured to input the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and to determine the presence of an unknown fire source when a standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data;

[0035] The random unit is configured to randomly select a plurality of possible fire source distances, and input the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in the second dome maximum temperature group corresponds to a temperature data;

[0036] a calculation unit configured to calculate a standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and select the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance;

[0037] The calibration unit is configured to calibrate the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source.

[0038] In a possible implementation, both the single fire source temperature model and the dual fire source temperature model adopt a double exponential fitting model:

[0039] ;

[0040] ;

[0041] Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the dome, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted.

[0042] Furthermore, the method further comprises a first fitting unit configured to generate the single fire source temperature model;

[0043] The first fitting unit is further configured to:

[0044] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0045] Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations;

[0046] The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

[0047] Furthermore, it also includes a second fitting unit configured to generate the dual-fire source temperature model;

[0048] The second fitting unit is further configured to convert the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula:

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source;

[0054] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0055] Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances;

[0056] The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

[0057] Furthermore, the calibration unit is further configured to:

[0058] Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance;

[0059] The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source;

[0060] The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] The present invention provides a two-lane highway traffic tunnel disaster analysis method and system. Through the above-mentioned technical solution, it is possible to judge the spread of fire by relying solely on temperature sensors, thereby clarifying the possible risks of the fire point and the spread direction of the fire point, thereby providing strong support for subsequent fire fighting operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0064] Figure 1 This is a schematic diagram of the steps of the method according to the embodiment of the present application;

[0065] Figure 2 This is a schematic diagram of a simulation model according to an embodiment of the present application;

[0066] Figure 3 This is a schematic diagram of the fitting curve of the dual fire source temperature model in the embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of illustration and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of the embodiments of the present application. It should be understood that the operations of the flowcharts can be implemented out of sequence, and steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art, under the guidance of the contents of this application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0068] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0069] Please refer to Figure 1 , which is a flow chart of a two-lane highway traffic tunnel disaster analysis method provided by an embodiment of the present invention. Furthermore, the two-lane highway traffic tunnel disaster analysis method may specifically include the contents described in the following steps S1 to S5.

[0070] S1: When a fire disaster occurs in the target tunnel, the location of the known fire source and the temperature data detected by multiple temperature sensors arranged longitudinally in the tunnel are obtained;

[0071] S2: Inputting the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and determining that an unknown fire source exists when the standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data;

[0072] S3: randomly selecting a plurality of possible fire source distances, and inputting the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in a second dome maximum temperature group corresponds to a temperature data;

[0073] S4: calculating the standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and selecting the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance;

[0074] S5: Calibrate the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source.

[0075] During implementation of the embodiments of the present application, when a fire occurs in a target tunnel, typically caused by a vehicle fire, such as a spontaneous combustion or traffic accident, the fire is likely caused by a vehicle fire. As smoke is generated and begins to spread within the tunnel, the temperature sensors within the tunnel will detect a temperature rise, at which point the fire point can be located. It should be understood that temperature sensors within the tunnel are typically located at the tunnel's vault and spaced longitudinally along the tunnel. In the early stages of a fire, it is typically a single-point fire, and its source can be identified using cameras or other means, i.e., a known fire source.

[0076] In the embodiments of the present application, a preset single-fire source temperature model can be used to calculate the maximum temperature that can be generated at the tunnel vault under a single-point fire source. Generally speaking, the location corresponding to the maximum temperature is the location of the single-point fire source. However, if the tunnel is not a single-point fire source, the maximum vault temperature calculated by different temperature sensors will vary. This is because the tunnel environment is relatively closed and the total amount of oxygen is relatively limited. Therefore, in the case of a single-point fire source, the combustion rate and flame height will be significantly increased, resulting in the vault temperature of a tunnel with a single fire source being much higher than that under multiple fire sources. Therefore, when the actual situation is not a single fire source, the temperature data detected at different locations will show significant differences in the first vault maximum temperature calculated using the single-fire source temperature model. Therefore, in the embodiments of the present application, the standard deviation of multiple first vault maximum temperatures can be used to assess the dispersion of these first vault maximum temperatures. If the data is relatively discrete, it indicates that the result calculated by the single-fire source temperature model is inaccurate, and the actual situation is no longer a single fire source.

[0077] In an embodiment of the present application, when there is a second fire source, it is necessary to first randomly select multiple possible fire source distances. The fire source distance here is the distance between the center point of the known fire source and the possible unknown fire source; it is generally selected based on the possible vehicle situation. At this time, it is necessary to form multiple groups of working conditions, each group of working conditions corresponds to a fire source distance, and the arch maximum temperature is calculated for each group of working conditions through multiple temperature data and a dual fire source temperature model, which will form multiple second arch maximum temperatures, each second arch maximum temperature corresponding to a fire source distance and a temperature data; the second arch maximum temperatures corresponding to the same fire source distance are formed into a set, which is the second arch maximum temperature group. At this time, the standard deviation within each second arch maximum temperature group is calculated, and the fire source distance corresponding to the second arch maximum temperature group with the smallest standard deviation is the predicted fire source distance closest to the actual situation. According to the predicted fire source distance, the position of the unknown fire source can be accurately estimated. The embodiment of the present application can estimate the location of an unknown fire source only through the temperature data detected by the temperature sensor, providing a basis for subsequent fire-fighting operations. The fire-fighting operation can determine the working mode of the fire-fighting sprinkler equipment in the tunnel according to the location of all fire sources, effectively utilizing limited on-site fire-fighting resources. It can determine what type of vehicle and cargo is on fire based on the location of the fire source, and then further use foam and other fire-extinguishing agents for spraying at the correct location.

[0078] In a possible implementation, both the single fire source temperature model and the dual fire source temperature model adopt a double exponential fitting model:

[0079] ;

[0080] ;

[0081] Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the dome, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted.

[0082] When the embodiment of the present application is implemented, both the single fire source temperature model and the dual fire source temperature model are fitted using a double exponential fitting model. It should be understood that both the single fire source temperature model and the dual fire source temperature model need to be fitted when the tunnel is in operation, so as to be prepared for use in various fire conditions. For example, when a fire occurs in a tunnel, a plurality of temperature sensors are arranged in the tunnel at a longitudinal interval of 5m. When a fire occurs, 10 temperature sensors detect temperature changes, and the temperature data detected are T1, T2, T3...T10, and the coordinates corresponding to the temperature sensors are x1, x2, x3...x10; at this time, the temperature sensor whose temperature has not changed is selected as the reference point, and the acquired data is input into the above model, and the maximum temperature of the arch corresponding to different temperature data can be obtained. For the single fire source temperature model, the output is the maximum temperature of the first arch, and for the dual fire source temperature model, the output is the maximum temperature of the second arch.

[0083] In one possible implementation, generating the single fire source temperature model includes:

[0084] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0085] Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations;

[0086] The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

[0087] When the embodiment of the present application is implemented, when the construction of the target tunnel is completed and the operation begins, it is necessary to first build a simulation model of the corresponding target tunnel. For its relevant arrangement, please refer to Figure 2 The dimensions of the simulation model must match the tunnel parameters, which include the shape and dimensions of the tunnel section and the tunnel's orientation. The simulation model is then assigned values ​​using environmental parameters, which include atmospheric pressure, air density, and portal boundary conditions. By performing simulation calculations on the simulation model, we can obtain the maximum vault temperature under different working conditions, the temperatures detected by sensors at different locations, and the sensor placement. This allows us to fit the aforementioned double exponential fitting model, calculate the first parameter to be fitted, and thus form a single fire source temperature model.

[0088] In one possible implementation, generating the dual-fire source temperature model includes converting the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula:

[0089] ;

[0090] ;

[0091] ;

[0092] ;

[0093] Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source;

[0094] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0095] Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances;

[0096] The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

[0097] When implementing the embodiment of the present application, the difference between the dual fire source temperature model and the single fire source temperature model is that the distance between the two fire sources needs to be considered. In this embodiment of the present application, the first parameters to be fitted are all converted into functions whose independent variables are the fire source distances. Although this will increase the number of parameters that need to be fitted, it will be closer to the situation of dual fire source combustion. Similar to the fitting of the single fire source temperature model, the same simulation model can be used for calculation, and two fire points can be set up in the tunnel for simulation. The calculated maximum vault temperature data can be used for parameter fitting calculation of the double exponential fitting model to generate the second parameters to be fitted to complete the fitting.

[0098] For example, during the simulation, two identical fire sources were used, each with a power of 5 MW. The fire sources were simplified to rectangular obstacles measuring 4 m × 2 m × 1.5 m. The center of the line connecting the two fire sources was located in the middle of the tunnel. The fire source distance was variable and set according to different operating conditions. The fire source fuel was set to propane (C3H8), unsteady-state combustion was adopted, the fire source power growth curve was set to the t² curve, and the fire growth coefficient was 0.1876 kW / s². The curves corresponding to different fire source distances are calculated. Figure 3 ,from Figure 3 It can be seen that it is consistent with the exponential function, so it is more reasonable to fit the double exponential function with the fire source position as the center. The double fire source temperature model after data fitting adopts the following formula:

[0099] .

[0100] In one possible implementation, calibrating the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source includes:

[0101] Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance;

[0102] The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source;

[0103] The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

[0104] When implementing the embodiment of the present application, a solution is also provided for locating an unknown fire source when the distance to the fire source is known. For the combustion of two fire sources, the highest dome temperature is generally located at the center of the two fire sources. For this reason, it is necessary to first estimate the approximate highest temperature of the second dome, that is, to predict the highest temperature. In the embodiment of the present application, the average value of the highest temperature of the second dome in the selected highest temperature group is used. In this case, in the double exponential fitting model, if T x Directly select T max If , then the solved x is the center point position of the two fire sources. At this time, one side of the solved center point is the position of the known fire source, and the symmetrical position on the other side is the unknown fire source. In this way, the directionless predicted fire source distance can be changed to a directional distance, thereby locating the position of the unknown fire source.

[0105] Based on the same inventive concept, the present application also provides a two-lane highway traffic tunnel disaster analysis system, comprising:

[0106] an acquisition unit configured to acquire, when a fire disaster occurs in a target tunnel, a location of a known fire source and temperature data detected by a plurality of temperature sensors arranged longitudinally in the tunnel;

[0107] a calculation unit configured to input the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and to determine the presence of an unknown fire source when a standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data;

[0108] The random unit is configured to randomly select a plurality of possible fire source distances, and input the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in the second dome maximum temperature group corresponds to a temperature data;

[0109] a calculation unit configured to calculate a standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and select the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance;

[0110] The calibration unit is configured to calibrate the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source.

[0111] In a possible implementation, both the single fire source temperature model and the dual fire source temperature model adopt a double exponential fitting model:

[0112] ;

[0113] ;

[0114] Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the dome, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted.

[0115] In a possible implementation, the method further includes a first fitting unit configured to generate the single fire source temperature model;

[0116] The first fitting unit is further configured to:

[0117] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0118] Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations;

[0119] The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

[0120] In a possible implementation, the method further includes a second fitting unit configured to generate the dual-fire source temperature model;

[0121] The second fitting unit is further configured to convert the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula:

[0122] ;

[0123] ;

[0124] ;

[0125] ;

[0126] Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source;

[0127] Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters;

[0128] Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances;

[0129] The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

[0130] In a possible implementation, the calibration unit is further configured to:

[0131] Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance;

[0132] The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source;

[0133] The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

[0134] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0136] The units described as separate components may or may not be physically separated. As units, it is obvious that a person of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0137] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0138] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or grid device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. 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.

[0139] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for analyzing disasters in a two-lane highway tunnel, characterized in that: include: When a fire disaster occurs in the target tunnel, the location of the known fire source and the temperature data detected by multiple temperature sensors arranged longitudinally in the tunnel are obtained; Inputting the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and determining that an unknown fire source exists when a standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data; Randomly selecting a plurality of possible fire source distances, and inputting the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in the second dome maximum temperature group corresponds to a temperature data; Calculating the standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and selecting the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance; calibrating the position of the unknown fire source based on the predicted fire source distance and the position of the known fire source; The single fire source temperature model and the dual fire source temperature model both adopt a double exponential fitting model: ； ； Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the vault, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted; The generation of the dual fire source temperature model includes converting the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula: ； ； ； ； Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source; Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters; Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances; The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

2. A two-lane highway traffic tunnel disaster analysis method according to claim 1, characterized in that: The generation of the single fire source temperature model includes: Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters; Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations; The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

3. A two-lane highway traffic tunnel disaster analysis method according to claim 1, characterized in that: Calibrating the position of the unknown fire source according to the predicted fire source distance and the position of the known fire source includes: Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance; The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source; The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

4. A two-lane highway traffic tunnel disaster analysis system, characterized in that: include: an acquisition unit configured to acquire, when a fire disaster occurs in a target tunnel, a location of a known fire source and temperature data detected by a plurality of temperature sensors arranged longitudinally in the tunnel; a calculation unit configured to input the plurality of temperature data into a preset single fire source temperature model to calculate a plurality of first dome maximum temperatures, and to determine the presence of an unknown fire source when a standard deviation of the plurality of first dome maximum temperatures is greater than a preset value; each first dome maximum temperature corresponds to one temperature data; The random unit is configured to randomly select a plurality of possible fire source distances, and input the plurality of temperature data and the fire source distances into a preset dual fire source temperature model to calculate a plurality of second dome maximum temperature groups; each second dome maximum temperature group corresponds to a fire source distance, and each second dome maximum temperature in the second dome maximum temperature group corresponds to a temperature data; a calculation unit configured to calculate a standard deviation of the second dome maximum temperature in each second dome maximum temperature group, and select the fire source distance corresponding to the second dome maximum temperature group with the smallest standard deviation as the predicted fire source distance; a calibration unit configured to calibrate the position of the unknown fire source based on the predicted fire source distance and the position of the known fire source; The single fire source temperature model and the dual fire source temperature model both adopt a double exponential fitting model: ； ； Where, T x is the temperature data at coordinate x, T0 is the temperature data at reference point x0, T max is the maximum temperature of the vault, h is the tunnel height, A1, A2, t1 and t2 are the first parameters to be fitted; Also included is a second fitting unit configured to generate the dual-fire source temperature model; The second fitting unit is further configured to convert the first parameter to be fitted into a function whose independent variable is the fire source distance according to the following formula: ； ； ； ； Wherein, B1, B2, B3, B4, C1, C2, C3, C4, C5 and C6 are the second parameters to be fitted, S is the distance from the fire source, and D is the size of the fire source; Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters; Assigning values ​​to the simulation model using the environmental parameters, and setting two fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations at different fire source distances; The second parameter to be fitted is obtained by fitting the double exponential fitting model after converting the fitting parameters using the simulated temperature data.

5. A two-lane highway traffic tunnel disaster analysis system according to claim 4, characterized in that: It also includes a first fitting unit configured to generate the single fire source temperature model; The first fitting unit is further configured to: Acquiring tunnel parameters and environmental parameters of the target tunnel, and constructing a simulation model according to the tunnel parameters; Assigning values ​​to the simulation model using the environmental parameters, and arranging fire points in the simulation model to perform simulation calculations to obtain simulation temperature data at different locations; The first parameter to be fitted is obtained by fitting the double exponential fitting model using the simulated temperature data.

6. A two-lane highway traffic tunnel disaster analysis system according to claim 4, characterized in that: The calibration unit is further configured to: Calculating an average value of all second dome maximum temperatures in a selected maximum temperature group as a predicted maximum temperature; the selected maximum temperature group is the second dome maximum temperature group corresponding to the predicted fire source distance; The predicted maximum temperature is also used as T max and T x , and solve for T x The corresponding coordinate x is used as the center point coordinate; the center point coordinate is the center point between the known fire source and the unknown fire source; The position of the unknown fire source is calibrated according to the center point coordinates and the predicted fire source distance.

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