A fire extinguishing bomb delivery compensation method and system

Abstract

The present invention discloses a method and system for compensating the placement of fire-extinguishing bombs, including: S1: collecting wind direction data, wind speed data and temperature data of the fire-extinguishing bomb environment through multiple sensors; S2: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data; S3: inputting the preprocessed data into meteorological simulation software to generate terrain factors in real time; S4: inputting the preprocessed data into meteorological simulation software to generate geothermal airflow disturbance factors in real time; S5: inputting the preprocessed data, terrain factors and thermal airflow disturbance factors into Wind-Compensation algorithm to calculate compensation strategies; S6: adjusting the flight angle of the fire-extinguishing bomb in real time according to the compensation strategies calculated by the Wind-Compensation algorithm. By real-time collection and preprocessing of environmental data, combined with terrain factors and thermal airflow disturbance factors generated by meteorological simulation software, the present invention can accurately compensate for the flight path of the fire-extinguishing bomb in a complex environment, thereby improving the accuracy and efficiency of fire extinguishing.

Description

Technical Field

[0001] The invention relates to the technical field of fire extinguishing bomb delivery compensation, and in particular to a fire extinguishing bomb delivery compensation method and system. Background Art

[0002] During the release of fire-extinguishing bombs, complex environmental factors have a significant impact on the flight path and fire-fighting effect of the fire-extinguishing bombs. Traditional release methods usually ignore the combined impact of terrain and fire thermal airflow on the wind field. Topographic features (such as mountains, hills, valleys, etc.) will significantly change the local wind speed and direction, and the thermal airflow generated by the fire will form updrafts and turbulence, further disturbing the flight path of the fire-extinguishing bombs. These factors make it difficult for strategies that rely solely on wind factors for compensation to cope with complex actual situations. In actual flight, even a small change in wind direction or a sudden thermal airflow disturbance may cause the fire-extinguishing bomb to deviate from the intended target, thereby affecting the efficiency and safety of fire extinguishing. Since a single fire-extinguishing bomb is relatively expensive, taking a 500-kilogram fire-extinguishing bomb as an example, the explosion point is set 15 meters above the fire scene, and the effective coverage area is about 200 square meters. If it is affected by the thermal air flow outside the fire scene, it will cause deviations, seriously affecting the effective coverage area, and then affecting the fire-fighting effect and the strategy of deploying fire-extinguishing bombs; therefore, it is necessary to adopt a more accurate compensation strategy, which is not only based on real-time wind direction, wind speed and temperature data, but also combines terrain factors and thermal air flow disturbance factors to dynamically adjust the flight angle of the fire-extinguishing bomb to cope with changing environmental conditions and improve the accuracy and efficiency of fire-fighting. Summary of the invention

[0003] In view of this, the present invention provides a fire extinguishing bomb delivery compensation method and system, the purpose of which is to use data processing and machine learning technology to comprehensively consider environmental factors such as wind direction, wind speed, temperature, terrain and thermal air flow, so as to improve the accuracy and effectiveness of fire extinguishing under complex and changeable environmental conditions.

[0004] To achieve the above object, the present invention provides a fire extinguishing bomb delivery compensation method and system, comprising the following steps:

[0005] S1: Collect wind direction data, wind speed data and temperature data of the fire bomb environment through multiple sensors;

[0006] S2: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data;

[0007] S3: input the preprocessed data into the meteorological simulation software to generate terrain factors in real time;

[0008] S4: input the preprocessed data into the meteorological simulation software to generate geothermal airflow disturbance factors in real time;

[0009] S5: inputting the preprocessed data, terrain factors and thermal airflow disturbance factors into a Wind-Compensation algorithm to calculate a compensation strategy;

[0010] S6: According to the compensation strategy calculated by the Wind-Compensation algorithm, the flight angle of the fire extinguishing bomb is adjusted in real time.

[0011] As a further improvement method of the present invention:

[0012] Optionally, in step S1, collecting wind direction data, wind speed data and temperature data of the fire extinguishing bomb environment through multiple sensors includes:

[0013] The wind direction sensor monitors and records changes in wind direction in real time. These data provide wind direction information, which is crucial for adjusting the release angle of the fire-extinguishing bomb. The wind speed sensor captures and records the current wind speed in real time. The rapid change of wind speed directly affects the flight trajectory of the fire-extinguishing bomb and is an indispensable input parameter for the calculation of the compensation strategy. The temperature sensor continuously monitors the ambient temperature. Temperature changes may affect the stability of wind speed and wind direction. Therefore, temperature data also has an important impact on the flight trajectory and compensation strategy of the fire-extinguishing bomb.

[0014] Step S1 provides the necessary environmental analysis for the compensation strategy by collecting wind direction, wind speed and temperature data in real time. This integrated sensor data not only enhances the system's adaptability to complex meteorological conditions, but also enables it to respond to environmental changes instantly, thereby significantly improving the accuracy and efficiency of fire extinguishing bomb delivery.

[0015] Optionally, in step S2, preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data includes:

[0016] S21: wind direction data O 1 Perform sine-cosine encoding to obtain sine-encoded wind direction data O 1,s Sum and cosine coded wind direction data O 1,c , specifically:

[0017] ;

[0018] Wind direction data from wind direction sensor 1 It is expressed in degrees. When performing sine-cosine encoding, the angle data must first be converted into radian data before performing sine-cosine encoding.

[0019] S22: The wind speed data O 2 and temperature data 3 Perform Min-Max normalization to obtain wind speed data O 2 ' and temperature data O 3 ';

[0020] The sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c , wind speed data 2' and temperature data 3' Constitute the preprocessed data.

[0021] The preprocessing method in step S2 not only optimizes the data format to make it more suitable for the input of the machine learning model, but also retains the periodic characteristics of wind direction, ensuring the effective integration of various environmental data in the algorithm.

[0022] Optionally, in step S3, the preprocessed data is input into a meteorological simulation software to generate terrain factors in real time, including:

[0023] S31: Input the pre-processed data into the meteorological simulation software and generate the simulated wind speed data V of the wind field in combination with the terrain data d,terrain and simulated wind direction data θ d,terrain ;

[0024] S32: simulate wind direction data θ d,terrain Perform sine and cosine encoding to obtain the simulated wind direction sinusoidal encoding data θ d,terrain,s and simulated wind direction cosine coded data θ d,terrain,c , specifically:

[0025] ;

[0026] Wind direction dataθ d,terrain It is an angle value. Directly using the angle for calculation may cause periodic errors. In order to accurately reflect the change of wind direction, wind direction data is usually processed through sine and cosine encoding;

[0027] S33: According to the simulated wind speed data V d,terrain , simulated wind direction sinusoidal encoding data θ d,terrain,s , simulated wind direction cosine encoding data θ d,terrain,c , sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c and wind speed data 2 ', calculate the terrain factor α, specifically: .

[0028] The terrain factor α provides a comprehensive measure that describes the overall perturbation effect of terrain on the local wind field. It is calculated by taking the relative differences of the following three components and taking the square root of the sum of the squares of these differences: The simulated wind speed V affected by terrain d,terrain With the preprocessed wind speed data O 2 'The relative difference between the simulated wind direction sinusoidal coded data θd,terrain,s The preprocessed wind direction sinusoidal coded data O 1,s The relative difference between the simulated wind direction cosine coded data θ d,terrain,c and the preprocessed wind direction cosine coded data O 1,c The relative difference between

[0029] Step S3 accurately reflects the regulating effect of terrain (such as mountains, valleys, hills, etc.) on wind speed and direction. Under complex terrain conditions, the terrain factor α is generated by using meteorological simulation software combined with terrain data, which can capture the changes in the local wind field and reflect the interference and guiding effect of terrain characteristics on air flow.

[0030] Optionally, in step S4, the preprocessed data is input into a meteorological simulation software to generate a geothermal airflow disturbance factor in real time, including:

[0031] S41: Input the preprocessed data into the meteorological simulation software, and input the fuel type of the fire scene, combine the terrain data to simulate the hot air flow generated by the fire scene and its influence on temperature and wind speed, and generate simulated temperature data T d,fire and simulated wind speed data V d,fire ;

[0032] S42: According to the simulated temperature data T d,fire , simulated wind speed data V d,fire , Temperature data 3 ' and wind speed data O 2 ', calculate the thermal air flow disturbance factor β, specifically:

[0033] .

[0034] Step S4 comprehensively simulates the disturbance of the fire scene thermal airflow on the environment. The meteorological simulation software is used to combine the fire scene parameters and terrain data to generate the thermal airflow disturbance factor β, which can comprehensively simulate the impact of the fire scene thermal airflow on the environment. This simulation can accurately reflect the changes in the surrounding meteorological conditions caused by the rising airflow and turbulence generated by the fire scene.

[0035] Optionally, in step S5, the pre-processed data, terrain factor α and thermal airflow disturbance factor β are input into a Wind-Compensation algorithm to calculate a compensation strategy, including:

[0036] S51: Set the parameters of the Wind-Compensation algorithm, including the number of trees, the maximum depth of each tree, the minimum number of node split samples, and the random seed;

[0037] This step can balance model performance and computational cost by setting an appropriate number of trees; setting an appropriate maximum depth helps improve the generalization ability of the model; setting an appropriate minimum number of node split samples effectively reduces the overfitting phenomenon of the model and improves training efficiency; setting a random seed ensures that the results of each model training are consistent and enhances the repeatability of the model;

[0038] S52: After completing the parameter setting, initialize the Wind-Compensation algorithm;

[0039] This step is initialized after setting the parameters, which can optimize the algorithm's computational efficiency and avoid unnecessary repeated adjustments.

[0040] S53: Based on the preprocessed data, terrain factor α and thermal disturbance factor β, a training data set is constructed, the mean square error MSE of the Wind-Compensation algorithm is calculated, and a feedback adjustment mechanism and its stop condition are established;

[0041] S54: Calculate the wind direction compensation strategy when the Wind-Compensation algorithm stops, specifically:

[0042] ;

[0043] Mapping function obtained by training the Wind-Compensation algorithm f u , used to calculate the wind direction compensation u and adjust the release angle of the fire bomb; f u They are obtained through model training, and their specific mathematical forms are data-driven, not predefined fixed formulas;

[0044] This step can dynamically adjust the delivery angle according to the real-time environment and optimize the fire extinguishing effect.

[0045] Step S5 generates a decision tree model by integrating multiple factors such as wind direction, terrain, and thermal airflow, and calculates the compensation strategy for the release of fire-extinguishing bombs. This step is highly adaptable and flexible, and can be dynamically adjusted under different environmental and weather conditions, significantly improving the accuracy and release efficiency of fire-extinguishing bombs, reducing errors caused by wind direction or terrain, and thus improving the fire-fighting effect.

[0046] Optionally, in step S53, a training data set is constructed based on the preprocessed data, the terrain factor α and the thermal airflow disturbance factor β, the mean square error MSE of the Wind-Compensation algorithm is calculated, and a feedback adjustment mechanism and its stop condition are established, including:

[0047] S531: define a threshold M for dynamically adjusting the interaction item, and obtain interaction item data N, specifically:

[0048] ;

[0049] ;

[0050] When the Wind-Compensation algorithm is run for the first time, the three-way interaction term is used by default, and then the interaction term N is selected based on the relationship between the current mean square error MSE of the Wind-Compensation algorithm and the threshold M;

[0051] If the mean square error MSE of the current Wind-Compensation algorithm exceeds 1.2 times the threshold M, it means that the model faces a large prediction error and may require a more complex model structure to handle this error, so the algorithm selects a nonlinear interaction term; if the mean square error MSE of the current Wind-Compensation algorithm is less than 1.1 times the threshold M, it means that the prediction performance of the model is within an acceptable range, so the algorithm chooses to use a binary interaction term; if the mean square error MSE of the current Wind-Compensation algorithm is between 1.1 and 1.2 times the threshold M, it means that although the model performs poorly, the error has not yet reached the most serious level, so the algorithm chooses to use a ternary interaction term;

[0052] The calculation formula of the nonlinear interaction term is: 1,s The sum of the topographic factor α is exponentially transformed, and the temperature data O 3 'The sum of the thermal flow factor β is logarithmically transformed, which is suitable for complex relationship processing under high fluctuation conditions; the binary interaction term calculation formula is cosine coded wind direction data O 1,c and sinusoidally encoded wind direction data O 1,s Respectively with wind speed data O 2 ', and then added to the terrain factor α and the thermal flow factor β respectively, which is suitable for processing the basic influence relationship between wind direction and wind speed; the calculation formula of the ternary interaction term is cosine coded wind direction data O 1,c and sinusoidally encoded wind direction data O 1,s Respectively with wind speed data O 2 ' and temperature data O 3 ' are multiplied and then added to the terrain factor α and the thermal flow factor β respectively to capture the complex interaction between wind direction, wind speed and temperature;

[0053] This step sets the MSE threshold M and dynamically selects interaction terms based on the actual MSE, so that the model can adjust its complexity according to the current prediction error, thereby improving the accuracy of the prediction; using nonlinear interaction terms when facing large prediction errors can handle more complex data patterns and outliers, thereby enhancing the robustness of the model; the use of binary and ternary interaction terms allows the model to simplify calculations when the prediction performance is good or moderate, improve computational efficiency, and maintain good prediction results.

[0054] S532: Establish a feedback adjustment mechanism to calculate the change rate MSE' of MSE in real time and adjust M according to MSE', specifically:

[0055] ;

[0056] Among them, the sign function sgn(MSE') is used to determine the positive or negative sign of MSE', which determines the increase or decrease of M. The adjustment factor 0.1 controls the adjustment amplitude of M to ensure that the adjustment amplitude is moderate and does not affect the system stability due to too fast or too slow changes. |MSE'| is the change amplitude of MSE, which is used to determine the specific amount of adjustment of M. The terrain factor α and the thermal airflow factor β are included in the adjustment formula to further refine the adjustment process of M to better adapt to environmental changes.

[0057] This step can continuously optimize the model performance, quickly respond to environmental changes, and improve response speed and accuracy by monitoring the change rate of MSE in real time and adjusting the threshold M accordingly.

[0058] S533: Set the stop condition of the feedback adjustment mechanism, repeat steps S531-S532 until MSE' is less than 0.5% and the algorithm stops when the condition is met three times in a row.

[0059] This step sets clear stopping conditions, saving computing resources while ensuring the stability and reliability of the model.

[0060] Step S53 provides a dynamic and adaptive solution for wind direction compensation of fire bomb delivery by comprehensively utilizing advanced machine learning technology and feedback mechanism. This step not only enhances the real-time response capability of the algorithm, but also ensures the maximum accuracy and efficiency of the operation through precise parameter adjustment and terminal decision support. In addition, the dynamic adjustment mechanism and optimized stop conditions of the algorithm further ensure the stability and reliability of the system in a changing environment, reduce the need for human intervention, and thus improve the safety of operation.

[0061] Optionally, in step S6, adjusting the flight angle of the fire-extinguishing bomb in real time according to the compensation strategy calculated by the Wind-Compensation algorithm includes:

[0062] Inputting the compensation strategy calculated by the Wind-Compensation algorithm into the control system of the fire-extinguishing bomb to adjust the flight angle of the fire-extinguishing bomb in real time;

[0063] Step S6 ensures that the fire extinguishing bomb can be dynamically adjusted according to the real-time environmental data.

[0064] The present invention also provides a fire extinguishing bomb delivery compensation system, comprising:

[0065] Data collection module: collects wind direction data, wind speed data and temperature data from multiple sensors in real time;

[0066] Data preprocessing module: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data;

[0067] Environmental factor generation module: inputs the preprocessed data into the meteorological simulation software to generate terrain factors and thermal disturbance factors;

[0068] Algorithm module: input the pre-processed data, terrain factors and thermal disturbance factors into the Wind-Compensation algorithm, establish a feedback adjustment mechanism, set stop conditions, and calculate compensation strategies;

[0069] Compensation module: The compensation strategy calculated by the algorithm module is input into the fire extinguishing bomb control system to adjust the flight angle of the fire extinguishing bomb in real time.

[0070] The beneficial effects of the present invention are:

[0071] The present invention provides a method and system for compensating the delivery of fire-extinguishing bombs. By collecting wind direction, wind speed and temperature data in real time, and performing preprocessing and comprehensive analysis, the present invention can adjust the flight angle of the fire-extinguishing bomb in real time during the delivery process, significantly improving the accuracy and effectiveness of fire extinguishing. The terrain factor and thermal air flow disturbance factor are generated by meteorological simulation software, and these factors are incorporated into the Wind-Compensation algorithm for calculation, which can comprehensively consider the complex and changeable environmental conditions, thereby effectively compensating for the various disturbances to which the fire-extinguishing bomb is subjected during flight. Specifically, the compensation method of the present invention not only solves the problem that the traditional delivery method ignores the influence of terrain and thermal air flow, but also can adjust the flight path in real time under complex environments, ensuring that the fire-extinguishing bomb can reach the target area more accurately, thereby improving the fire-extinguishing effect. In addition, the algorithm reduces the need for human intervention by automatically optimizing the compensation strategy, and improves the operational safety and reliability of the system. In practical applications, the method can significantly reduce the deviation of the fire-extinguishing bomb caused by wind field and thermal air flow disturbance, improve fire extinguishing efficiency and resource utilization, and is suitable for the delivery of fire-extinguishing bombs in a variety of complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 The present invention is a flowchart of a fire extinguishing bomb delivery compensation method and system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The present invention is further described below in conjunction with the accompanying drawings, but the present invention is not limited in any way. Any changes or substitutions made based on the teachings of the present invention belong to the protection scope of the present invention.

[0074] Embodiment 1: In order to achieve the above-mentioned object, the present invention provides a method and system for compensating the delivery of fire extinguishing bombs, such as Figure 1 The following steps are shown:

[0075] S1: Collect wind direction data, wind speed data and temperature data of the fire bomb environment through multiple sensors; in this embodiment, the wind direction sensor monitors and records wind direction changes in real time at a frequency of once per second. This high sampling frequency ensures that rapidly changing wind direction information can be captured. The wind speed sensor also records wind speed at a frequency of once per second to ensure that it can respond in real time and adjust the flight strategy to cope with sudden wind speed changes during flight. The temperature sensor records the temperature once a minute, which is sufficient to track the trend of ambient temperature changes, which is equally important for evaluating weather conditions and temperature fluctuations that may affect wind direction and wind speed.

[0076] S2: Preprocess the wind direction data, wind speed data and temperature data to obtain preprocessed data:

[0077] S21: wind direction data O 1 Perform sine-cosine encoding to obtain sine-encoded wind direction data O 1,s Sum and cosine coded wind direction data O 1,c , specifically:

[0078] ;

[0079] S22: The wind speed data O 2 and temperature data 3 Perform Min-Max normalization to obtain wind speed data O 2 ' and temperature data O 3 ';

[0080] The sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c , wind speed data 2' and temperature data 3' Constitute the preprocessed data.

[0081] S3: Input the preprocessed data into the meteorological simulation software to generate terrain factors in real time:

[0082] S31: Input the pre-processed data into the meteorological simulation software and generate the simulated wind speed data V of the wind field in combination with the terrain data d,terrain and simulated wind direction data θ d,terrain ; The meteorological simulation software WRF of this embodiment;

[0083] S32: simulate wind direction data θ d,terrain Perform sine and cosine encoding to obtain the simulated wind direction sinusoidal encoding data θ d,terrain,s and simulated wind direction cosine coded data θ d,terrain,c , specifically:

[0084] ;

[0085] S33: According to the simulated wind speed data V d,terrain , simulated wind direction sinusoidal encoding data θ d,terrain,s , simulated wind direction cosine encoding data θ d,terrain,c , sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c and wind speed data 2 ', calculate the terrain factor α, specifically: .

[0086] S4: Input the preprocessed data into the meteorological simulation software to generate the geothermal airflow disturbance factor in real time:

[0087] S41: Input the preprocessed data into the meteorological simulation software, and input the fuel type of the fire scene, combine the terrain data to simulate the hot air flow generated by the fire scene and its influence on temperature and wind speed, and generate simulated temperature data T d,fire and simulated wind speed data V d,fire ;The input fire fuel type in this embodiment is grass;

[0088] S42: According to the simulated temperature data T d,fire , simulated wind speed data V d,fire , Temperature data 3 ' and wind speed data O 2 ', calculate the thermal air flow disturbance factor β, specifically:

[0089] .

[0090] S5: Input the pre-processed data, terrain factor α and thermal disturbance factor β into the Wind-Compensation algorithm to calculate the compensation strategy:

[0091] S51: Set the parameters of the Wind-Compensation algorithm, including the number of trees, the maximum depth of each tree, the minimum number of node split samples, and the random seed; the number of trees in this embodiment is set to 100, and the setting of 100 trees is considered to be a reasonable balance point in most practical applications. The maximum depth of each tree is set to 10, allowing the model to automatically select the optimal depth, which can prevent individual decision trees from becoming too complex, thereby reducing the risk of overfitting. The minimum number of split samples is set to 10, which can effectively prevent the model from overfitting, while ensuring that the tree can perform reasonable splits and decisions with sufficient data support. The random seed is 42, which is used to ensure the consistency of compensation strategies such as wind speed, wind direction, and temperature each time the model runs.

[0092] S52: After completing the parameter setting, initialize the Wind-Compensation algorithm;

[0093] S53: Based on the preprocessed data, terrain factor α and thermal disturbance factor β, a training data set is constructed, the mean square error MSE of the Wind-Compensation algorithm is calculated, and a feedback adjustment mechanism and its stop condition are established;

[0094] S531: define a threshold M for dynamically adjusting the interaction item, and obtain interaction item data N, specifically:

[0095] ;

[0096] ;

[0097] When the Wind-Compensation algorithm is run for the first time, the three-way interaction term is used, and then the interaction term N is selected based on the relationship between the mean square error MSE of the current Wind-Compensation algorithm and the threshold M;

[0098] If the mean square error MSE of the current Wind-Compensation algorithm exceeds 1.2 times the threshold M, the nonlinear interaction term is used. The calculation formula of the nonlinear interaction term is: 1,s The sum of the topographic factor α is exponentially transformed, and the temperature data O 3 'The sum of the thermal flow factor β is logarithmically transformed; if the current Wind-Compensation algorithm mean square error MSE is less than 1.1 times the threshold M, the binary interaction term is used. The binary interaction term calculation formula is cosine coded wind direction data O 1,c and sinusoidally encoded wind direction data O 1,s Respectively with wind speed data O 2', and then add them to the terrain factor α and the thermal flow factor β respectively; if the current Wind-Compensation algorithm mean square error MSE is between 1.1 and 1.2 times the threshold M, the ternary interaction term is used. The calculation formula of the ternary interaction term is cosine coded wind direction data O 1,c and sinusoidally encoded wind direction data O 1,s Respectively with wind speed data O 2 ' and temperature data O 3 ', and then added to the terrain factor α and the thermal factor β respectively; the threshold M of this embodiment is initially set to 0.1, and the selection of this threshold is based on the prediction error tolerance of the model and is derived in combination with preliminary experimental results. By setting a lower threshold M, the system can make more detailed adjustments when the error is small to improve the prediction accuracy of the model, while avoiding the computational burden caused by excessive adjustments.

[0099] S532: Establish a feedback adjustment mechanism to calculate the change rate MSE' of MSE in real time and adjust M according to MSE', specifically:

[0100] ;

[0101] Among them, the sign function sgn(MSE') is used to determine the positive or negative sign of MSE', which determines the increase or decrease of M. The adjustment factor 0.1 controls the adjustment amplitude of M to ensure that the adjustment amplitude is moderate and will not affect the system stability due to too fast or too slow changes. |MSE'| is the change amplitude of MSE, which is used to determine the specific amount of adjustment of M.

[0102] S533: Set the stop condition of the feedback adjustment mechanism, repeat steps S531-S532 until MSE' is less than 0.5% and the algorithm stops when the condition is met three times in a row.

[0103] S54: Calculate the wind direction compensation strategy when the Wind-Compensation algorithm stops, specifically:

[0104] ;

[0105] Where u is the wind direction compensation, f u is the mapping function obtained through Wind-Compensation algorithm training;

[0106] S6: According to the compensation strategy calculated by the Wind-Compensation algorithm, the flight angle of the fire extinguishing bomb is adjusted in real time:

[0107] The compensation strategy calculated by the Wind-Compensation algorithm is input into the control system of the fire-extinguishing bomb to adjust the flight angle of the fire-extinguishing bomb in real time.

[0108] Embodiment 2:

[0109] The present invention also provides a fire extinguishing bomb delivery compensation system, the system comprising:

[0110] Data collection module: collects wind direction data, wind speed data and temperature data from multiple sensors in real time;

[0111] Data preprocessing module: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data;

[0112] Environmental factor generation module: inputs the preprocessed data into the meteorological simulation software to generate terrain factors and thermal disturbance factors;

[0113] Algorithm module: input the pre-processed data, terrain factors and thermal disturbance factors into the Wind-Compensation algorithm, establish a feedback adjustment mechanism, set stop conditions, and calculate compensation strategies;

[0114] Compensation module: The compensation strategy calculated by the algorithm module is input into the fire extinguishing bomb control system to adjust the flight angle of the fire extinguishing bomb in real time.

[0115] In detail, each module in the fire extinguishing bomb delivery compensation system in the embodiment of the present invention is used in the same manner as above. Figure 1 The same technical means as the fire extinguishing bomb release compensation method described in the above are used and can produce the same technical effects, so they will not be repeated here.

[0116] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0117] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. And the terms "including", "comprising" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0118] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0119] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A fire extinguishing bomb delivery compensation method, characterized in that: The following steps are involved: S1: Collect wind direction data, wind speed data and temperature data of the fire bomb environment through multiple sensors; S2: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data; S3: input the preprocessed data into the meteorological simulation software to generate terrain factors in real time; S4: input the preprocessed data into the meteorological simulation software to generate geothermal airflow disturbance factors in real time; S5: Inputting the pre-processed data, terrain factors and thermal disturbance factors into the Wind-Compensation algorithm to calculate the compensation strategy; including: S51: Set the parameters of the Wind-Compensation algorithm, including the number of trees, the maximum depth of each tree, the minimum number of node split samples, and the random seed; S52: After completing the parameter setting, initialize the Wind-Compensation algorithm; S53: Based on the preprocessed data, terrain factor α and thermal disturbance factor β, a training data set is constructed, the mean square error MSE of the Wind-Compensation algorithm is calculated, and a feedback adjustment mechanism and its stop condition are established; including: S531: define a threshold M for dynamically adjusting the interaction item, and obtain interaction item data N, specifically: ； ； When the Wind-Compensation algorithm is first run, the three-way interaction term is used, and then the interaction term N is selected based on the relationship between the mean square error MSE of the current Wind-Compensation algorithm and the threshold M; S532: Establish a feedback adjustment mechanism to calculate the change rate MSE' of MSE in real time and adjust M according to MSE', specifically: ； S533: Set the stop condition of the feedback adjustment mechanism, repeat steps S531-S532 until MSE' is less than 0.5% and the condition is met three times in a row, then the algorithm stops; S54: Calculate the wind direction compensation strategy when the Wind-Compensation algorithm stops, specifically: ； Where u is the wind direction compensation, f u is the mapping function obtained through Wind-Compensation algorithm training; S6: According to the compensation strategy calculated by the Wind-Compensation algorithm, the flight angle of the fire extinguishing bomb is adjusted in real time.

2. The fire extinguishing bomb delivery compensation method according to claim 1, characterized in that: The step S2 comprises: S21: Perform sine-cosine encoding on the wind direction data O1 to obtain sine-encoded wind direction data O 1,s Sum and cosine coded wind direction data O 1,c , specifically: ； S22: performing Min-Max normalization on the wind speed data O2 and the temperature data O3 to obtain wind speed data O2' and temperature data O3'; The sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c , wind speed data 2' and temperature data 3' Constitute the preprocessed data.

3. The fire extinguishing bomb delivery compensation method according to claim 2, characterized in that: The step S3 comprises: S31: Input the pre-processed data into the meteorological simulation software and generate the simulated wind speed data V of the wind field in combination with the terrain data d,terrain and simulated wind direction data θ d,terrain ; S32: simulate wind direction data θ d,terrain Perform sine and cosine encoding to obtain the simulated wind direction sinusoidal encoding data θ d,terrain,s and simulated wind direction cosine coded data θ d,terrain,c , specifically: ； S33: According to the simulated wind speed data V d,terrain , simulated wind direction sinusoidal encoding data θ d,terrain,s , simulated wind direction cosine encoding data θ d,terrain,c , sinusoidal coded wind direction data O 1,s , cosine coded wind direction data O 1,c And wind speed data O2', calculate the terrain factor α, specifically: 。 4. The fire extinguishing bomb delivery compensation method according to claim 3, characterized in that: The step S4 includes: S41: Input the preprocessed data into the meteorological simulation software, and input the fuel type of the fire scene, combine the terrain data to simulate the hot air flow generated by the fire scene and its influence on temperature and wind speed, and generate simulated temperature data T d,fire and simulated wind speed data V d,fire ; S42: According to the simulated temperature data T d,fire , simulated wind speed data V d,fire , temperature data O3' and wind speed data O2', calculate the thermal airflow disturbance factor β, specifically: 。 5. The fire extinguishing bomb delivery compensation method according to claim 1, characterized in that: The step S6 includes: The compensation strategy calculated by the Wind-Compensation algorithm is input into the control system of the fire-extinguishing bomb to adjust the flight angle of the fire-extinguishing bomb in real time.

6. A fire extinguishing bomb delivery compensation system, characterized in that: include: Data collection module: collects wind direction data, wind speed data and temperature data from multiple sensors in real time; Data preprocessing module: preprocessing the wind direction data, wind speed data and temperature data to obtain preprocessed data; Environmental factor generation module: input preprocessed data into the meteorological simulation software to generate terrain factors and thermal disturbance factors; Algorithm module: input the pre-processed data, terrain factors and thermal disturbance factors into the Wind-Compensation algorithm, establish a feedback adjustment mechanism, set stop conditions, and calculate compensation strategies; Compensation module: inputs the compensation strategy calculated by the algorithm module into the fire extinguishing bomb control system to adjust the flight angle of the fire extinguishing bomb in real time; To realize a fire extinguishing bomb delivery compensation method as described in any one of claims 1-5.

Images