Rapid rescue helicopter cooperative command method and system
By cluster analysis of historical helicopter flight data and route optimization using 3D solid models, the problems of fuel consumption estimation errors and unreasonable resource allocation in helicopter collaborative command were solved, enabling rapid and accurate execution of rescue missions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-17
- Publication Date
- 2026-03-27
AI Technical Summary
Existing helicopter collaborative command methods rely on experience-based judgment, resulting in large errors in fuel consumption estimation, unreasonable resource allocation, and difficulty in achieving efficient multi-task collaborative coverage, thus affecting the speed and accuracy of emergency rescue.
By clustering analysis of historical helicopter flight data, flight characteristics under different loads and speeds are determined. Combined with a three-dimensional solid model, flight routes are optimized to achieve the optimal collaborative command method and resource allocation.
Precise quantification of fuel consumption and flight distance optimizes resource allocation, improves the efficiency and safety of rescue missions, shortens response time, and avoids errors from traditional experience-based judgments.
Smart Images
Figure CN121745532A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of helicopter technology, specifically to a method and system for coordinated command of rapid rescue helicopters. Background Technology
[0002] In the current field of rapid rescue, helicopters have become one of the core equipment in emergency rescue missions due to their advantages of maneuverability and rapid response. However, there are still many problems to be solved in the existing helicopter collaborative command methods.
[0003] First, the determination of helicopter flight characteristics relies heavily on the experience of operators, failing to fully leverage the value of historical flight data. This leads to significant errors in the estimation of fuel consumption and flight distance under different loads and flight speeds, which can easily result in insufficient helicopter fuel or unreasonable load matching, thus affecting the smooth progress of rescue missions.
[0004] Secondly, in the allocation of rescue resources, when faced with multiple rescue points and multiple helicopters, there is a lack of systematic allocation logic and quantitative evaluation standards. The simple approach of "assigning the nearest one" is often adopted without considering the performance compatibility of helicopters and the overall mission time. This may lead to resource waste or untimely coverage of rescue points. In particular, when the number of rescue points exceeds the number of helicopters, it is difficult to achieve efficient collaborative coverage of multiple missions.
[0005] These problems collectively restrict the efficiency and safety of coordinated command of rapid rescue helicopters, making it difficult to meet the core requirements of "speed, accuracy and efficiency" for emergency rescue missions. Therefore, a systematic and data-driven coordinated command method is urgently needed to break through the existing technological bottlenecks. Summary of the Invention
[0006] To address the shortcomings of existing technologies, this invention provides a rapid rescue helicopter collaborative command method and system, which solves the problem of failing to meet the core requirements of "speed, accuracy, and efficiency" for emergency rescue missions.
[0007] To achieve the above objectives, the present invention provides a rapid rescue helicopter coordinated command method, comprising the following steps:
[0008] Step 1: Analyze the historical flight data of different helicopters to identify the flight characteristics associated with different loads and flight speeds, and record and confirm these different flight characteristics. The specific method is as follows:
[0009] Historical flight data associated with different helicopters is extracted. From this extracted historical flight data, historical flight data belonging to the same load range are initially extracted as initial data, with the load range set as a preset range. Then, secondary extraction data associated with the same flight speed is identified from the initial extraction data. Fuel consumption data is then identified from the secondary extraction data, and the identified fuel consumption data is clustered: the identified groups of fuel consumption data are sorted in ascending order of value to confirm the fuel consumption data sequence. Finally, the initial value YH of the fuel consumption data sequence is determined. min and the terminal value YH max Generate fuel consumption characteristic range [YH] min YH max Then, several variable intervals are generated synchronously, and the variable intervals ∈ [YH]. min YH max ], confirm the interval density associated with each variable interval, and select from several confirmed interval density sets M k The maximum value is selected, and the variable range associated with the maximum value is recorded as the flight characteristic of this helicopter at the corresponding flight speed state in the corresponding load range;
[0010] From the historical flight data associated with different helicopters, the flight characteristics associated with different helicopters under different load ranges and flight speeds are determined sequentially;
[0011] Step 2: Confirm the rescue data associated with different rescue points, simultaneously confirm the total number of helicopters, confirm the flight routes associated with the takeoff points and rescue points, conduct comprehensive verification of multiple helicopter groups, confirm and display the optimal coordinated command method, specifically as follows:
[0012] Confirm the number of rescue points S1, and then confirm the total number of helicopters S2:
[0013] If S1≤S2, determine the total amount of required items from the rescue data associated with different rescue points. Then, based on the set load range, determine the load range associated with the total amount for each rescue point, and record it as the associated range for the corresponding rescue point. Next, determine the variable range associated with the maximum flight speed of each helicopter for the associated range from the flight characteristics recorded by each helicopter, and select the median value of the variable range as the fuel consumption characteristic of the corresponding helicopter. Determine the preset flight route between each helicopter and different rescue points, and determine the flight distance. Use: Flight distance × Fuel consumption characteristic = Total fuel consumption. Then, record the fuel tank volume associated with each helicopter as R. i Where i represents different helicopters, satisfying: R i Rescue points with a value greater than 2 × total fuel consumption are recorded as the reachable points of the corresponding helicopters, and the reachable points associated with each helicopter are confirmed sequentially.
[0014] Based on the different reachable points associated with different helicopters, several sets of allocation logic are executed. Within each allocation logic: each helicopter is associated with a set of reachable points, and all reachable points are associated. A single reachable point is associated with only one set of helicopters. The allocation characteristics associated with each allocation logic are determined.
[0015] Then, from the different allocation characteristics associated with different allocation logics, select the minimum value, record the allocation logic associated with the minimum value as the optimal collaborative command method, and display it.
[0016] If S1 > S2, determine the total amount of required items from the rescue data associated with different rescue points, and then determine the load range associated with the total amount of each rescue point according to the set load range. Record it as the associated range of the corresponding rescue point. Then, randomly combine different load ranges and stop when the total number of the combined ranges is consistent with S2. Confirm several combination methods.
[0017] For a single combination method, the combined load range is recorded as the comprehensive range, and the combined rescue point is recorded as the combination point. The variable range associated with the maximum flight speed of each helicopter in the comprehensive range is identified, and the median value of the variable range is selected as the fuel consumption characteristic of the corresponding helicopter. The starting point of the helicopter is determined, and the rescue point closest to the starting point is identified from the multiple rescue points associated with the combination point as the initial arrival point. The preset flight route of other rescue points within the range of starting point - initial arrival point - combination point is identified, and the total fuel consumption associated with the corresponding helicopter is identified based on the flight distance and fuel consumption characteristics. Then, the reachable combination point associated with the corresponding helicopter is identified using the same determination method as the reachable point. If the corresponding point is not a combination point, the same determination method as the reachable point is used for determination.
[0018] Based on the different reachable combination points or reachable points associated with different helicopters, several sets of allocation logic are executed. Each different combination method is associated with several different allocation logics. The allocation logic is determined by the same allocation characteristics. The minimum value is selected from several allocation characteristics. The allocation logic associated with the minimum value is recorded as the optimal coordinated command method and displayed.
[0019] Step 3: Based on the determined optimal collaborative command method, confirm the flight routes associated with each different helicopter, and optimize the flight routes using a pre-set 3D solid model. The optimized routes are then determined and displayed. The specific method is as follows:
[0020] The flight path associated with each helicopter is determined, and the specific route location is determined simultaneously by combining the three-dimensional solid model. Each route point within the flight path is processed vertically downwards, and the associated vertical point is determined on the three-dimensional solid model.
[0021] Based on the determined associated vertical point, a set of spatial points are identified vertically upwards. The straight-line distance between the spatial points and the associated vertical point is L, where L is a preset value. Then, the identified sets of spatial points are integrated to identify the preliminary optimized route associated with the corresponding flight route.
[0022] Each route point within the initial optimized route is moved up and down within a preset range. Several movement processes are executed, and the vertical distance between the highest and lowest route points in a single movement process is determined. From the several vertical distances associated with the several movement processes, the minimum value is selected, and the initial optimized route associated with the minimum value is recorded as the optimized route and displayed.
[0023] Preferably, in step one, the method for confirming the interval density associated with each variable interval is as follows:
[0024] Let F be the range of intervals associated with each variable interval. k Where k represents different variable intervals, and the number of fuel consumption data points included in each variable interval is denoted as G. k G k ÷F k =M k Confirm the interval density M associated with the corresponding interval k The interval density M associated with each different variable interval k Please confirm.
[0025] Preferably, in step two, the allocation feature associated with each allocation logic is determined as follows: based on the flight distance and maximum flight speed associated with each helicopter, the flight time associated with each helicopter is determined, and the maximum value is selected from the flight time associated with each helicopter as the allocation feature of the corresponding allocation logic.
[0026] Preferred, rapid rescue helicopter collaborative command system includes:
[0027] The flight characteristic recording terminal analyzes the historical flight data of different helicopters to identify the flight characteristics associated with different helicopters under different loads and flight speeds, and records and confirms the different flight characteristics.
[0028] The optimal collaborative command method confirmation terminal confirms the rescue data associated with different rescue points, simultaneously confirms the total number of helicopters, confirms the flight routes associated with the takeoff point and the rescue point, performs comprehensive verification on multiple groups of helicopters, confirms the optimal collaborative command method and displays it.
[0029] The route determination end optimizes the flight path of each helicopter based on the determined optimal collaborative command method. It then optimizes the flight path by combining it with the preset 3D solid model, and displays the optimized route.
[0030] This invention provides a method and system for coordinated command of rapid rescue helicopters. Compared with existing technologies, it has the following advantages:
[0031] This invention determines the flight characteristics under different loads and speeds by cluster analysis of historical helicopter flight data, accurately quantifies the correlation between fuel consumption and flight distance, provides a data-driven decision-making basis for subsequent task allocation, avoids the errors of traditional experience-based judgment, and ensures the scientific and adaptable nature of helicopter scheduling.
[0032] Secondly, for different scenarios with varying numbers of rescue points and helicopters, the system achieves optimal allocation of rescue resources by comparing the characteristics of reachable point determination and multiple allocation logics. When there are few rescue points, it ensures efficient execution of single tasks, and when there are many rescue points, it achieves multi-task collaborative coverage through combination optimization, significantly shortening the overall rescue response time.
[0033] Finally, the flight path was optimized by combining the three-dimensional solid model. Through vertical point spatial mapping and smooth adjustment of route points, the safety of the flight path in avoiding terrain obstacles was ensured, and the flight stability and efficiency were improved by minimizing the vertical distance of the route, while reducing fuel consumption and flight risks.
[0034] In summary, this method realizes a closed loop of "data-driven decision-making, dynamic allocation, and precise planning" in rescue command, effectively improving the overall efficiency, resource utilization, and flight safety of rapid rescue, and providing reliable technical support for emergency rescue missions. Attached Figure Description
[0035] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation
[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0037] First Embodiment
[0038] Please see Figure 1 This application provides a method for coordinated command of rapid rescue helicopters, including the following steps:
[0039] Step 1: Analyze the historical flight data of different helicopters to identify the flight characteristics associated with different loads and flight speeds. Record and confirm these flight characteristics. Specifically, different flight parameters result in different flight characteristics, which are reflected in the fuel consumption under corresponding conditions. By combining this with the associated fuel tank information for each helicopter, the associated flight distance can be effectively simulated, facilitating subsequent comprehensive determination of the helicopter's flight path.
[0040] The specific methods for recording and confirming different flight characteristics are as follows:
[0041] Historical flight data associated with different helicopters is extracted. From this extracted historical flight data, historical flight data belonging to the same load range are initially extracted as initial extraction data. The load range is a preset range, determined in advance by the operator based on experience. Then, secondary extraction data associated with the same flight speed is identified from the initial extraction data. Fuel consumption data is then identified from the secondary extraction data, and the identified fuel consumption data is clustered: the identified groups of fuel consumption data are sorted in ascending order of value to confirm the fuel consumption data sequence. Finally, the initial value YH of the fuel consumption data sequence is determined. min and the terminal value YH max Generate fuel consumption characteristic range [YH] min YH max Then, several variable intervals are generated synchronously, and the variable intervals ∈ [YH]. min YH max For each variable interval, the interval density associated with it is confirmed, and the interval range associated with each variable interval is denoted as F. k Where k represents different variable intervals, and the number of fuel consumption data points included in each variable interval is denoted as G. k G k ÷F k =M k Confirm the interval density M associated with the corresponding interval k The interval density M associated with each different variable interval k Confirmation is performed, and the density M of the confirmed intervals is determined. k The maximum value is selected, and the variable range associated with the maximum value is recorded as the flight characteristic of this helicopter at the corresponding flight speed state in the corresponding load range;
[0042] From the historical flight data associated with different helicopters, the flight characteristics associated with different helicopters under different load ranges and flight speeds are determined sequentially;
[0043] Specifically, different helicopters have different characteristics such as size, and they have different flight speeds under different flight conditions, which are associated with different flight characteristics. In order to better coordinate and command different helicopters and achieve the best rapid rescue effect, it is necessary to determine the flight characteristics of different helicopters and combine them with the actual flight conditions to achieve the best coordinated command effect.
[0044] Step 2: Confirm the rescue data associated with different rescue points, simultaneously confirm the total number of helicopters, confirm the flight routes associated with the takeoff points and rescue points, conduct comprehensive verification of multiple groups of helicopters, confirm the optimal collaborative command method and display it.
[0045] The specific method for confirming the optimal coordinated command approach is as follows:
[0046] Confirm the number of rescue points S1, and then confirm the total number of helicopters S2:
[0047] If S1≤S2, determine the total amount of required items from the rescue data associated with different rescue points. Then, based on the set load range, determine the load range associated with the total amount for each rescue point, and record it as the associated range for the corresponding rescue point. Next, determine the variable range associated with the maximum flight speed of each helicopter for the associated range from the flight characteristics recorded by each helicopter, and select the median value of the variable range as the fuel consumption characteristic of the corresponding helicopter. Determine the preset flight route between each helicopter and different rescue points, and determine the flight distance. Use: Flight distance × Fuel consumption characteristic = Total fuel consumption. Then, record the fuel tank volume associated with each helicopter as R. i Where i represents different helicopters, satisfying: R i Rescue points with a value greater than 2 × total fuel consumption are recorded as the reachable points of the corresponding helicopters, and the reachable points associated with each helicopter are confirmed sequentially.
[0048] Based on the different reachable points associated with different helicopters, several sets of allocation logic are executed. Within each allocation logic: each helicopter is associated with a set of reachable points, and all reachable points are associated. A single reachable point is associated with only one set of helicopters. The allocation characteristics associated with each allocation logic are determined: based on the flight distance and maximum flight speed associated with each helicopter, the flight time associated with each helicopter is determined, and the maximum value is selected from the flight times associated with each helicopter as the allocation characteristic of the corresponding allocation logic.
[0049] Then, from the different allocation characteristics associated with different allocation logics, select the minimum value, record the allocation logic associated with the minimum value as the optimal collaborative command method, and display it.
[0050] If S1 > S2, determine the total amount of required items from the rescue data associated with different rescue points, and then determine the load range associated with the total amount of each rescue point according to the set load range. Record it as the associated range of the corresponding rescue point. Then, randomly combine different load ranges and stop when the total number of the combined ranges is consistent with S2. Confirm several combination methods.
[0051] For a single combination method, the combined load range is recorded as the comprehensive range, and the combined rescue point is recorded as the combination point. The variable range associated with the maximum flight speed of each helicopter in the comprehensive range is identified, and the median value of the variable range is selected as the fuel consumption characteristic of the corresponding helicopter. The starting point of the helicopter is determined, and the rescue point closest to the starting point is identified from the multiple rescue points associated with the combination point as the initial arrival point. The preset flight route of other rescue points within the range of starting point - initial arrival point - combination point is identified, and the total fuel consumption associated with the corresponding helicopter is identified based on the flight distance and fuel consumption characteristics. Then, the reachable combination point associated with the corresponding helicopter is identified using the same determination method as the reachable point. If the corresponding point is not a combination point, the same determination method as the reachable point is used for determination.
[0052] Based on the different reachable combination points or reachable points associated with different helicopters, several sets of allocation logic are executed. Each different combination method is associated with several different allocation logics. The allocation logic is determined by the same allocation characteristics. The minimum value is selected from several allocation characteristics. The allocation logic associated with the minimum value is recorded as the optimal coordinated command method and displayed.
[0053] Specifically, when the total number of corresponding rescue points is less than the total number of helicopters, a comprehensive analysis and evaluation can be conducted based on the specific flight routes and load conditions. The optimal method can be selected from several analysis and processing methods to ensure effective reduction of rescue time.
[0054] When the total number of corresponding rescue points exceeds the total number of corresponding helicopters, a single helicopter needs to reach multiple rescue points to implement the corresponding rescue plan and dispatch and distribute the necessary supplies. However, in the actual process, it is necessary to determine the helicopters that can reach multiple rescue points, and then conduct multi-terminal analysis and verification based on the actual situation to make a comprehensive evaluation, determine the optimal command method, and make a comprehensive selection.
[0055] Step 3: Based on the determined optimal collaborative command method, confirm the flight routes associated with each different helicopter, and optimize the flight routes by combining them with the preset 3D solid model, determine the optimized routes and display them;
[0056] The specific methods for optimizing flight routes are as follows:
[0057] The flight path associated with each helicopter is determined, and the specific route location is determined simultaneously by combining the three-dimensional solid model. Each route point within the flight path is processed vertically downwards, and the associated vertical point is determined on the three-dimensional solid model.
[0058] Based on the determined associated vertical point, a set of spatial points are identified vertically upwards. The straight-line distance between the spatial point and the associated vertical point is L, where L is a preset value, generally between 80m and 100m. Then, the identified sets of spatial points are integrated to confirm the preliminary optimized route associated with the corresponding flight route.
[0059] Each route point within the initial optimized route is moved vertically, with the movement range being a preset value, typically ±5m. Several movement processes are executed, and the vertical distance between the highest and lowest route points in a single movement process is determined. From the several vertical distances associated with several movement processes, the minimum value is selected, and the initial optimized route associated with the minimum value is recorded as the optimized route and displayed.
[0060] Specifically, in the route optimization process, there is an associated preliminary optimized route. Based on the determined preliminary optimized route and the upward and downward fluctuation of the corresponding route points, the smoothness of the route is further optimized to lock in the optimal optimized route.
[0061] Second Embodiment
[0062] A rapid rescue helicopter collaborative command system includes:
[0063] The flight characteristic recording terminal analyzes the historical flight data of different helicopters to identify the flight characteristics associated with different helicopters under different loads and flight speeds, and records and confirms the different flight characteristics.
[0064] The optimal collaborative command method confirmation terminal confirms the rescue data associated with different rescue points, simultaneously confirms the total number of helicopters, confirms the flight routes associated with the takeoff point and the rescue point, performs comprehensive verification on multiple groups of helicopters, confirms the optimal collaborative command method and displays it.
[0065] The route determination end optimizes the flight path of each helicopter based on the determined optimal collaborative command method. It then optimizes the flight path by combining it with the preset 3D solid model, and displays the optimized route.
[0066] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.
[0067] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.
Claims
1. A rapid rescue helicopter coordinated command method, characterized in that, Includes the following steps: Step 1: Analyze the historical flight data of different helicopters to identify the flight characteristics associated with different loads and flight speeds, and record and confirm the different flight characteristics. Step 2: Confirm the rescue data associated with different rescue points, simultaneously confirm the total number of helicopters, confirm the flight routes associated with the takeoff points and rescue points, conduct comprehensive verification of multiple groups of helicopters, confirm the optimal collaborative command method and display it. Step 3: Based on the determined optimal collaborative command method, confirm the flight routes associated with each different helicopter, and optimize the flight routes by combining them with the preset three-dimensional solid model, determine the optimized routes and display them.
2. The rapid rescue helicopter coordinated command method according to claim 1, characterized in that, In step one, the specific method for recording and confirming different flight characteristics is as follows: Historical flight data associated with different helicopters is extracted. From this extracted historical flight data, historical flight data belonging to the same load range are initially extracted as initial data, with the load range set as a preset range. Then, secondary extraction data associated with the same flight speed is identified from the initial extraction data. Fuel consumption data is then identified from the secondary extraction data, and the identified fuel consumption data is clustered: the identified groups of fuel consumption data are sorted in ascending order of value to confirm the fuel consumption data sequence. Finally, the initial value YH of the fuel consumption data sequence is determined. min and the terminal value YH max Generate fuel consumption characteristic range [YH] min YH max Then, several variable intervals are generated synchronously, and the variable intervals ∈ [YH]. min YH max ], confirm the interval density associated with each variable interval, and select from several confirmed interval density sets M k The maximum value is selected, and the variable range associated with the maximum value is recorded as the flight characteristic of this helicopter at the corresponding flight speed state in the corresponding load range; The flight characteristics associated with different helicopters under different load ranges and flight speeds are determined sequentially from the historical flight data associated with different helicopters.
3. The rapid rescue helicopter coordinated command method according to claim 2, characterized in that, In step one, the method for confirming the interval density associated with each variable interval is as follows: Let F be the range of intervals associated with each variable interval. k Where k represents different variable intervals, and the number of fuel consumption data points included in each variable interval is denoted as G. k G k ÷F k =M k Confirm the interval density M associated with the corresponding interval k The interval density M associated with each different variable interval k Please confirm.
4. The rapid rescue helicopter coordinated command method according to claim 1, characterized in that, In step two, the specific method for confirming the optimal collaborative command method is as follows: Confirm the number of rescue points S1, and then confirm the total number of helicopters S2: If S1≤S2, determine the total amount of required items from the rescue data associated with different rescue points. Then, based on the set load range, determine the load range associated with the total amount for each rescue point, and record it as the associated range for the corresponding rescue point. Next, determine the variable range associated with the maximum flight speed of each helicopter for the associated range from the flight characteristics recorded by each helicopter, and select the median value of the variable range as the fuel consumption characteristic of the corresponding helicopter. Determine the preset flight route between each helicopter and different rescue points, and determine the flight distance. Use: Flight distance × Fuel consumption characteristic = Total fuel consumption. Then, record the fuel tank volume associated with each helicopter as R. i Where i represents different helicopters, satisfying: R i Rescue points with a value greater than 2 × total fuel consumption are recorded as the reachable points of the corresponding helicopters, and the reachable points associated with each helicopter are confirmed sequentially. Based on the different reachable points associated with different helicopters, several sets of allocation logic are executed. Within each allocation logic: each helicopter is associated with a set of reachable points, and all reachable points are associated. A single reachable point is associated with only one set of helicopters. The allocation characteristics associated with each allocation logic are determined. Then, from the different allocation characteristics associated with different allocation logics, select the minimum value, record the allocation logic associated with the minimum value as the optimal collaborative command mode, and display it.
5. The rapid rescue helicopter coordinated command method according to claim 4, characterized in that, In step two, the allocation feature associated with each allocation logic is determined as follows: based on the flight distance and maximum flight speed associated with each helicopter, the flight time associated with each helicopter is determined, and the maximum value is selected from the flight time associated with each helicopter as the allocation feature of the corresponding allocation logic.
6. The rapid rescue helicopter coordinated command method according to claim 4, characterized in that, If S1 > S2, determine the total amount of required items from the rescue data associated with different rescue points, and then determine the load range associated with the total amount of each rescue point according to the set load range. Record it as the associated range of the corresponding rescue point. Then, randomly combine different load ranges and stop when the total number of the combined ranges is consistent with S2. Confirm several combination methods. For a single combination method, the combined load range is recorded as the comprehensive range, and the combined rescue point is recorded as the combination point. The variable range associated with the maximum flight speed of each helicopter in the comprehensive range is identified, and the median value of the variable range is selected as the fuel consumption characteristic of the corresponding helicopter. The starting point of the helicopter is determined, and the rescue point closest to the starting point is identified from the multiple rescue points associated with the combination point as the initial arrival point. The preset flight route of other rescue points within the range of starting point - initial arrival point - combination point is identified, and the total fuel consumption associated with the corresponding helicopter is identified based on the flight distance and fuel consumption characteristics. Then, the reachable combination point associated with the corresponding helicopter is identified using the same determination method as the reachable point. If the corresponding point is not a combination point, the same determination method as the reachable point is used for determination. Based on the different reachable combination points or reachable points associated with different helicopters, several sets of allocation logic are executed. Each different combination method is associated with several different allocation logics. The allocation logic is determined by the same allocation characteristics. The minimum value is selected from several allocation characteristics. The allocation logic associated with the minimum value is recorded as the optimal coordinated command method and displayed.
7. The rapid rescue helicopter coordinated command method according to claim 1, characterized in that, In step three, the specific method for optimizing the flight route is as follows: The flight path associated with each helicopter is determined, and the specific route location is determined simultaneously by combining the three-dimensional solid model. Each route point within the flight path is processed vertically downwards, and the associated vertical point is determined on the three-dimensional solid model. Based on the determined associated vertical point, a set of spatial points are identified vertically upwards. The straight-line distance between the spatial points and the associated vertical point is L, where L is a preset value. Then, the identified sets of spatial points are integrated to identify the preliminary optimized route associated with the corresponding flight route. Each route point within the initial optimized route is moved up and down within a preset range. Several movement processes are executed, and the vertical distance between the highest and lowest route points in a single movement process is determined. From the several vertical distances associated with the several movement processes, the minimum value is selected, and the initial optimized route associated with the minimum value is recorded as the optimized route and displayed.
8. A rapid rescue helicopter collaborative command system, wherein the system operates according to the rapid rescue helicopter collaborative command method according to any one of claims 1-7, characterized in that, include: The flight characteristic recording terminal analyzes the historical flight data of different helicopters to identify the flight characteristics associated with different helicopters under different loads and flight speeds, and records and confirms the different flight characteristics. The optimal collaborative command method confirmation terminal confirms the rescue data associated with different rescue points, simultaneously confirms the total number of helicopters, confirms the flight routes associated with the takeoff point and the rescue point, performs comprehensive verification on multiple groups of helicopters, confirms the optimal collaborative command method and displays it. The route determination end optimizes the flight path of each helicopter based on the determined optimal collaborative command method. It then optimizes the flight path by combining it with the preset 3D solid model, and displays the optimized route.