A Petri net-based adaptive display method and system for aircraft key actions

Abstract

The present invention relates to the technical field of aircraft key action display technology, and in particular to a Petri net-based method and system for adaptively displaying aircraft key actions. The method comprises: S1, decomposing an aircraft flight test into a hierarchical nested structure of "aircraft - primary key action - secondary key action - ... - component behavior"; S2, parameterizing aircraft component behaviors based on aircraft key action constraints; S3, adding the parameterized aircraft component behaviors to an aircraft key action behavior library; and S4, using an adaptive drive control Petri net model to drive and control the aircraft component behaviors in the aircraft key action behavior library, thereby achieving adaptive display of aircraft key actions. The present invention can adaptively display aircraft key actions.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft key action display, and in particular to a Petri net-based aircraft key action adaptive display method and system. Background Art

[0002] Demonstrating key aircraft maneuvers is crucial for command and control personnel to understand and interpret the subtle changes in an aircraft's state caused by these maneuvers. Rapidly responding to the need for displaying key aircraft maneuvers is a crucial requirement for the development and testing of aircraft weaponry, especially in multi-target integrated situational displays.

[0003] Researchers at home and abroad have developed image-based techniques for detecting and judging aircraft key maneuvers. These techniques, which capture live video from optical imaging equipment and utilize image processing techniques, have enabled key maneuver detection for launch vehicles, missiles, and other flight equipment. Key maneuver detection techniques based on multi-source measurement and control data fuse telemetry and external measurement data to extract key maneuver data features, enabling key maneuver detection. These two approaches, however, struggle to obtain effective images for aircraft at high altitudes and speeds, hindering detection results. Summary of the Invention

[0004] In order to solve the technical problems existing in the above-mentioned prior art, the present invention provides a method for adaptively displaying key aircraft actions based on Petri nets. The technical solution is as follows:

[0005] On the one hand, a method for adaptively displaying key actions of an aircraft based on Petri nets is provided, the method comprising:

[0006] S1. Decompose the aircraft flight test into a hierarchical nested structure of "aircraft-first-level critical action-second-level critical action-...-component behavior";

[0007] S2. Parameterize the behavior of aircraft components based on the key aircraft motion constraints;

[0008] S3. Add the parameterized aircraft component behaviors to the aircraft key action behavior library;

[0009] S4. Using an adaptive drive control Petri net model, the aircraft component behaviors in the aircraft key action behavior library are driven and controlled to achieve adaptive display of the aircraft key actions.

[0010] Optionally, the S1 specifically includes:

[0011] Traverse all key action lists in the aircraft key action behavior library and determine whether the current key action behavior list meets the requirements of this aircraft flight test:

[0012] If the conditions are met, the aircraft flight test is directly decomposed according to the key actions in the current key action list;

[0013] If this is not satisfied, there are two situations:

[0014] In the first case, if some key actions in multiple key action lists can be combined to meet the requirements of this flight test, a new key action list for this aircraft is added to the aircraft key action behavior library, which contains the combination of multiple key actions in the library, and this flight test is decomposed according to the newly added list;

[0015] In the second case, this flight test has new key actions, and the combination of some key actions in multiple key action lists still cannot meet the requirements of this flight test. In this case, after adding the key action list of this aircraft to the aircraft key action behavior library, the new key actions are recursively decomposed, and the secondary key actions are used to decompose the new key actions one by one, and finally the aircraft flight test is decomposed into a hierarchical nested structure of "aircraft-first-level key actions-second-level key actions-...-component behaviors".

[0016] Optionally, the S2 specifically includes:

[0017] S21. Make the following constraints on the key actions of the aircraft:

[0018] ① The aircraft is composed of various components, and there is a hierarchical relationship between the components. The components that behave first are at a lower level, and the components that behave later are at a higher level. Adjacent levels are connected by model binding.

[0019] ② The behavior of the component conforms to the laws of rigid body kinematics, which is a linear combination of two basic motions: translation and rotation;

[0020] ③The aircraft is composed of various component models in a hierarchical relationship;

[0021] ④ The tail flame of the component is realized by particle effects. As a special component, it does not follow constraint ②;

[0022] S22. Based on the above constraints, parameterize the behavior of aircraft components:

[0023] <Unit name,resource,offset,orient,time,end_offset,end_orient,visible>

[0024] The parameter Unit represents the aircraft component; resource represents the component resource variable, and the variable value is the 3D model resource path; offset and end_offset represent the translation movement of the component behavior; orient and end_orient represent the rotation movement of the component behavior; time represents the duration of the behavior; visible represents whether the component is displayed or hidden;

[0025] S23. Based on the above constraints, parameterize the tail flame of the component:

[0026] <Fx name,type,offset,color,start_size,end_size,length,duration,visible>

[0027] The parameter Fx represents the tail flame; offset represents the offset between the tail flame and the bound component; start_size and end_size represent the change in the tail flame range; length represents the length of the tail flame; duration represents the life cycle of the tail flame particle; and visible represents the display or hiding of the particle effect.

[0028] Optionally, the adaptive drive control Petri net model consists of a flight posture control subnet, a key action deduction subnet and a residual token cleaning subnet, the flight posture control subnet is connected in parallel with the key action deduction subnet, and the key action deduction subnet and the residual token cleaning subnet are coupled to each other;

[0029] The flight attitude control subnet is used to adjust the position and attitude of the aircraft in real time according to the attitude data received by the system throughout the test;

[0030] The key action deduction subnet is used to correctly deduce the key actions of different types of aircraft so that the aircraft can complete the key action demonstration of the test;

[0031] The residual token cleaning subnet is used to clean up the residual data tokens in the key action deduction subnet, so that the key action deduction subnet can be reused in multi-target aircraft tests.

[0032] Optionally, the flight posture control subnet is composed of three transitions t1, t2, and t3 for executing key action model animations, three corresponding places s1, s2, and s3 for storing data tokens, and finally a place s4 for storing data tokens, wherein after t1 is executed, the data token is transferred to s2, s2 and t2 form a self-loop, t3 is constrained by s2 and s3 at the same time, and after t3 is executed, the token is transferred to s4, which is represented by a Petri net Σ=(S, T; F, K, W, M0), where K is a capacity function, indicating the maximum value of the data tokens stored in place s∈S. If not specifically marked, the default value is infinite; W is a weight function, so that each directed arc f∈F corresponds to a positive integer. If not specifically marked, the default value is 1; M is a resource function, indicating the resource distribution of the network, M0 is the initial resource distribution in the network, M(s1)=M(s2)=M(s3)=M(s4)=0; for X=S∪T, · x={y|y∈X∩(y,x)∈F} is the front set of x, x · ={y|y∈X∩(x,y)∈F} is the subsequent set of x. When s1 receives the "takeoff" command, M(s1)=1. The condition for triggering transition t is as follows: The aircraft takes off; then according to formula (2), after transition t occurs, the global resource changes to: Resources change in the Petri net; then s2 obtains the token, and the aircraft adjusts its posture. Since this is a self-loop structure, under the alternating and repeated effects of formulas (1) and (2), the aircraft continuously adjusts its posture; until s3 receives the "stop" command, causing s2 to lose the token and the aircraft stops.

[0033] Optionally, the key action deduction subnet is composed of a plurality of basic units i with a symmetrical structure, each basic unit i contains a transition t i and the corresponding places i , for the change i Set the corresponding "dummy" transition t i ' and the corresponding library s i ', change t i After execution, the data token is sent to the library s i and s i 'Flow, change i 'After execution, the data token is sent to the library s i ' and s i Flow, in addition, in the transition t i and t i 'Set up two more libraries s 0i With s 0i ',t i Connect to s 0i , s 0i With ti ' are connected by constraint arcs, t i 'Connect to s 0i ',s 0i 'with t i They are connected by constraint arcs, where "dumb" transitions correspond to transitions. After execution, no action occurs, and there is no actual model animation. Constraint arcs implement logical "not". When there is no data token in the place or all data tokens are lost, the corresponding transition is triggered.

[0034] Connect multiple basic units end to end and set up the total storage place S T With all changes j , j = 1, 2, ... connected, corresponding to the total library S T 'With all "dumb" transitions j ', j = 1, 2, ... are connected to form the key action deduction subnet, which drives the control of the aircraft model animation with real-time data to achieve the effect of adaptive deduction of key actions. Assuming that the flight experiment includes 4 key actions, the transition set T = {t1, t2, t3, t4} is the complete set of key actions in the aircraft key action behavior library, and T' = {t'1, t'2, t'3, t'4} corresponds to T and is the corresponding "dummy" transition. Assuming that there are two aircraft A and B, the driving control logic of the key action deduction subnet is:

[0035] Assume that their respective key action deduction paths are: A =t1→t2→t3→t4, Ψ B =t1→t3→t4, for Ψ A , library s T Receive 4 data tokens, according to formula (1) and (2), the transitions t1, t2, t3, and t4 are triggered in sequence, and A completes all key actions; for Ψ B , library s T Receive 1 data token, according to formula (1), transition t1 is triggered, according to formula (2) data flow, then library s' T Automatically put in 1 data token, triggering transition t'2, until the library s T Receive the data token again and get the path and B completes all key actions.

[0036] Optionally, the residual token cleaning subnet, for each basic unit's library s 0i With s 0i ', correspondingly add 2 transitions and 1 library place to construct a logical "OR" Petri net structure, and then use a transition to connect the operation results of all "OR" structure Petri nets to form the residual token cleaning subnet.

[0037] In another aspect, a Petri net-based adaptive display system for aircraft key actions is provided, the system comprising:

[0038] Decomposition module, used to decompose the aircraft flight test into a hierarchical nested structure of "aircraft-first-level key action-second-level key action-...-component behavior";

[0039] Parameterization module, used to parameterize the behavior of aircraft components based on the key action constraints of the aircraft;

[0040] Add a module to add parameterized aircraft component behaviors to the aircraft key action behavior library;

[0041] The adaptive display module is used to use the adaptive drive control Petri net model to drive and control the aircraft component behaviors in the aircraft key action behavior library to achieve adaptive display of the aircraft key actions.

[0042] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the above-mentioned Petri net-based adaptive display method for key aircraft actions.

[0043] On the other hand, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the above-mentioned Petri net-based adaptive display method for key aircraft actions.

[0044] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0045] The present invention realizes efficient modification of aircraft model animation and adaptive display of key actions of multi-type and multi-target aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 This is a flow chart of a method for adaptively displaying key aircraft actions based on Petri nets provided by an embodiment of the present invention;

[0048] Figure 2This is a general block diagram of a Petri net-based adaptive display method for aircraft key actions provided by an embodiment of the present invention;

[0049] Figure 3 1 is a schematic diagram of a hierarchical nested structure of an aircraft flight test decomposition according to an embodiment of the present invention;

[0050] Figure 4 This is a parameterized schematic diagram of component behavior of a certain type of rocket provided by an embodiment of the present invention;

[0051] Figure 5 Schematic diagram of the flight attitude control subnet structure provided by an embodiment of the present invention;

[0052] Figure 6 This is a flow chart of aircraft flight action control provided by an embodiment of the present invention;

[0053] Figure 7 Schematic diagram of the key action deduction subnet structure provided by an embodiment of the present invention;

[0054] Figure 8 Schematic diagram of the basic unit structure of the key action deduction subnet provided by an embodiment of the present invention;

[0055] Figure 9 This is a schematic diagram of the residual token cleaning subnet structure provided by an embodiment of the present invention;

[0056] Figure 10 Schematic diagram of the structure of the adaptive drive control Petri net model provided by an embodiment of the present invention;

[0057] Figure 11 This is a block diagram of a Petri net-based adaptive display system for aircraft key actions provided by an embodiment of the present invention;

[0058] Figure 12 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0060] An embodiment of the present invention provides a method for adaptively displaying key aircraft actions based on Petri nets. The method can be implemented by an electronic device, which can be a terminal or a server. Figure 1 The flow chart of this method is shown in FIG. Figure 2 The overall block diagram of the method is shown below. The processing flow may include the following steps:

[0061] S1. Decompose the aircraft flight test into a hierarchical nested structure of "aircraft-first-level critical action-second-level critical action-...-component behavior";

[0062] Optionally, the S1 specifically includes:

[0063] Traverse all key action lists in the aircraft key action behavior library and determine whether the current key action behavior list meets the requirements of this aircraft flight test:

[0064] If the conditions are met, the aircraft flight test is directly decomposed according to the key actions in the current key action list;

[0065] If this is not satisfied, there are two situations:

[0066] In the first case, if some key actions in multiple key action lists can be combined to meet the requirements of this flight test, a new key action list for this aircraft is added to the aircraft key action behavior library, which contains the combination of multiple key actions in the library, and this flight test is decomposed according to the newly added list;

[0067] In the second case, this flight test has new key actions, and the combination of some key actions in multiple key action lists still cannot meet the requirements of this flight test. In this case, after adding the key action list of this aircraft to the aircraft key action behavior library, the new key actions are recursively decomposed, and the secondary key actions are used to decompose the new key actions one by one, and finally the aircraft flight test is decomposed into a hierarchical nested structure of "aircraft-first-level key actions-second-level key actions-...-component behaviors".

[0068] The embodiment of the present invention decomposes the aircraft flight test into a hierarchical nested structure of "aircraft-first-level key action-second-level key action-...-component behavior" as shown in the following example: Figure 3 shown.

[0069] S2. Parameterize the behavior of aircraft components based on the key aircraft motion constraints;

[0070] Existing key aircraft actions are usually displayed in the form of frame animations. The strong "model-time" correlation makes frame animations difficult to adjust and modify (① and ② in Table 1). Therefore, the embodiment of the present invention parameterizes model resources and behaviors to achieve decoupling of three-dimensional models and time, thereby improving the efficiency of animation modification (③ in Table 1).

[0071] Table 1 Comparison of the difficulty of modifying frame animation and parametric animation

[0072]

[0073] Optionally, the S2 specifically includes:

[0074] S21. Make the following constraints on the key actions of the aircraft:

[0075] ① The aircraft is composed of various components, and there is a hierarchical relationship between the components. The components that behave first are at a lower level, and the components that behave later are at a higher level. Adjacent levels are connected by model binding.

[0076] ② The behavior of the component conforms to the laws of rigid body kinematics, which is a linear combination of two basic motions: translation and rotation;

[0077] ③The aircraft is composed of various component models in a hierarchical relationship;

[0078] ④ The tail flame of the component is realized by particle effects. As a special component, it does not follow constraint ②;

[0079] S22. Based on the above constraints, parameterize the behavior of aircraft components:

[0080] <Unit name,resource,offset,orient,time,end_offset,end_orient,visible>

[0081] The parameter Unit represents the aircraft component; resource represents the component resource variable, and the variable value is the 3D model resource path; offset and end_offset represent the translation movement of the component behavior; orient and end_orient represent the rotation movement of the component behavior; time represents the duration of the behavior; visible represents whether the component is displayed or hidden;

[0082] S23. Based on the above constraints, parameterize the tail flame of the component:

[0083] <Fx name,type,offset,color,start_size,end_size,length,duration,visible>

[0084] The parameter Fx represents the tail flame; offset represents the offset between the tail flame and the bound component; start_size and end_size represent the change in the tail flame range; length represents the length of the tail flame; duration represents the life cycle of the tail flame particle; and visible represents the display or hiding of the particle effect.

[0085] The embodiment of the present invention takes a certain type of rocket as an example. The rocket consists of 7 Units and 3 Fxs. The behavior of its components is parameterized as follows: Figure 4 shown.

[0086] S3. Add the parameterized aircraft component behaviors to the aircraft key action behavior library;

[0087] S4. Using an adaptive drive control Petri net model, the aircraft component behaviors in the aircraft key action behavior library are driven and controlled to achieve adaptive display of the aircraft key actions.

[0088] The aircraft key action behavior library is relatively static and fragmented, and it is necessary to design a real-time, accurate, flexible and efficient drive control method for the key action animation to achieve a coherent and beautiful dynamic effect and realize the adaptive display of key actions of multi-target and multi-type aircraft. Therefore, an embodiment of the present invention designs an adaptive drive control Petri net model based on Petri net to drive and control the behavior of aircraft components in the aircraft key action behavior library to realize the adaptive display of aircraft key actions.

[0089] Optionally, the adaptive drive control Petri net model consists of a flight posture control subnet, a key action deduction subnet and a residual token cleaning subnet, the flight posture control subnet is connected in parallel with the key action deduction subnet, and the key action deduction subnet and the residual token cleaning subnet are coupled to each other;

[0090] The flight attitude control subnet is used to adjust the position and attitude of the aircraft in real time according to the attitude data received by the system throughout the test;

[0091] The key action deduction subnet is used to correctly deduce the key actions of different types of aircraft so that the aircraft can complete the key action demonstration of the test;

[0092] The residual token cleaning subnet is used to clean up the residual data tokens in the key action deduction subnet, so that the key action deduction subnet can be reused in multi-target aircraft tests.

[0093] Alternatively, as Figure 5 As shown, the flight posture control subnet consists of three transitions t1, t2, and t3 (e.g., Figure 5 , usually denoted as t symbol), the corresponding three places s1, s2, s3 for storing data tokens (such as Figure 5In the figure, the data token is transferred to s2 after t1 is executed, and s2 and t2 form a self-loop. t3 is constrained by s2 and s3 at the same time. After t3 is executed, the token is transferred to s4, which is represented by Petri net Σ=(S,T;F,K,W,M0), K is the capacity function, which represents the maximum value of the data token stored in the place s∈S. If not specifically marked, the default value is infinite; W is the weight function, which makes each directed arc f∈F correspond to a positive integer. If not specifically marked, the default value is 1; M is the resource function, which represents the resource distribution of the network. M0 is the initial resource distribution in the network, M(s1)=M(s2)=M(s3)=M(s4)=0; for X=S∪T, · x={y|y∈X∩(y,x)∈F} is the front set of x, x · ={y|y∈X∩(x,y)∈F} is the subsequent set of x. When s1 receives the "takeoff" command, M(s1)=1. The condition for triggering transition t is as follows: The aircraft takes off; then according to formula (2), after transition t occurs, the global resource changes to: A resource change occurs in the Petri net; then s2 obtains a token, and the aircraft adjusts its posture. Since this is a self-loop structure, the aircraft continuously adjusts its posture under the alternating action of formulas (1) and (2); until s3 receives a "stop" command, causing s2 to lose the token and the aircraft to stop. The process is as follows: Figure 6 shown.

[0094] Alternatively, as Figure 7 As shown, the key action deduction subnet is composed of multiple basic units i with symmetrical structures, such as Figure 8 As shown, each basic unit i contains transition t i and the corresponding places i , for the change i Set the corresponding "dummy" transition t i ' and the corresponding library s i ', change t i After execution, the data token is sent to the library s i and s i 'Flow, change i 'After execution, the data token is sent to the library s i ' and s i Flow, in addition, in the transition t i and t i 'Set up two more libraries s 0i With s 0i ',t i Connect to s 0i , s 0i With ti ' are connected by constraint arcs, t i 'Connect to s 0i ',s 0i 'with t i They are connected by constraint arcs, where "dumb" transitions correspond to transitions. After execution, no action occurs, and there is no actual model animation. Constraint arcs implement logical "not". When there is no data token in the place or all data tokens are lost, the corresponding transition is triggered.

[0095] Connect multiple basic units end to end and set up the total storage place S T With all changes j , j = 1, 2, ... connected, corresponding to the total library S T 'With all "dumb" transitions j ', j = 1, 2, ... are connected to form the key action deduction subnet, which drives the control of the aircraft model animation with real-time data to achieve the effect of adaptive deduction of key actions. Assuming that the flight experiment includes 4 key actions, the transition set T = {t1, t2, t3, t4} is the complete set of key actions in the aircraft key action behavior library, and T' = {t'1, t'2, t'3, t'4} corresponds to T and is the corresponding "dummy" transition. Assuming that there are two aircraft A and B, the driving control logic of the key action deduction subnet is:

[0096] Assume that their respective key action deduction paths are: A =t1→t2→t3→t4, Ψ B =t1→t3→t4, for Ψ A , library s T Receive 4 data tokens, according to formula (1) and (2), the transitions t1, t2, t3, and t4 are triggered in sequence, and A completes all key actions, such as Figure 7 As shown by the dotted arrow; for Ψ B , library s T Receive 1 data token, according to formula (1), transition t1 is triggered, according to formula (2) data flow, then library s' T Automatically put in 1 data token, triggering transition t'2, until the library s T Receive the data token again and get the path and B completes all key actions, such as Figure 7 Indicated by solid arrow.

[0097] In a multi-target flight test, if aircraft A and B each complete all their critical maneuvers, the integrated situation display system will need to load seven critical maneuver simulation animations. After optimization using the present invention, three critical maneuver modules, t1, t3, and t4, are reused by modifying component behavior parameters in real time. This reduces the number of loaded critical maneuver simulation animations to four, significantly improving display efficiency.

[0098] For a new type of aircraft, if its key actions are not available in the behavior library, you can Figure 7 The key action of the deduction subnet is to insert the basic unit. The insertion principle is the same as the linked list data structure, and the theoretical insertion efficiency is O(1), which makes Figure 7 The key action deduction subnet is easily expandable to new types of aircraft.

[0099] Alternatively, as Figure 9 As shown, the residual token cleaning subnet, for each basic unit of the library s 0i With s 0i ', two transitions and one place are added accordingly to construct a logical "OR" Petri net structure, and then a transition is used to connect the calculation results of all "OR" structure Petri nets to form the residual token cleaning subnet, so that network reuse can be achieved when multiple target aircraft are flying.

[0100] The flight posture control subnet is connected in parallel with the key action deduction subnet, and the key action deduction subnet is coupled with the residual token cleaning subnet to form the adaptive drive control Petri net model, as shown in Figure 10 shown.

[0101] like Figure 11 As shown, an embodiment of the present invention further provides an aircraft key action adaptive display system based on Petri nets, the system comprising:

[0102] A decomposition module 1110 is used to decompose the aircraft flight test into a hierarchical nested structure of "aircraft-first-level key action-second-level key action-...-component behavior";

[0103] A parameterization module 1120 is used to parameterize the behavior of aircraft components based on key aircraft motion constraints;

[0104] An adding module 1130 is used to add the parameterized aircraft component behavior to the aircraft key action behavior library;

[0105] The adaptive display module 1140 is used to use the adaptive drive control Petri net model to drive and control the aircraft component behaviors in the aircraft key action behavior library to achieve adaptive display of the aircraft key actions.

[0106] An embodiment of the present invention provides an aircraft key action adaptive display system based on Petri nets, and its functional structure corresponds to an aircraft key action adaptive display method based on Petri nets provided by an embodiment of the present invention, which will not be repeated here.

[0107] Figure 12 It is a structural diagram of an electronic device 1200 provided in an embodiment of the present invention. The electronic device 1200 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 1201 and one or more memories 1202, wherein at least one instruction is stored in the memory 1202, and the at least one instruction is loaded and executed by the processor 1201 to implement the steps of the above-mentioned Petri net-based adaptive display method of key aircraft actions.

[0108] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory device containing instructions. The instructions are executable by a processor in a terminal to implement the Petri net-based adaptive display method for aircraft key maneuvers. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0109] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit 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 adaptively displaying key aircraft actions based on Petri nets, characterized in that: The method comprises: S1. Decompose the aircraft flight test into a hierarchical nested structure of "aircraft - first-level critical action - second-level critical action - ... - component behavior"; S2. Parameterize the behavior of aircraft components based on the key aircraft motion constraints; S3. Add the parameterized aircraft component behaviors to the aircraft key action behavior library; S4. Using an adaptive drive control Petri net model, driving and controlling the behaviors of aircraft components in the aircraft key action behavior library to achieve adaptive display of aircraft key actions; Said S2 specifically includes: S21. Make the following constraints on the aircraft's key actions: ① The aircraft is composed of various components, and there is a hierarchical relationship between the components. The components that behave first are at a lower level, and the components that behave later are at a higher level. Adjacent levels are connected by model binding. ② The behavior of the component conforms to the laws of rigid body kinematics, which is a linear combination of two basic motions: translation and rotation; ③The aircraft is composed of various component models in a hierarchical relationship; ④ The tail flame of the component is realized by particle effects. As a special component, it does not follow constraint ②; S22. Based on the above constraints, parameterize the behavior of aircraft components: <Unit name,resource,offset,orient,time,end_offset,end_orient,visible> The parameter Unit represents the aircraft component; resource represents the component resource variable, and the variable value is the 3D model resource path; offset and end_offset represent the translation movement of the component behavior; orient and end_orient represent the rotation movement of the component behavior; time represents the duration of the behavior; visible represents whether the component is displayed or hidden; S23. Based on the above constraints, parameterize the tail flame of the component: <Fx name,type,offset,color,start_size,end_size,length,duration,visible> The parameter Fx represents the tail flame; offset represents the offset between the tail flame and the bound component; start_size and end_size represent the change in the tail flame range; length represents the length of the tail flame; duration represents the life cycle of the tail flame particle; and visible represents the display or hiding of the particle effect.

2. The method according to claim 1, characterized in that Said S1 specifically includes: Traverse all key action lists in the aircraft key action behavior library and determine whether the current key action behavior list meets the requirements of this aircraft flight test: If the conditions are met, the aircraft flight test is directly decomposed according to the key actions in the current key action list; If this is not satisfied, there are two situations: In the first case, if some key actions in multiple key action lists are combined to satisfy the current flight test, a new key action list for this aircraft is added to the aircraft key action behavior library. The list contains the combination of multiple key actions in the library, and the current flight test is decomposed according to the newly added list. In the second case, this flight test has new key actions, and the combination of some key actions in multiple key action lists still cannot meet the requirements of this flight test. In this case, after adding the key action list of this aircraft to the aircraft key action behavior library, the new key actions are recursively decomposed, and the new key actions are decomposed one by one using secondary key actions. Finally, the aircraft flight test is decomposed into a hierarchical nested structure of "aircraft-first-level key actions-second-level key actions-...-component behaviors".

3. The method according to claim 1, characterized in that The adaptive drive control Petri net model consists of a flight posture control subnet, a key action deduction subnet and a residual token cleaning subnet. The flight posture control subnet is connected in parallel with the key action deduction subnet, and the key action deduction subnet is coupled with the residual token cleaning subnet. The flight attitude control subnet is used to adjust the position and attitude of the aircraft in real time according to the attitude data received by the system throughout the test; The key action deduction subnet is used to correctly deduce the key actions of different types of aircraft so that the aircraft can complete the key action demonstration of the test; The residual token cleaning subnet is used to clean the residual data tokens in the key action deduction subnet, so that the key action deduction subnet can be reused in multi-target aircraft tests.

4. The method according to claim 3, characterized in that The flight posture control subnet is composed of three transitions t1, t2, and t3 for executing key action model animations, three corresponding places s1, s2, and s3 for storing data tokens, and finally a place s4 for storing data tokens. After t1 is executed, the data token is transferred to s2, and s2 and t2 form a self-loop. t3 is constrained by both s2 and s3. After t3 is executed, the token is transferred to s4. It is represented by a Petri net Σ=(S, T; F, K, W, M0), where K is a capacity function, indicating the maximum value of the data tokens that can be stored in the place s∈S. If not specifically marked, the default value is infinite; W is a weight function, which makes each directed arc f∈F correspond to a positive integer. If not specifically marked, the default value is 1. M is the resource function, which indicates the resource distribution of the network. M0 is the initial resource distribution in the network, M(s1)=M(s2)=M(s3)=M(s4)=0. For X=S∪T, · x={y|y∈X∩(y,x)∈F} is the front set of x, x · ={y|y∈X∩(x,y)∈F} is the subsequent set of x. When s1 receives the "takeoff" command, M(s1)=1. The condition for triggering transition t is as follows: The aircraft takes off; then according to formula (2), after transition t occurs, the global resource changes to: Resources change in the Petri net; then s2 obtains the token, and the aircraft adjusts its posture. Since this is a self-loop structure, under the alternating and repeated effects of formulas (1) and (2), the aircraft continuously adjusts its posture; until s3 receives the "stop" command, causing s2 to lose the token and the aircraft stops.

5. The method according to claim 4, characterized in that The key action deduction subnet is composed of multiple basic units i with symmetrical structures, each of which contains transitions t i and the corresponding places i , for the change i Set the corresponding "dumb" transition t i ' and the corresponding library s i ', change t i After execution, the data token is sent to the library s i and s i 'Flow, change i 'After execution, the data token is sent to the library s i ' and s i Flow, in addition, in the transition t i and t i 'Set up two more libraries s 0i With s 0i ',t i Connect to s 0i , s 0i With t i ' are connected by constraint arcs, t i 'Connect to s 0i ',s 0i 'with t i They are connected by constraint arcs. "Dummy" transitions correspond to transitions. After execution, no action occurs, and there is no actual model animation. Constraint arcs implement logical "not". When there is no data token in the place or all data tokens are lost, the corresponding transition is triggered. Connect multiple basic units end to end and set up the total storage place S T With all changes j , j = 1, 2, ... connected, corresponding to the total library S T 'With all "dumb" transitions j ', j = 1, 2, ... are connected to form the key action deduction subnet, which drives the control of the aircraft model animation with real-time data to achieve the effect of adaptive deduction of key actions. Assuming that the flight experiment includes 4 key actions, the transition set T = {t1, t2, t3, t4} is the complete set of key actions in the aircraft key action behavior library, and T' = {t'1, t'2, t'3, t'4} corresponds to T and is the corresponding "dummy" transition. Assuming that there are two aircraft A and B, the driving control logic of the key action deduction subnet is: Assume that their respective key action deduction paths are: A =t1→t2→t3→t4, Ψ B =t1→t3→t4, for Ψ A , library s T Receive 4 data tokens, according to formula (1) and (2), the transitions t1, t2, t3, and t4 are triggered in sequence, and A completes all key actions; for Ψ B , library s T Receive 1 data token, according to formula (1), transition t1 is triggered, according to formula (2) data flow, then library s' T Automatically put in 1 data token, triggering transition t'2, until the library s T Receive the data token again and get the path and B completes all key actions.

6. The method according to claim 5, characterized in that The residual token cleaning subnet, for each basic unit of the library s 0i With s 0i ', correspondingly add 2 transitions and 1 library to construct a logical "OR" Petri net structure, and then use a transition to connect the calculation results of all "OR" structure Petri nets to form the residual token cleaning subnet.

7. A Petri net-based adaptive display system for aircraft key actions, characterized by: The system comprises: Decomposition module, used to decompose the aircraft flight test into a hierarchical nested structure of "aircraft-first-level key action-second-level key action-...-component behavior"; Parameterization module, used to parameterize the behavior of aircraft components based on the key action constraints of the aircraft; Add a module to add parameterized aircraft component behaviors to the aircraft key action behavior library; An adaptive display module is used to drive and control the behaviors of aircraft components in the aircraft key action behavior library using an adaptive drive control Petri net model to achieve adaptive display of the aircraft key actions; The parameterization module is specifically used to: The following constraints are imposed on the key actions of the aircraft: ① The aircraft is composed of various components, and there is a hierarchical relationship between the components. The components that behave first are at a lower level, and the components that behave later are at a higher level. Adjacent levels are connected by model binding. ② The behavior of the component conforms to the laws of rigid body kinematics, which is a linear combination of two basic motions: translation and rotation; ③The aircraft is composed of various component models in a hierarchical relationship; ④ The tail flame of the component is realized by particle effects. As a special component, it does not follow constraint ②; Based on the above constraints, the behavior of aircraft components is parameterized: <Unit name,resource,offset,orient,time,end_offset,end_orient,visible> The parameter Unit represents the aircraft component; resource represents the component resource variable, and the variable value is the 3D model resource path; offset and end_offset represent the translation movement of the component behavior; orient and end_orient represent the rotation movement of the component behavior; time represents the duration of the behavior; visible represents whether the component is displayed or hidden; Based on the above constraints, the tail flame of the component is parameterized: <Fx name,type,offset,color,start_size,end_size,length,duration,visible> The parameter Fx represents the tail flame; offset represents the offset between the tail flame and the bound component; start_size and end_size represent the change in the tail flame range; length represents the length of the tail flame; duration represents the life cycle of the tail flame particle; and visible represents the display or hiding of the particle effect.

8. An electronic device comprising a processor and a memory, wherein the memory stores at least one instruction, characterized in that: The at least one instruction is loaded and executed by the processor to implement the Petri net-based adaptive display method for key aircraft actions as described in any one of claims 1-6.

9. A computer-readable storage medium, wherein at least one instruction is stored in the storage medium, characterized in that: The at least one instruction is loaded and executed by the processor to implement the Petri net-based adaptive display method for key aircraft actions as described in any one of claims 1-6.

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