CN113919068B - Task-based aviation equipment support system simulation evaluation method - Google Patents
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Abstract
The invention belongs to the technical field of aviation equipment support systems, and particularly relates to a task-based aviation equipment support system simulation evaluation method. The method comprises the following steps of: determining design parameters of an aviation equipment support system simulation optimization model and an optimization target to be evaluated; step 2: performing first abstraction on a physical system, and establishing an aviation equipment support system conceptual model; step 3: performing second abstraction on the basis of the conceptual model, and establishing an aviation equipment support system entity model; step 4: according to the entity model of the aviation equipment support system established in the step 3, a multi-stage task-oriented model is further established; step 5: according to the entity model of the aviation equipment support system established in the step 3, further establishing an equipment support model; step 6: establishing a guarantee business process; step 7: and establishing a simulation deduction calculation evaluation model, and performing simulation analysis evaluation and guarantee efficiency evaluation.
Description
Technical Field
The invention belongs to the technical field of aviation equipment support systems, and particularly relates to a task-based aviation equipment support system simulation evaluation method.
Background
With the deep advancement of army actual combat training, the use intensity of various warplanes is greatly increased, the guarantee capability is formed as soon as possible by limited resources, and the improvement of the guarantee working efficiency is a new opportunity and a new challenge for equipment maintenance and guarantee work.
The research of the equipment support system oriented to the multi-stage task has practical significance, because the process of completing the combat task does not need to pay special attention to the completeness or non-completeness of a specific equipment, but focuses on maintaining the completeness of the configuration of the task equipment. The following five purposes can be achieved by carrying out simulation evaluation on the guarantee system:
firstly, analyzing the use scheme of equipment, and determining equipment guarantee activities which should be provided; secondly, evaluating a plurality of maintenance and guarantee schemes and determining an optimal scheme; optimizing resource supply, allocation and use strategies; fourthly, evaluating the guarantee efficiency of the maintenance mechanism and optimizing the maintenance process; fifthly, analyzing maintenance and guarantee bottlenecks affecting completion of combat training tasks, and timely adjusting to ensure completion of the tasks. Therefore, the simulation evaluation of the system guarantee of the aviation equipment has important practical significance.
The basic elements constituting the equipment guarantee system comprise guarantee resources, maintenance mechanisms and maintenance rules. The guarantee resource is an entity constituting the equipment guarantee system, and is a basic means for implementing the guarantee. The function of the guarantee system is to complete maintenance tasks and convert equipment to be maintained into equipment with technical conditions meeting the specified requirements. In the process, various related combat training task requirements, information, materials and the like are required to be input. The ability to secure a system depends on both its constituent elements and interrelationships, as well as on external environmental factors.
Therefore, the change of the system state is ensured to occur at certain discrete time points or quantization intervals, modeling is focused on describing events which cause the system state to change and determining logic relations related to each type of events, and a simulation main line is characterized in that the change of the system state is triggered according to the logic relations of various events in a certain time sequence, so that the system state is dynamically written, and evolution and emergence rules of the system state are explored.
In the equipment guarantee system, the system state is driven by discrete events, so that the system is discrete; the system state is influenced by a plurality of random factors at the same time, so that the dynamic randomness of the system is caused; the system state increases exponentially with the increase of the characteristic parameters, resulting in the complexity of the system; the system state evolves with the change of boundary and demand, resulting in the adaptability and the purpose of the system.
Therefore, the equipment support system is a discrete, dynamic, complex and evolution system, and the relevant elements of the system are organically combined according to actual operation logic by combining an analytic model and simulation modeling, so that the state and the behavior of the system are truly reflected.
Disclosure of Invention
Aiming at the technical problems, the invention provides a task-based aviation equipment support system simulation evaluation method, which firstly determines the characteristics of an aviation equipment support system and main problems of support system simulation optimization solution, determines design parameters of an aviation equipment support system simulation model and an optimization target to be evaluated, performs first abstraction on a real physical system, and establishes a task equipment decomposition mapping model, a support service intelligent model and a simulation deduction evaluation model; through research, a foundation can be laid for deep propulsion of the system guarantee modeling and analysis of the aviation equipment, and support is provided for high-efficiency and accurate implementation of the assessment, control, overall planning and optimization of the maintenance guarantee capability of the modern aviation equipment system.
The technical scheme adopted by the invention is as follows:
a task-based aviation equipment support system simulation evaluation method comprises the following steps:
step 1: determining design parameters of the simulation optimization model of the aviation equipment support system and an optimization target to be evaluated, namely inputting and outputting the simulation optimization model of the aviation equipment support system;
step 2: carrying out first abstraction on a real physical system on the basis of an optimization target to be evaluated of the simulation optimization model of the aviation equipment support system determined in the step 1, and establishing an aviation equipment support system conceptual model comprising three parts of task sources, support task implementation and environment information input;
step 3: performing second abstraction on the basis of the aviation equipment support system conceptual model established in the step 2, and establishing an aviation equipment support system entity model comprising an equipment system model, an equipment support system model, an equipment base model, an equipment scene instance model and an Agent model;
step 4: according to the entity model of the aviation equipment support system established in the step 3, a multi-stage task-oriented model is further established;
step 5: according to the entity model of the aviation equipment support system established in the step 3, further establishing an equipment support model;
step 6: taking the multi-stage task-oriented model established in the step 4 as an object, taking multi-stage combat task propulsion as a logic main line, and decomposing and mapping combat tasks layer by layer to basic equipment units, so as to establish a guarantee business process;
step 7: and establishing an HLA-based simulation deduction calculation evaluation model, and performing simulation analysis evaluation and guarantee efficiency evaluation on the operation efficiency of the maintenance and guarantee business.
Preferably, in the step 1, firstly, determining a problem to be solved by simulation optimization of an aviation equipment support system, forming a task required equipment configuration, a connection relation between the equipment configurations and a conversion logic under the driving of a multi-stage task and a logic conversion relation thereof, and further establishing a task-oriented aviation equipment support system model;
after the aviation equipment support system model is established, the input of the aviation equipment support system simulation optimization is divided into two types, wherein one type is support capability parameters of equipment units, and the other type is task and environment parameters facing tasks; the output of the simulation optimization is equipment system guarantee parameter and system task success rate parameter.
Preferably, in the step 2, the abstract conceptual model determines the research scope and the overall situation of the aviation equipment security system, including the source, time, boundary, object, resource and flow of the task. Preferably, in the step 3, various functional entity models that can be interactively accessed by the simulation system are further abstracted from the components of the established conceptual model, and the entity model of the aviation equipment support system is established.
Preferably, in the step 4, a multi-stage task model is built for the whole task flow, task time sequence, information flow, used equipment, connection relation among the equipment and mutual influence of the equipment system model according to the task flow, task phase division and task execution process of the equipment system model;
step 4.1: establishing an equipment system task model, wherein the equipment system task is defined by a plurality of stage tasks and logic conversion relations thereof, and mapped to an equipment unit and a basic equipment unit layer by layer;
step 4.2: establishing an equipment unit task model, wherein the equipment unit task is defined by tasks of the basic equipment unit in a plurality of stages and logic conversion relations thereof;
step 4.3: and establishing a basic equipment unit task model, mapping basic aviation equipment units to single equipment, and modeling basic equipment unit tasks.
Preferably, in the step 5, the equipment support system modeling includes a support command model, a support monitoring model, an equipment maintenance model, an equipment supply model, an ammunition supply model and a basic model of the integrated support system, and after the equipment support task is dispatched, the corresponding model triggers a support event to advance a support activity to mobilize the corresponding support resource.
Preferably, in the step 6, an HLA-based simulation deduction calculation evaluation model is established, activity, event and time data of each entity SOM are recorded, redis high-speed data caching is adopted to process calculation process data, the calculation process data are stored in a simulation calculation process data set to be uniformly managed, data storage, data analysis and evaluation optimization are adopted to perform simulation analysis and evaluation on maintenance and guarantee service operation efficiency, and a four-level index system is adopted to evaluate guarantee efficiency.
Compared with the prior art, the invention has the beneficial effects that:
1. the comprehensive utilization and maintenance support evaluation problems of multiple types of aviation equipment for completing a certain multi-stage combat task are solved.
2. A complex system business simulation key flow is constructed, and agent-based simulation entity and business process development are constructed.
3. And establishing a task equipment decomposition mapping model, a guarantee service agent model and a simulation deduction calculation evaluation model. The method can lay a foundation for simulating and evaluating the deep propulsion aviation equipment support system.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is an input and output diagram of the simulation optimization problem description of the aircraft equipment support system of the present invention.
FIG. 3 is a diagram of an Agent development process of the aircraft equipment support system of the present invention.
FIG. 4 is a task composition diagram of an avionics system of the present invention.
FIG. 5 is a task model diagram of an avionics architecture of the present invention.
FIG. 6 is a task model diagram of an avionics unit in accordance with the present invention.
FIG. 7 is a task model diagram of an aircraft equipment base unit according to the present invention.
FIG. 8 is a diagram of an aircraft equipment repair agent model according to the present invention.
FIG. 9 is a diagram of an in-site repair process according to the present invention.
Fig. 10 is a diagram of a distributed simulation evaluation process based on HLA according to the present invention.
FIG. 11 is a flow chart of the maintenance and assurance service of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A task-based aviation equipment support system simulation evaluation method is characterized by comprising the following steps of: comprising the following steps:
step 1: the main problem to be solved in describing the simulation optimization model of the aviation equipment support system is to form equipment configuration required by a task, connection relation among the equipment configuration and conversion logic under the driving of a multi-stage task and logic conversion relation thereof; establishing a task-oriented support system operation model; during the task propulsion process, equipment and equipment configuration generate random faults and combat damages, and the maintenance and guarantee process is controlled to optimize a guarantee system. The problem is solved by following the basic principle of Monte Carlo simulation, namely, a random process involved in the promotion of a construction system, pseudo-random numbers are generated from known probability distribution sampling, unbiased estimation amounts are established, and evaluation and optimization are carried out on the basis.
And then determining design parameters of the simulation model of the aviation equipment support system and an optimization target to be evaluated, namely, input and output of the simulation model of the aviation equipment support system.
The input of the simulation model of the aviation equipment security system is divided into two types, wherein one type is security capability parameters of the equipment unit, such as average fault interval time MTBF, average serious fault interval time MTBCF, average maintenance time MTTR, security resource delay time LDT, management delay time ADT and the like; the other type is task and environment parameters facing to tasks, such as a multi-stage task PMS, environment disturbance Evn, guarantee command and control C2 and the like;
the output of the simulation model of the aviation equipment support system is equipment system support parameters and system task success rate parameters, such as the integrity rate R of the aviation equipment system rrsos Availability of aircraft equipment system A osos Task duration probability R of aviation equipment system mcsos PMS task success rate MC, etc.
An abstract description of the simulation optimization problem of the aviation equipment support system is shown in fig. 2. Wherein Mtbf is the average inter-fault time; mtbf mean critical fault interval time, MTTR mean maintenance time, LDT logistic delay time, ADT supply delay; PMS multistage task; EVN environmental parameters; c2 command control; success rate of Rrrsos task system; the Aosos system uses the availability Rmcsso system task duration probability; MC task success rate.
In addition, the RMS parameter model at the equipment unit level has existing mature results, and is not described herein, and the invention only describes the system level parameter calculation:
R rrsos the calculation formula:
wherein N is r For the number of intact systems, N t The number of equipment units constituting the system;
A osos the calculation formula:
wherein the availability of the aviation equipment system is denoted as A osos ，Tava ij Representing the availability time of the jth device architecture of the ith task stage, MT_unava ij LDT_unava for the time that the jth equipment architecture is unavailable for maintenance reasons in the ith task stage ij For the time when the jth equipment system is unavailable in the ith task stage due to the guarantee delay;
R mcsos the calculation formula:
R mcsos ＝P(r≥T)＝
P((t 1 ≥T 1 )(t 2 ≥T 2 )…(t i ≥T i )…(t n ≥T n ))＝
P((t n ≥T n )|(t n-1 ≥T n-1 )…(t 2 ≥T 2 )(t 1 ≥T 1 ))
…P((t n-i ≥T n-i )|(t n-i-1 ≥T n-i-1 )…(t 2 ≥T 2 )(t 1 ≥T 1 ))
…P((t 2 ≥T 1 )|(t 1 ≥T 1 ))P(t 1 ≥T 1 ) (3)
wherein t is the time before the task of the equipment system is interrupted; t is a specified equipment hierarchy task duration; t is t i ≥T i The task intensity of the i-th stage configuration equipment constituting the equipment system is characterized.
PMS task success rate MC calculation formula:
wherein N is c To number of successful system tasks, N s To construct the number of simulations.
The security analysis mainly focuses on parameter correlation and sensitivity analysis, takes the input and output of a simulation model as index control, and optimizes the success rate requirement of a security system to achieve a mission task through command control.
Step 2: according to the optimization target to be evaluated of the aviation equipment support system simulation model determined in the step 1, it can be further seen that aviation equipment support system simulation realizes efficient allocation and use of support resources and evaluation optimization of a support scheme through construction and research of the model, so that the requirement of aviation equipment support system simulation model establishment abstracts the aviation equipment and a real physical system of a support system thereof to form a conceptual model of the support system. The establishment of a conceptual model is the first abstraction of a physical system of reality, and forms basic elements such as entities, relations, behaviors, environments and the like related to a system.
The concept model can determine the research scope and the overall situation of the aviation equipment support system, and is mainly divided into three parts, namely a task source, support task implementation and environment information input, wherein the three parts comprise the source, time, boundary, object, resource and flow of the task.
Step 3: in order to realize the evaluation and optimization of the guarantee process in the computer system, various functional entity models which can be interactively accessed by the simulation system are further abstracted from all the components described by the abstract conceptual model, wherein the functional entity models comprise a static entity model of an aviation equipment guarantee system of an equipment system model, an equipment guarantee system model, an equipment basic model, an equipment scene instance model and an Agent model;
the guarantee flow model is a description of the principle and procedure followed by the requirements of the guarantee elements, such as maintenance grades, maintenance institutions and the like; the basic model is used for describing weapon equipment, maintenance mechanisms, guarantee resources and the like; a scene instance model is a three-dimensional entity representing a safeguard object. The Agent model mainly represents a computing entity which can continuously and autonomously play roles and has the characteristics of initiative, reactivity, autonomy and the like. The aircraft equipment support system agent development process is shown in fig. 3.
Step 4: according to the entity model of the aviation equipment support system established in the step 4, a multi-stage task oriented model is further established to be a dynamic flow model, and modeling of multi-stage tasks is performed by describing the task flow, task stage division and task execution process of the aviation equipment system, so that the whole task flow, task time sequence, information flow, used equipment and connection relation and interaction among all equipment of the aviation equipment system are modeled.
Describing the task, the task equipment architecture is composed as shown in fig. 3. The task equipment system is composed of different equipment units to complete specific mission tasks, such as accurately striking the army base of a country outside the defending area, and the equipment units of the fire striking, information support, information fight, command control and the like are required to cooperatively complete the fight tasks. Taking an information supporting equipment unit as an example, task targets comprise acquisition of target images, positions, surrounding situations and enemy air defense system information, air early warning monitoring and air command platform construction near an air defense area.
The equipment unit consists of basic equipment, the basic equipment unit is the minimum unit capable of independently executing the combat task, and consists of a single equipment system or a homotype equipment system group and a guarantee system, and the fire hitting equipment unit for the precise hitting task outside the defending area consists of a bomber or a bomber formation. The basic battle unit is configured with an accompanying guarantee repair group, and the battle unit is configured with a battle field rush repair team to jointly form an equipment guarantee system.
Step 4.1: an equipment system task model is built, as shown in fig. 5, wherein the equipment system task is defined by a plurality of stage tasks and logic conversion relations thereof, and the stage tasks are mapped to the equipment units and the basic equipment units layer by layer. The equipment system task covers the task of each equipment unit, and the equipment units provide different combat capabilities in the equipment system, mutually influence and restrict, have dynamic characteristics and change along with the time advance and the change of task execution conditions. The equipment unit tasks cover the tasks of the individual basic equipment units, but are not equivalent to the superposition of the individual basic equipment unit tasks, the basic equipment units generally constituting a k/n redundancy configuration. After the task is issued, the minimum configuration of the equipment system at each stage is determined, so that the system configuration is superior to a threshold value required by the task in order to ensure that the task is continuously completed, namely the task intensity is not less than the required intensity S, and the stage task intensity can be characterized by the required equipment working time with a certain configuration. When equipment forming the system fails with a certain probability, the maintenance and guarantee system operation cannot maintain the threshold value of the system configuration, and the system cannot continuously execute tasks.
Step 4.2: the method comprises the steps of establishing an equipment unit task model, taking equipment system task input and equipment unit task intensity as constraints, defining equipment unit tasks by tasks of basic equipment units in a plurality of stages and logic conversion relations thereof, and performing simulation optimization on an aviation equipment support system, wherein the aim of performing comparison analysis on different support schemes and providing implementation suggestions is precisely achieved, so that the intensity requirements of the equipment units can be met again with the fastest minimum resource consumption when the basic equipment units fail. As shown in fig. 6, assuming that the task intensity of the equipment unit vi is required to be 2/4 and the task intensity of the equipment unit i is required to be 1/3 in the f-stage and h-stage of the task, the task profile of the equipment unit may meet the task requirement in the f-stage, and the task intensity of the equipment unit vi may not meet the task requirement in the h-stage although the task intensity of the equipment unit i meets the task requirement in the h-stage, so that the task of the h-stage fails, and thus the task of the equipment system also fails.
Step 4.3: the basic equipment unit task is modeled, namely the basic aviation equipment unit is generally mapped to single equipment, a basic aviation equipment unit task model is shown in fig. 7, and after the basic equipment unit task is modeled, the pre-flight preparation time, the task flight time, the fault maintenance time, the fault waiting spare part time, the re-starting preparation time, the post-flight inspection time, the task success judgment point and the like are defined. For example, basic aviation equipment units are mapped to a certain type of fighter, and during the task execution process of the fighter, a secondary system and components thereof forming the fighter generate faults or combat losses in a certain model, and the fighter must be returned to the field for maintenance or be disabled, so that the continuous progress of the task is affected.
The base equipment unit in performing the multi-stage mission, pre-flight preparation time T 1 ＝t 1 -t 0 ；t 1 Starting the maneuver at the moment t 2 Executing the fight task in the space domain of the moment arrival task, and maneuvering time T 2 ＝t 2 -t 1 ＝T 4 ＝t 4 -t 3 The method comprises the steps of carrying out a first treatment on the surface of the Effective support time T for performing tasks on equipment units 3 ＝t 3 -t 2 The method comprises the steps of carrying out a first treatment on the surface of the Time of fault maintenance T 5 ＝t 5 -t 4 The method comprises the steps of carrying out a first treatment on the surface of the Maintenance waiting spare part time T 6 ＝t 6 -t 5 The method comprises the steps of carrying out a first treatment on the surface of the Readiness time to again start T 7 ＝t 7 -t 6 The method comprises the steps of carrying out a first treatment on the surface of the The successful judgment point of the stage task is the moment when the equipment unit continuously meets the strength requirement and reaches stage conversion. During the execution of a task by an equipment system, the system does not pay excessive attention to the completion of a basic equipment unitIn a good state, only whether the task strength of the equipment unit is satisfied is required to be concerned, so that comprehensive guarantee resources and scheduled service objects are transferred from traditional rough guarantee oriented to single equipment to fine guarantee oriented to an equipment system, and the comprehensive guarantee resources and the scheduled service objects are basic departure points and foothold points of follow-up simulation optimization.
Step 5: and (3) further establishing an equipment guarantee model according to the entity model of the aviation equipment guarantee system established in the step (3), and implementing the process and the step for equipment guarantee. After the equipment security tasks are distributed, the corresponding models trigger security events, and the security activities are advanced to mobilize the corresponding security resources.
Specifically, step 3 establishes an aviation equipment support system entity model of the Agent model, taking an equipment Agent and an equipment maintenance Agent as examples, the equipment Agent inputs maintenance information to the equipment maintenance Agent, the maintenance information comprises preventive maintenance, natural fault and rescue, and the equipment maintenance Agent completes maintenance tasks after receiving the information.
Internal construction As shown in FIG. 8, the Agent function includes creating a maintenance work tree to manage maintenance and usage activities, recording maintenance work attributes and associated maintenance work models. The maintenance function takes the occurrence of a guarantee event and the promotion of a guarantee activity as carriers, wherein a guarantee event model comprises the automatic synchronization of a guarantee work tree and the attribute configuration of the guarantee event, and a guarantee activity model comprises the automatic synchronization of the guarantee work tree and the definition of the guarantee activity.
The process drawing of the guarantee activity stage is the bottom layer abstraction of the organization implementation guarantee activity, is the detailed description of the maintenance process, and takes the aircraft repairability maintenance process as an example, and comprises in-situ direct maintenance, replacement maintenance process and additional disassembly maintenance process. The equipment failure can be repaired by replacing one or more components, or by directly repairing an unremovable part of the equipment, and the components can be repaired by directly repairing or replacing the next-stage failed component. The in-site repair procedure is shown in fig. 9. And meanwhile, the specific time consumption of a direct maintenance process, a replacement maintenance process and an additional disassembly process model, the component failure rate and the like are also calculated.
Step 6: taking the multi-stage task-oriented model established in the step 4 as an object, taking multi-stage combat task propulsion as a logic main line, and decomposing and mapping combat tasks layer by layer to basic equipment units, so as to establish a guarantee business process; and along with the progress of task time, converting the equipment system to execute the task according to the task requirement. In the task process, a reliability model of the equipment replaceable unit is used as a fault mechanism to trigger natural faults, and corresponding repairability maintenance tasks are generated; generating corresponding preventive maintenance tasks by taking the equipment security event model as a trigger mechanism, and conveying equipment to a maintenance site to execute maintenance security activities; because of different maintenance institutions, equipment maintenance is usually carried out by an accompanying guarantee repair group, and if the maintenance capability is insufficient, a battlefield rush-repair team is required to be scheduled to be completed on site; if the equipment still cannot be repaired, the equipment is sent to a maintenance factory or a major repair factory to complete equipment maintenance; in the equipment maintenance process, required guarantee resources, aviation material supply and the like are continuously invoked. Returning to the equipment unit after equipment repair continues to perform the combat task until the equipment architecture task is completed, as shown in particular in fig. 11.
Step 7: an HLA-based simulation deduction calculation evaluation model is established, and as shown in fig. 10, an HLA-based distributed simulation system is the basis of simulation calculation deduction. After the deduction definition of the simulation experiment service is completed, the FOM provides simulation federation service, the FOM is driven by a time line and an event line, the time line controls the task of the stage to advance, and the event line controls the event which occurs and corresponds to the time line, namely, the event is advanced to the corresponding time to occur. After FOM initiation, the SOM begins initialization, including IP registration, SOM object initialization, message subscription, and event registration. Aiming at various entities and focused core agents, distributed deployment, communication, calculation and analysis are realized through corresponding SOMs. According to the requirements of simulation service, the SOM is divided into a task decomposition SOM, a command management SOM, an equipment maintenance SOM, an aviation material supply SOM and a service monitoring SOM, and various SOMs are mapped to corresponding entities, and the SOMs define Agent agents according to whether the entities have logic-state attributes or not.
And along with the propulsion of the time main line, various aircraft system models, aircraft task models, guarantee resource models and the like are called to finish the guarantee tasks. The business process of the equipment maintenance support system is the behavior participated by the human body, the states of the activities and the events are diversified, and the control of the activities and the events becomes the key of a trigger mechanism. The successor node is activated only if the previous activity is in the end state. The trigger mechanism based on the event is adopted to solve the starting, executing and stopping of daily use tasks or maintenance guarantee tasks, and the tasks are pushed to be carried out by means of a simulation engine along with the execution of the tasks which are completed in the sequence defined by the activities.
In the simulation calculation process, the activity, event and time data of each entity SOM are recorded, the Redis high-speed data cache is adopted to process the calculation process data, and the calculation process data are stored in a simulation calculation process data set for unified management.
The simulation analysis and evaluation is divided into three parts of data storage, data analysis and evaluation optimization, and the operation efficiency of the maintenance and guarantee service is subjected to simulation analysis and evaluation, wherein the data storage is uniformly stored and managed aiming at a process data flow table and a data entity table; the data analysis builds a scientific index system aiming at different guarantee action characteristics and rules, selects a reasonable algorithm to generate evaluation data, provides references and bases for modification of a guarantee scheme, optimization of guarantee force, establishment of a guarantee system, rationality of a task plan and the like, and provides various index data required by evaluation.
The guarantee efficiency evaluation adopts a four-level index system, namely a task completion capacity index, a task supporting capacity index, a comprehensive guarantee capacity index and an equipment unit capacity index. Corresponding to different requirements of security capability, the command and evaluation mechanism maintains a plurality of indexes within an acceptable range through scientific and effective organization of security activities. The simulation evaluation mainly realizes the comparative analysis of the guarantee capability under the maintenance and guarantee operation condition and provides various index data required by the evaluation.
When the experimental deduction operation is guaranteed, a simulation control strategy based on time/event mixing is adopted, and a Hadoop big data technology is adopted for storing and accessing simulation data.
The foregoing is merely illustrative of the present invention and not restrictive, and other modifications and equivalents thereof may occur to those skilled in the art without departing from the spirit and scope of the present invention.
Claims (1)
1. A task-based aviation equipment support system simulation evaluation method is characterized by comprising the following steps of: comprising the following steps:
step 1: determining design parameters of the simulation optimization model of the aviation equipment support system and an optimization target to be evaluated, namely inputting and outputting the simulation optimization model of the aviation equipment support system;
step 2: carrying out first abstraction on a real physical system on the basis of an optimization target to be evaluated of the simulation optimization model of the aviation equipment support system determined in the step 1, and establishing an aviation equipment support system conceptual model comprising three parts of task sources, support task implementation and environment information input;
step 3: performing second abstraction on the basis of the aviation equipment support system conceptual model established in the step 2, and establishing an aviation equipment support system entity model comprising an equipment system model, an equipment support system model, an equipment base model, an equipment scene instance model and an Agent model;
step 4: according to the entity model of the aviation equipment support system established in the step 3, a multi-stage task oriented model is further established, wherein the multi-stage task oriented model comprises an equipment system task model, an equipment unit task model and a basic equipment unit task model;
step 5: according to the entity model of the aviation equipment support system established in the step 3, further establishing an equipment support model;
step 6: taking the multi-stage task-oriented model established in the step 4 as an object, taking multi-stage combat task propulsion as a logic main line, and decomposing and mapping combat tasks layer by layer to basic equipment units, so as to establish a guarantee business process;
step 7: establishing an HLA-based simulation deduction calculation evaluation model, and performing simulation analysis evaluation and guarantee efficiency evaluation on the operation efficiency of maintenance and guarantee business;
in the step 1, firstly, determining the problem to be solved by simulation optimization of an aviation equipment support system, forming a task-required equipment configuration, a connection relation between equipment configurations and a conversion logic under the driving of a multi-stage task and a logic conversion relation thereof, and further establishing a task-oriented aviation equipment support system model;
after the aviation equipment support system model is established, the input of the aviation equipment support system simulation optimization is divided into two types, wherein one type is support capability parameters of equipment units, and the other type is task and environment parameters facing tasks; the output of the simulation optimization is equipment system guarantee parameters and system task success rate parameters;
in the step 2, the abstract conceptual model determines the research scope and the overall situation of the aviation equipment security system, including the source, time, boundary, object, resource and flow of the task;
in the step 3, various functional entity models which can be interactively accessed by the simulation system are further abstracted from the components of the established conceptual model, and the entity model of the aviation equipment support system is established;
in the step 4, a multi-stage task model is established for the whole task flow, task time sequence, information flow, used equipment and connection relation and mutual influence among the equipment of the equipment system model according to the task flow, task phase division and task execution process of the equipment system model;
step 4.1: establishing an equipment system task model, wherein the equipment system task is defined by a plurality of stage tasks and logic conversion relations thereof, and mapped to an equipment unit and a basic equipment unit layer by layer;
step 4.2: establishing an equipment unit task model, wherein the equipment unit task is defined by tasks of the basic equipment unit in a plurality of stages and logic conversion relations thereof;
step 4.3: a basic equipment unit task model is established, basic aviation equipment units are mapped to single equipment, and basic equipment unit tasks are modeled;
in the step 5, the equipment support system modeling includes a support command model, a support monitoring model, an equipment maintenance model, an equipment supply model, an ammunition supply model and a basic model of the comprehensive support system, and after the equipment support task is distributed, the corresponding model triggers a support event to promote support activities to mobilize corresponding support resources;
in the step 7, an HLA-based simulation deduction calculation evaluation model is established, activity, event and time data of each entity SOM are recorded, the dis high-speed data cache is adopted to process calculation process data, the calculation process data are stored in a simulation calculation process data set to be subjected to unified management, the maintenance security service operation efficiency is subjected to simulation analysis evaluation by adopting data storage, data analysis and evaluation optimization, and the security effectiveness is evaluated by adopting a four-level index system.
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