CN110705065A - Multi-quality characteristic integrated modeling simulation evaluation method for aviation equipment - Google Patents
Multi-quality characteristic integrated modeling simulation evaluation method for aviation equipment Download PDFInfo
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Abstract
The invention provides an integrated modeling simulation evaluation method for multi-quality characteristics of aviation equipment, which comprehensively integrates a training task submodel, an equipment submodel, a resource guaranteeing submodel, a process guaranteeing submodel and a reliability, testability and maintainability model by taking the training task of the aviation equipment as traction, triggers guarantee requirements according to the reliability, the testability and the maintainability in the simulation process, calls the resource guaranteeing submodel and the process guaranteeing submodel to realize equipment guarantee, and finally analyzes the simulation result through the integrated evaluation method to realize the evaluation of equipment guarantee efficiency. Based on the simulation evaluation method, the aviation equipment guarantee capacity can be effectively evaluated and the process can be monitored in the early development stage, the effect of prior analysis is fully exerted, and multi-quality characteristic balance optimization, assessment verification in the shaping stage and resource optimization in the use stage in the development process are effectively supported.
Description
Technical Field
The invention belongs to the field of comprehensive guarantee of equipment, and particularly relates to a guarantee efficiency evaluation method for multi-quality characteristic integrated modeling simulation of aviation equipment.
Background
The guarantee capability of the aviation equipment is comprehensively embodied as various quality characteristic levels of the aviation equipment, and the aviation equipment receives more and more extensive attention in recent years. In the process of developing and using the aviation equipment, various quality characteristics interact with each other to influence the guarantee capability of the aviation equipment together, if evaluation is carried out only aiming at a single quality characteristic, the influence of the single quality characteristic on the guarantee capability can only be reflected, and the comprehensive guarantee capability level of the whole aviation equipment system can not be reflected, so that the comprehensive evaluation can be carried out on multiple quality characteristics of the aviation equipment in time and effectively, and the method is a necessary means for ensuring the exertion of the guarantee capability of the aviation equipment.
At present, comprehensive evaluation of multi-quality characteristics of aviation equipment is mainly carried out based on statistical data, but an evaluation method and a system for carrying out integrated simulation based on a quality characteristic model of the aviation equipment are not available, and the existing evaluation means is mainly carried out in the later stage of equipment development and has poor effect on improving the comprehensive guarantee level of the equipment, so that the equipment guarantee capability needs to be effectively evaluated and monitored in the early stage of equipment development, the effect of prior analysis is fully exerted, and the requirements of balance optimization of multi-quality characteristics, evaluation verification in a shaping stage, resource optimization in a use stage and the like in the development process are effectively supported.
Disclosure of Invention
The invention aims to provide a simulation evaluation method which is suitable for early development stage of aviation equipment and can effectively integrate the reliability, maintainability, testability and supportability design analysis models of the aviation equipment.
In order to solve the technical problem, the invention provides an integrated modeling simulation evaluation method for multi-quality characteristics of aviation equipment, which comprises the following steps:
the method comprises the following steps:
step 1, integrated modeling of multi-quality characteristics of aviation equipment, which comprises the following specific steps:
step 11, establishing an aviation equipment guarantee effectiveness simulation evaluation model, which comprises a training task sub-model, an equipment sub-model, a guarantee resource sub-model and a guarantee process sub-model;
the training task sub-model is used for describing a training task plan of the aviation equipment within a certain time;
the equipment submodel is used for describing the type, the quantity and the decomposition structure of the aviation equipment;
the resource guarantee sub-model is used for describing manpower, spare parts, guarantee equipment and guarantee facilities, including functions of guarantee resources, guarantee objects, related use and maintenance guarantee activities, and describing grades and functions of each guarantee site and hierarchical relations and support relation models among different guarantee sites;
the support process submodel is used for describing the use and maintenance support process of the equipment;
step 12, establishing a basic reliability model, a task reliability model, a maintainability model and a testability model of the aviation equipment, and describing related elements of reliability, maintainability and testability which influence the guarantee capability of the aviation equipment, wherein the related elements comprise fault definition, a fault trigger mechanism, a fault distribution function, a maintenance process, maintenance time, a test means, a test process and test time which influence a task;
step 13, integrating multiple quality characteristic models of the aviation equipment;
step 2, aviation equipment guarantee capability simulation evaluation based on aviation equipment multi-quality characteristic integrated modeling comprises the following specific steps:
step 201, using the training task sub-model as a driver, determining available equipment according to the aviation equipment combat training task profile and the task configuration requirements, and allocating a corresponding amount of equipment for the training task according to the optimal matching principle;
step 202, the control system advances a simulation process according to a planning time node, carries out preparation activities before flight according to task requirements, and enters a task execution stage after the preparation is finished;
step 203, the control system calls the equipment submodel, the guarantee effectiveness simulation evaluation model and the basic reliability model in the task execution process; the guarantee efficiency simulation evaluation model and the basic reliability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port; in the calling process, the control system transmits data such as flight hours and landing times to the basic reliability model, the basic reliability model compares and analyzes the received data with the occurrence probability of each functional fault mode of the product, if the flight hours or the landing times exceed a preset functional fault set value, the functional fault of the product is triggered, and then step 204 is executed, otherwise step 209 is executed;
step 204, calling a testability model, and judging whether the functional fault can be detected in the task execution; the performance guaranteeing simulation evaluation model and the testability model wait for external data to trigger the control system to execute corresponding actions by monitoring the network port; in the calling process, the guaranteed effectiveness simulation evaluation model transmits the functional fault mode generated in the step 203 to the testability model, the testability model judges whether the functional fault can be detected in the task execution through a diagnosis strategy, if so, the detection and isolation of the fault are finished, and the step 205 is executed, and if not, the step 209 is executed;
step 205, calling a task reliability model, and judging whether the fault affects the completion of the task; the performance guarantee simulation evaluation model and the task reliability model wait for external data to trigger the control system to execute corresponding actions through monitoring a network port; in the calling process, the performance guarantee simulation evaluation model transmits the fault product information detected in the step 204 to the task reliability model, the task reliability model matches the fault product information with the task dictionary to judge whether the execution of the task is influenced, whether the fault influencing the execution of the task can be solved by a function reconstruction mode is further analyzed, if the fault can not be solved, the step 206 is executed, otherwise, the step 210 is executed;
step 206, because the fault affects the task execution, canceling the task and returning to the home;
step 207, calling a maintainability model to perform fault repairing simulation; the method comprises the following steps that a guaranteed efficiency simulation evaluation model and a maintainability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port, in a calling process, the guaranteed efficiency simulation evaluation model transmits information of a fault to be repaired to the maintainability model, the maintainability model matches a fault repairing process corresponding to the repaired fault from a model library, and the guaranteed resource requirements of spare parts and guaranteed equipment in the fault repairing process are fed back to the guaranteed efficiency simulation evaluation model;
step 208, adding the repaired fault equipment into the available equipment again, and executing step 211;
step 209, after the task is completed and the task is checked, adding the equipment into the available equipment in the equipment submodel again, and executing step 210;
step 210, completing the task, performing post-task inspection, and executing step 211;
step 211, whether tasks are scheduled subsequently or not, if yes, the step 201 is returned, and if not, the simulation is ended; and
and step 212, the control system counts simulation result data, calls an evaluation algorithm and evaluates the guarantee efficiency of the aviation equipment.
Preferably, the step 13 comprises the following specific steps:
step 131, calling the basic reliability model in the process of executing the mission of the aviation equipment to judge whether the aviation equipment breaks down during the mission;
step 132, if the aviation equipment fails during the mission, calling the testability model to determine whether the failure is detectable;
step 133, if the fault cannot be detected in the task execution process, ignoring the fault, continuing to complete the task by the aviation equipment, simultaneously calling the testability model again, performing more detailed fault diagnosis on the aviation equipment after the task is completed, and calling the maintainability model after the fault LRU is determined so as to complete fault elimination work;
and 134, if the fault can be detected in the task execution process, calling the task reliability model to judge whether the fault LRU influences the task execution, if the fault influences the task, the aviation equipment directly returns, if the fault does not influence the task execution, the aviation equipment continues to execute the task, and after returning and task checking, calling the maintainability model to finish the troubleshooting work.
Preferably, the integrated modeling simulation method adopts a Monte Carlo simulation method.
Preferably, the simulation result data comprises the number of aviation equipment, the number of faults, the fault rate, the task completion rate, the flight time and the number of landing times.
Preferably, the evaluation indexes of the aviation equipment guarantee performance evaluation include equipment availability, equipment completeness, mission-capable rate and mission success rate.
Preferably, the evaluation algorithm comprises a fuzzy synthesis evaluation method.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an integrated modeling simulation evaluation method for multi-quality characteristics of aviation equipment, which takes the completion of a training task of the aviation equipment as traction, comprehensively integrates a training task submodel, an equipment submodel, a resource guaranteeing submodel, a process guaranteeing submodel, a reliability, testability and maintainability model, triggers guarantee requirements according to the reliability, the testability and the maintainability in the simulation process, calls the resource guaranteeing submodel and the process guaranteeing submodel to realize equipment guarantee, and finally analyzes a simulation result through the comprehensive evaluation method to realize the evaluation of equipment guarantee efficiency. Based on the simulation evaluation method, the air equipment guarantee capacity can be effectively evaluated and the process can be monitored in the early development stage, the effect of prior analysis is fully exerted, and multi-quality characteristic balance optimization, assessment verification in the shaping stage and resource optimization in the use stage in the development process are effectively supported.
Drawings
FIG. 1 is a simulation evaluation model framework of aviation equipment guarantee effectiveness according to an embodiment of the present invention;
FIG. 2 is an equipment submodel of an embodiment of the invention;
FIG. 3 is a secured resource sub-model of an embodiment of the present invention;
FIG. 4 is a maintenance support process for a turbofan engine according to an embodiment of the invention;
FIG. 5 is a simulation flow of the safeguard efficiency of the aviation equipment according to the embodiment of the present invention; and
FIG. 6 is a flowchart of the integrated modeling simulation evaluation method for the multi-quality characteristic of the aviation equipment.
Detailed Description
In the embodiment, the simulation evaluation of the guarantee efficiency of the aviation equipment at the initial stage of the development stage is realized by simulating the guarantee efficiency simulation evaluation model, the basic reliability model, the task reliability model, the testability model and the maintainability model. The established aviation equipment guarantee effectiveness simulation evaluation model framework is shown in fig. 1.
The aviation equipment guarantee efficiency simulation evaluation model is used as a main body of simulation evaluation and can be further subdivided into a training task submodel, an equipment submodel, a guarantee resource submodel and a guarantee process submodel, and around relevant influence factors of aviation equipment guarantee efficiency, the guarantee process submodel is used as a core, and the incidence relation among training tasks, equipment configurations, reliability, maintainability, testability, guarantee level and guarantee resources is established in the guarantee process submodel, so that the operation of the whole equipment system is described. Wherein:
the training task sub-model comprises a training task plan and a training task profile, the training task plan comprises a plurality of training tasks, each training task is described by one training task profile, and the training task profile describes the training tasks to be executed and comprises the following attributes: the contents of the task start time, the task duration, the task type, the equipment required for executing the task, the number of the equipment required for the task, and the like are shown in table 1, and the specific data structure can be set by those skilled in the art according to the actual situation. The training task is to drive the equipment to use by the whole driver for guaranteeing the simulation operation of the efficiency, and to trigger the equipment to fail in the using process, so as to generate the use and maintenance guarantee activities of the equipment and the related resource requirements.
TABLE 1 training task profiles
| Serial number | Attribute name | Means of |
| 1 | Task start time | Start time of typical task |
| 2 | Duration of a task | Duration of the task |
| 3 | Task type | Description of task type, e.g. assault, patrol, etc |
| 4 | Equipment required for executing task | Equipment type identification or equipment type name required for performing a task |
| 5 | Number of equipment required for task | Number of equipment required to be driven by task |
The equipment submodel, which is the main body for performing training tasks and use and maintenance support activities, includes both basic combat unit configuration and equipment configuration as shown in fig. 2. The basic combat unit is configured to take a device group for executing tasks as a research object and describe information such as the type, the quantity, the composition structure and the like of devices in the device group. The equipment configuration mainly takes a single airplane as a research object to describe the functional structure of the airplane and characteristic information of the constituent units of the airplane.
In this example, there is a 7-day combat mission that requires A, B two model airplanes to participate and perform combat and patrol missions, respectively, with the same mission plan being performed each day, and the training mission sub-model is shown in Table 2.
TABLE 2 training task submodel
The equipment submodel comprises basic combat units consisting of A, B two models of airplanes, wherein the A, B airplanes are respectively 8 frames and 4 frames, and descriptions of functional structures and characteristics of the constituent units are respectively given.
The resource guarantee sub-model describes the configuration conditions of guarantee resources such as manpower, spare parts, guarantee equipment and guarantee facilities in a chart form, and dynamically records the state change conditions of occupation, release, consumption, supply and the like of each guarantee resource in the guarantee process. Resources may include human/personnel, spare parts, equipment, facilities, tools, and materials/information as in fig. 3. The embodiment comprises 12 maintenance personnel, 2 hydraulic pumps, 3 flight control computers, 4 jacks, 2 hydraulic oil pump trucks and the like.
The support process submodel adopts a chart form to describe each item of use and maintenance support activities of the equipment and related elements thereof in detail, wherein the details comprise the time sequence and logic relationship of each item of support activity, the occurrence probability of the support activity, the duration of the support activity, the type and quantity of required support resources and the like. Fig. 4 shows a maintenance process of the turbofan engine in the present embodiment.
The basic reliability model can be constructed by using any relevant software or tools as long as all key function fault modes of the product can be defined, the occurrence probability distribution of each fault mode is determined, and the dynamic and static relations of fault logic transmitted from bottom to top of the faults of the products with different hierarchical structures of the complex system are established. The basic reliability model can be operated independently of the guaranteed efficiency simulation evaluation model, and before the basic reliability model is simulated by the guaranteed efficiency simulation evaluation model, the basic reliability model needs to be built in related software or tools in advance.
The task reliability model can be constructed by using any relevant software or tools, as long as a task dictionary can be defined, and for each task, the corresponding relation between the task success criterion and the product failure list is established on the basis of comprehensively considering design information such as task profile definition, functional system redundancy, dynamic reconstruction mechanism and the like. The task reliability model can independently operate independently of the guaranteed efficiency simulation evaluation model, and before the task reliability model is simulated by the guaranteed efficiency simulation evaluation model, the task reliability model needs to be built in related software or tools in advance.
The testability model can be constructed by using any relevant software or tools, as long as all possible test diagnosis modes of the product and corresponding information such as test diagnosis processes, test diagnosis time, test diagnosis resource requirements and the like under various test diagnosis modes can be determined according to each key fault mode of the product. The testability model can independently run independently of the guarantee efficiency simulation evaluation model, and before the testability model is simulated by the guarantee efficiency simulation evaluation model, the testability model needs to be built in related software or tools in advance.
The maintainability model can be constructed by using any relevant software or tools, as long as all possible troubleshooting modes of the maintainability model, corresponding troubleshooting processes under various troubleshooting modes, troubleshooting time, guarantee resources required in the troubleshooting process and the like can be determined according to each key failure mode of the product. The maintainability model can be operated independently of the guaranteed efficiency simulation evaluation model, and before the maintainability model is simulated by the guaranteed efficiency simulation evaluation model, the maintainability model needs to be built in related software or tools in advance.
In the embodiment, the basic reliability model, the task reliability model, the testability model and the maintainability model are all existing models, and the basic reliability model, the task reliability model, the testability model and the maintainability model are organically linked through the aviation equipment guarantee efficiency simulation evaluation model.
The aviation equipment guarantee efficiency simulation evaluation method in the embodiment comprises the steps that equipment is driven to be used by training a task sub-model, a basic reliability model, a task reliability model, a testability model and a maintainability model are called by the guarantee efficiency simulation evaluation model respectively in the task execution process of the equipment, equipment faults are triggered through the basic reliability model, fault diagnosis is carried out through the testability model, whether the tasks are affected by the faults is judged through the task reliability, fault product repair is carried out through the maintainability model, and resource supports such as guarantee equipment and spare parts are provided for the testability model and the maintainability model respectively in the fault diagnosis and repair processes.
The aviation equipment guarantee efficiency simulation flow in the embodiment is shown in fig. 5. The process takes a guarantee efficiency simulation evaluation model as a core, and a basic reliability model, a task reliability model, a testability model and a maintainability model are simulated and called in the using and maintenance guarantee process. After the simulation times, the simulation period and the confidence degree requirement are set, simulation evaluation can be performed on aviation equipment guarantee efficiency parameters such as the availability, the equipment integrity rate and the mission-capable rate by utilizing a Monte Carlo simulation method based on the aviation equipment guarantee efficiency simulation evaluation model. The method comprises the following specific steps:
step one, taking a training task plan in a training task submodel as a driver, determining available equipment according to equipment required by a task to be executed of the training task and task configuration requirements, and distributing corresponding quantity of equipment for the training task from the equipment submodel according to a best matching principle;
step two, starting to execute the task;
and step three, calling a basic reliability model in the task execution process, and judging whether the equipment has a functional fault during the task. If yes, executing the step four, otherwise, executing the step nine;
step four, calling a testability model, and judging whether the functional fault generated in the step three can be detected and isolated, if so, executing the step five, otherwise, executing the step nine;
step five, calling a task reliability model, judging whether the fault affects the task, further analyzing whether the fault can be solved by a function reconstruction mode aiming at the fault affecting the task, if the fault cannot be solved, executing the step six, otherwise, executing the step ten;
step six, the fault influences the task execution, cancels the task and returns to the home;
and step seven, calling the maintainability model to repair the fault, and determining the fault repair time and the resource guarantee requirements of spare parts, guarantee equipment, human personnel and the like required in the fault repair process.
Step eight, adding the repaired fault equipment into the available equipment again, and executing the step eleven;
step nine, after the task is completed and the task is checked, adding the equipment into the available equipment in the equipment submodel again, and executing the step eleven;
step ten, completing the task, checking after the task, and executing the step seven;
step eleven, if the task arrangement is available subsequently, returning to the step one, and if not, ending the simulation;
and step twelve, the control system calculates and counts simulation result data such as the number of the aviation equipment, the number of faults, the fault rate, the task completion rate, the flight time and the number of the landing times, calls a fuzzy comprehensive evaluation algorithm and evaluates the guaranteed efficiency parameters of the aviation equipment, wherein evaluation indexes comprise equipment availability, equipment completeness rate, task execution rate and task success rate.
In summary, as shown in fig. 6, the method for evaluating the integrated modeling simulation of the multiple quality characteristics of the aviation equipment according to the present invention includes the following steps:
step 1, integrated modeling of multi-quality characteristics of aviation equipment, which comprises the following specific steps:
step 11, establishing an aviation equipment guarantee effectiveness simulation evaluation model, which comprises a training task sub-model, an equipment sub-model, a guarantee resource sub-model and a guarantee process sub-model;
the training task sub-model is used for describing a training task plan of the aviation equipment within a certain time;
the equipment submodel is used for describing the type, the quantity and the decomposition structure of the aviation equipment;
the resource guarantee sub-model is used for describing manpower, spare parts, guarantee equipment and guarantee facilities, including functions of guarantee resources, guarantee objects, related use and maintenance guarantee activities, and describing grades and functions of each guarantee site and hierarchical relations and support relation models among different guarantee sites;
the support process submodel is used for describing the use and maintenance support process of the equipment;
step 12, establishing a basic reliability model, a task reliability model, a maintainability model and a testability model of the aviation equipment, and describing related elements of reliability, maintainability and testability which influence the guarantee capability of the aviation equipment, wherein the related elements comprise fault definition, a fault trigger mechanism, a fault distribution function, a maintenance process, maintenance time, a test means, a test process and test time which influence a task;
step 13, integrating multiple quality characteristic models of the aviation equipment;
step 2, aviation equipment guarantee capability simulation evaluation based on aviation equipment multi-quality characteristic integrated modeling, and more specifically comprises the following specific steps:
step 201, using the training task sub-model as a driver, determining available equipment according to the aviation equipment combat training task profile and the task configuration requirements, and allocating a corresponding amount of equipment for the training task according to the optimal matching principle;
step 202, the control system advances a simulation process according to a planning time node, carries out preparation activities before flight according to task requirements, and enters a task execution stage after the preparation is finished;
step 203, the control system calls the equipment submodel, the guarantee effectiveness simulation evaluation model and the basic reliability model in the task execution process; the guarantee efficiency simulation evaluation model and the basic reliability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port; in the calling process, the control system transmits data such as flight hours and landing times to the basic reliability model, the basic reliability model compares and analyzes the received data with the occurrence probability of each functional fault mode of the product, if the flight hours or the landing times exceed a preset functional fault set value, the functional fault of the product is triggered, and then step 204 is executed, otherwise step 209 is executed;
step 204, calling a testability model, and judging whether the functional fault can be detected in the task execution; the performance guaranteeing simulation evaluation model and the testability model wait for external data to trigger the control system to execute corresponding actions by monitoring the network port; in the calling process, the guaranteed effectiveness simulation evaluation model transmits the functional fault mode generated in the step 203 to the testability model, the testability model judges whether the functional fault can be detected in the task execution process through a diagnosis strategy, if so, the detection and isolation of the fault are completed, and the step 205 is executed; if the judgment result is "no", executing step 209;
step 205, calling a task reliability model, and judging whether the fault affects the completion of the task; the performance guarantee simulation evaluation model and the task reliability model wait for external data to trigger the control system to execute corresponding actions through monitoring a network port; in the calling process, the performance guarantee simulation evaluation model transmits the fault product information detected in the step 204 to the task reliability model, the task reliability model matches the fault product information with the task dictionary to judge whether the execution of the task is influenced, whether the fault influencing the execution of the task can be solved by a function reconstruction mode is further analyzed, if the fault can not be solved, the step 206 is executed, otherwise, the step 210 is executed;
step 206, because the fault affects the task execution, canceling the task and returning to the home;
step 207, calling a maintainability model to perform fault repairing simulation; the method comprises the following steps that a guaranteed efficiency simulation evaluation model and a maintainability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port, in a calling process, the guaranteed efficiency simulation evaluation model transmits information of a fault to be repaired to the maintainability model, the maintainability model matches a fault repairing process corresponding to the repaired fault from a model library, and the guaranteed resource requirements of spare parts and guaranteed equipment in the fault repairing process are fed back to the guaranteed efficiency simulation evaluation model;
step 208, adding the repaired fault equipment into the available equipment again, and executing step 211;
step 209, after the task is completed and the task is checked, adding the equipment into the available equipment in the equipment submodel again, and executing step 210;
step 210, completing the task, performing post-task inspection, and executing step 211;
step 211, whether tasks are scheduled subsequently or not, if yes, the step 201 is returned, and if not, the simulation is ended; and
and step 212, the control system counts simulation result data, calls an evaluation algorithm and evaluates the guarantee efficiency of the aviation equipment.
Finally, it should be noted that: the above-mentioned embodiments are only used for illustrating the technical solution of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. The integrated modeling simulation evaluation method for the multi-quality characteristics of the aviation equipment is characterized by comprising the following steps of:
step 1, integrated modeling of multi-quality characteristics of aviation equipment, which comprises the following specific steps:
step 11, establishing an aviation equipment guarantee effectiveness simulation evaluation model, which comprises a training task sub-model, an equipment sub-model, a guarantee resource sub-model and a guarantee process sub-model;
the training task sub-model is used for describing a training task plan of the aviation equipment within a certain time;
the equipment submodel is used for describing the type, the quantity and the decomposition structure of the aviation equipment;
the resource guarantee sub-model is used for describing manpower, spare parts, guarantee equipment and guarantee facilities, including functions of guarantee resources, guarantee objects, related use and maintenance guarantee activities, and describing grades and functions of each guarantee site and hierarchical relations and support relation models among different guarantee sites;
the support process submodel is used for describing the use and maintenance support process of the equipment;
step 12, establishing a basic reliability model, a task reliability model, a maintainability model and a testability model of the aviation equipment, and describing related elements of reliability, maintainability and testability which influence the guarantee capability of the aviation equipment, wherein the related elements comprise fault definition, a fault trigger mechanism, a fault distribution function, a maintenance process, maintenance time, a test means, a test process and test time which influence a task;
step 13, integrating multiple quality characteristic models of the aviation equipment;
step 2, aviation equipment guarantee capability simulation evaluation based on aviation equipment multi-quality characteristic integrated modeling comprises the following specific steps:
step 201, using the training task sub-model as a driver, determining available equipment according to the aviation equipment combat training task profile and the task configuration requirements, and allocating a corresponding amount of equipment for the training task according to the optimal matching principle;
step 202, the control system advances a simulation process according to a planning time node, carries out preparation activities before flight according to task requirements, and enters a task execution stage after the preparation is finished;
step 203, the control system calls the equipment submodel, the guarantee effectiveness simulation evaluation model and the basic reliability model in the task execution process; the guarantee efficiency simulation evaluation model and the basic reliability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port; in the calling process, the control system transmits data such as flight hours and landing times to the basic reliability model, the basic reliability model compares and analyzes the received data with the occurrence probability of each functional fault mode of the product, if the flight hours or the landing times exceed a preset functional fault set value, the functional fault of the product is triggered, and then step 204 is executed, otherwise step 209 is executed;
step 204, calling a testability model, and judging whether the functional fault can be detected in the task execution; the performance guaranteeing simulation evaluation model and the testability model wait for external data to trigger the control system to execute corresponding actions by monitoring the network port; in the calling process, the guaranteed effectiveness simulation evaluation model transmits the functional fault mode generated in the step 203 to the testability model, the testability model judges whether the functional fault can be detected in the task execution through a diagnosis strategy, if so, the detection and isolation of the fault are finished, and the step 205 is executed, and if not, the step 209 is executed;
step 205, calling a task reliability model, and judging whether the fault affects the completion of the task; the performance guarantee simulation evaluation model and the task reliability model wait for external data to trigger the control system to execute corresponding actions through monitoring a network port; in the calling process, the performance guarantee simulation evaluation model transmits the fault product information detected in the step 204 to the task reliability model, the task reliability model matches the fault product information with the task dictionary to judge whether the execution of the task is influenced, whether the fault influencing the execution of the task can be solved by a function reconstruction mode is further analyzed, if the fault can not be solved, the step 206 is executed, otherwise, the step 210 is executed;
step 206, because the fault affects the task execution, canceling the task and returning to the home;
step 207, calling a maintainability model to perform fault repairing simulation; the method comprises the following steps that a guaranteed efficiency simulation evaluation model and a maintainability model wait for external data to trigger a control system to execute corresponding actions through monitoring a network port, in a calling process, the guaranteed efficiency simulation evaluation model transmits information of a fault to be repaired to the maintainability model, the maintainability model matches a fault repairing process corresponding to the repaired fault from a model library, and the guaranteed resource requirements of spare parts and guaranteed equipment in the fault repairing process are fed back to the guaranteed efficiency simulation evaluation model;
step 208, adding the repaired fault equipment into the available equipment again, and executing step 211;
step 209, after the task is completed and the task is checked, adding the equipment into the available equipment in the equipment submodel again, and executing step 210;
step 210, completing the task, performing post-task inspection, and executing step 211;
step 211, whether tasks are scheduled subsequently or not, if yes, the step 201 is returned, and if not, the simulation is ended; and
and step 212, the control system counts simulation result data, calls an evaluation algorithm and evaluates the guarantee efficiency of the aviation equipment.
2. The integrated modeling simulation evaluation method for the multi-quality characteristic of the aviation equipment as claimed in claim 1, wherein the step 13 comprises the following specific steps:
step 131, calling the basic reliability model in the process of executing the mission of the aviation equipment to judge whether the aviation equipment breaks down during the mission;
step 132, if the aviation equipment fails during the mission, calling the testability model to determine whether the failure is detectable;
step 133, if the fault cannot be detected in the task execution process, ignoring the fault, continuing to complete the task by the aviation equipment, simultaneously calling the testability model again, performing more detailed fault diagnosis on the aviation equipment after the task is completed, and calling the maintainability model after the fault LRU is determined so as to complete fault elimination work;
and 134, if the fault can be detected in the task execution process, calling the task reliability model to judge whether the fault LRU influences the task execution, if the fault influences the task, the aviation equipment directly returns, if the fault does not influence the task execution, the task is continuously executed, and after the return and the task inspection, calling the maintainability model to finish the troubleshooting work.
3. The integrated modeling simulation evaluation method for the multi-quality characteristics of the aviation equipment as claimed in claim 1 or 2, wherein the integrated modeling simulation method adopts a Monte Carlo simulation method.
4. The integrated modeling simulation evaluation method for the multi-quality characteristics of the aviation equipment according to the claim 1 or 2, wherein the simulation result data comprises the number of the aviation equipment, the number of faults, the fault rate, the mission completion rate, the flight time and the number of the landings.
5. The integrated modeling simulation evaluation method for the multi-quality characteristics of the aviation equipment according to claim 1 or 2, wherein the evaluation indexes of the aviation equipment guarantee performance evaluation include equipment availability, equipment completeness, mission-capable rate and mission success rate.
6. The integrated modeling simulation evaluation method for the multi-quality characteristics of the aviation equipment as claimed in claim 1 or 2, wherein the evaluation algorithm comprises a fuzzy comprehensive evaluation method.
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| CN112989697A (en) * | 2021-03-11 | 2021-06-18 | 中国人民解放军空军工程大学航空机务士官学校 | Maintenance support equipment optimization method based on task |
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| CN113221321A (en) * | 2021-03-31 | 2021-08-06 | 北京瑞风协同科技股份有限公司 | Simulation and index evaluation method and system based on task equipment fault |
| CN113222399A (en) * | 2021-05-08 | 2021-08-06 | 中国人民解放军陆军工程大学 | Engineering equipment operation guarantee comprehensive efficiency evaluation method |
| CN113222399B (en) * | 2021-05-08 | 2024-04-23 | 中国人民解放军陆军工程大学 | Comprehensive performance evaluation method for engineering equipment operation guarantee |
| CN114118757A (en) * | 2021-11-20 | 2022-03-01 | 中国人民解放军32181部队 | Weapon sexuality collaborative optimization method and system with security as center |
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