CN109657420B - Equipment guarantee characteristic simulation modeling method based on aerospace task - Google Patents
Equipment guarantee characteristic simulation modeling method based on aerospace task Download PDFInfo
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Abstract
The application relates to a device guarantee characteristic simulation modeling method based on a space mission, which comprises the steps of importing acquired space mission historical mission data into a database to form a historical mission database; carrying out overall task decomposition on the historical tasks to form a basic task sequence formed by a plurality of basic tasks, and obtaining basic task historical data; establishing an equipment guarantee characteristic simulation model of the basic task for the basic task historical data; according to the task sequence of the basic task sequence and the forwarding probability of the adjacent tasks, an equipment guarantee characteristic simulation model based on the aerospace task is built according to the built basic task equipment guarantee characteristic simulation model. The method takes the aerospace task as a drive, takes aerospace equipment as a base, takes equipment guarantee as a core, adopts modeling and simulation means to analyze and pre-judge weak links which possibly fail in advance, really improves the success capability of the aerospace launching task, and has obvious benefits.
Description
Technical Field
The application relates to the technical field of equipment support, in particular to an equipment support characteristic simulation modeling method based on a space mission.
Background
The aerospace equipment is a material technology basis for completing the test and identification of the aerospace equipment, and the problem of guaranteeing the aerospace equipment in the whole life cycle can be solved through researching the guaranteeing characteristics of the aerospace equipment.
The complexity of the aerospace mission requires that the aerospace equipment has diversity and complexity, and in different stages of the aerospace mission, the related aerospace equipment has different requirements on the security characteristics of the aerospace equipment, in order to better evaluate and evaluate the security capability of the aerospace equipment, an equipment security characteristic simulation model of the aerospace mission needs to be established,
however, due to the fact that the requirement on the standard capability of the aerospace task is high and the historical data of the aerospace test task is less, the aerospace equipment guarantee characteristic simulation model applicable to the aerospace task is lacking.
Disclosure of Invention
In view of the analysis, the application aims to provide an equipment guarantee characteristic simulation modeling method based on a space mission, construct a space equipment guarantee characteristic model capable of accurately describing quality characteristics of space equipment and establish a foundation for space equipment guarantee characteristic evaluation.
The aim of the application is mainly realized by the following technical scheme:
an equipment guarantee characteristic simulation modeling method based on a space mission comprises the following steps:
importing the acquired aerospace historical task data into a database to form a historical task database;
carrying out overall task decomposition on the historical tasks to form a basic task sequence consisting of a plurality of basic tasks; classifying historical task data by taking basic tasks and related equipment as indexes to obtain basic task historical data;
establishing an equipment guarantee characteristic simulation model of the basic task for the basic task historical data;
according to the task sequence of the basic task sequence and the forwarding probability of the adjacent tasks, an equipment guarantee characteristic simulation model based on the aerospace task is built according to the built basic task equipment guarantee characteristic simulation model.
Further, the overall task decomposition includes coarse decomposition and fine decomposition;
the rough decomposition divides the complex task into sub task sequences which are connected end to end in time and are not overlapped with each other in task according to task stage information in the task information data;
the subtotal is used for dividing the subtasks into basic task sequences which are connected end to end in time and are not overlapped with each other in task according to the minimum functional configuration related to the aerospace equipment in the subtasks.
Further, according to the minimum functional configuration of the aerospace equipment, the basic task is divided into a single-loading task completed by the single-task aerospace equipment, a subsystem task completed by an equipment subsystem formed by a plurality of mutually-related single aerospace equipment, and a joint system task completed by an equipment joint system formed by a plurality of mutually-related equipment subsystems;
the built basic task equipment guarantee characteristic simulation model also correspondingly comprises a single-loading task equipment guarantee characteristic simulation model, a subsystem task equipment guarantee characteristic simulation model or a combined system task equipment guarantee characteristic simulation model.
Further, the single-package guarantee characteristic simulation model comprises an availability model of a single-package task and a single-package task efficiency model;
the availability model of the single-loading task is as follows
The single-loading task efficiency model is M E1 ＝A 01 [R M1 +(1-R M1 )M 01 ]+(1-A 01 )M 01 ；
In the formula, MTBF 1 Mean time between failures for equipment in a single-load task; MLDT 1 The average guarantee delay time of the equipment in the single-loading task comprises the repair maintenance interval, the preventive maintenance interval, the delay time of logistics and management of the single-loading; r is R M1 Task credibility for equipping in the single-loading task; m is M 01 For the maintenance of the equipment in the single-loading task.
Further, the subsystem task equipment guarantee characteristic simulation model comprises an availability model of a subsystem task and a subsystem task efficiency model;
the availability model of the subsystem task is as follows:
the subsystem task performance model is as follows: m is M E2 ＝A 02 [R M2 +(1-R M2 )M 02 ]+(1-A 02 )M 02 ；
In the formula, MTBF 2 Is the average inter-fault time of the equipment subsystem in the subsystem task; MLDT 2 The average guarantee delay time of the equipment subsystem in the subsystem task is ensured; r is R M2 The task reliability of the equipment subsystem in subsystem tasks is the task reliability of the equipment subsystem; m is M 02 Is the maintenance of the equipment subsystem in subsystem tasks.
Further, the combined system task equipment guarantee characteristic simulation model comprises an availability model of a combined system task and a combined system task efficiency model;
the availability model of the joint system task is as follows:
the joint system task performance model is as follows: m is M E3 ＝A 03 [R M3 +(1-R M3 )M 03 ]+(1-A 03 )M 03 ；
In the formula, MTBF 3 Is the average inter-fault time of the joint system in the joint system task；MLDT 3 The average guarantee delay time of the combined system in the task of the combined system is; r is R M3 The task reliability of the joint system in the joint system task is determined; m is M 03 Is the maintenance degree of the combined system in the task of the combined system.
Further, the availability simulation model of the whole task included in the equipment guarantee characteristic simulation model based on the aerospace task is thatIn the formula, MTBF i Average inter-fault time for the ith basic task contained in the overall task; MLDT i An average failure delay time for the ith basic task included in the overall task.
Further, task performance simulation included in the equipment guarantee characteristic simulation model based on the aerospace task is realized through a statistical method, and the method comprises the following steps:
1) Setting task success conditions of each basic task, simulating times of task efficiency, and carrying out initial zero setting on basic task serial numbers, simulation counts, task success counts and task failure counts;
2) Adding 1 to the simulation count, calling a basic task with the sequence number of 1, and judging that the basic task is a single-loading task, a subsystem task or a combined system task; according to the established single-loading task equipment guarantee characteristic simulation model, subsystem task equipment guarantee characteristic simulation model or combined system task equipment guarantee characteristic simulation model; performing equipment guarantee characteristic simulation of the basic task to obtain a simulation result;
3) Judging a simulation result according to a set task success condition, if judging that the basic task is successful, entering 4), if judging that the basic task is unsuccessful, performing one-time task failure counting by a task failure counter, stopping the simulation, and returning to 2);
4) Adding 1 to the basic task sequence number, calling the basic task of the next sequence number, judging whether the next basic task can start smoothly, and entering 5) if the next basic task can start smoothly; if the simulation cannot be successfully started, the task failure counter performs task failure counting once, stops the simulation, and returns to the step 2);
5) Performing security feature simulation and simulation result judgment according to the basic task types, if the basic task is judged to be successful, continuously performing type judgment, security feature simulation and simulation result judgment on the basic task in sequence until the last basic task simulation result is that the task is successful, performing task success counting once by a task success counter, ending the simulation, and returning to the step 2); if the basic task is judged to be unsuccessful, the task failure counter counts the task failure once, stops the simulation, and returns to the step 2);
6) And stopping simulation until the simulation count reaches the set simulation times, counting a task success count value and a task failure count value, and performing task efficiency evaluation of the overall aerospace task.
Further, the basic task success condition is that the availability and task efficiency of the basic task simulation result exceed the availability and task efficiency threshold, and the task quantity completed in the basic task time reaches the task quantity threshold.
Further, the condition that the next basic task can start smoothly is that the probability P of the transition of the adjacent task i Greater than the smooth start probability threshold.
The application has the following beneficial effects:
the equipment guarantee characteristic simulation modeling method based on the aerospace task starts from the top-level requirements of high integrity of the aerospace equipment and high success of the aerospace task, takes the aerospace task as a drive, takes the aerospace equipment as a base, takes equipment guarantee as a core, is close to real scenes and environments, real equipment and guarantee, real use conditions and maintenance conditions of the actual combat simulation execution aerospace task, adopts modeling and simulation means to analyze and pre-judge weak links which possibly fail in advance, can find problems and solve the problems before the task, ensures high reliability and high integrity, practically improves the success capability of the aerospace launching task, and has obvious benefits.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
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The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the application, like reference numerals being used to refer to like parts throughout the several views.
FIG. 1 is a flow chart of an equipment support characteristic simulation modeling method based on a space mission in an embodiment of the application;
FIG. 2 is a flow chart of overall task performance simulation in an embodiment of the present application.
Detailed Description
Preferred embodiments of the present application are described in detail below with reference to the attached drawing figures, which form a part of the present application and are used in conjunction with embodiments of the present application to illustrate the principles of the present application.
The embodiment discloses an equipment guarantee characteristic simulation modeling method based on a space mission, which comprises the following steps as shown in fig. 1:
step S1, importing the acquired aerospace historical task data into a database to form a historical task database;
the historical task data comprises task process data, aerospace equipment data and aerospace equipment guarantee characteristic data
Specific historical data include:
the task process data includes: task stage, task section, task content, task time, task constraint, task quantity, task success condition, processing of emergency in task execution and other information;
the aerospace equipment data includes: equipment basic information, equipment function data, equipment structure data, equipment-related document data, and equipment technical state data;
the aerospace equipment security characteristic data includes: space equipment reliability data, space equipment maintainability data, space equipment assurances data and the like.
Wherein the aerospace equipment reliability data comprises: reliability design data, reliability modeling data, fault tree analysis data, reliability block diagram data, fault mode influence analysis data, event tree analysis ETA data and use process reliability data of the aerospace equipment;
the aerospace equipment serviceability data includes: maintainability design data, fault mode influence analysis data, maintenance task data and use process maintainability data of the aerospace equipment;
the aerospace equipment security data includes: the method comprises the following steps of guaranteeing design data, using process guaranteeing data, guaranteeing resource data and guaranteeing task demand data of the aerospace equipment;
s2, performing overall task decomposition on the historical tasks to form a basic task sequence consisting of a plurality of basic tasks; and establishing a corresponding relation between the basic task and the equipment, classifying the historical data of the historical task database by taking the task content and the related equipment as indexes, and obtaining the basic task historical data.
Specifically, the overall task decomposition includes coarse decomposition and fine decomposition;
in the rough decomposition process, according to task stage information in task process data, dividing a complex task into sub-task sequences which are connected end to end in time and are not overlapped with each other in task, and determining task constraint information including task start-stop time, task quantity and the like of each sub-task, and related aerospace equipment data and aerospace equipment guarantee characteristic data; establishing a corresponding relation between a subtask and aerospace equipment, classifying historical data of a historical task database by taking subtask content and related aerospace equipment as indexes to obtain the subtask historical data;
in the sub-division process, dividing the subtasks into basic task sequences which are connected end to end in time and are not overlapped with each other in tasks according to the minimum functional configuration of the subtasks related to the aerospace equipment, and extracting attribute information of the basic tasks from the subtask historical data;
wherein the attribute information includes task constraint information and aerospace equipment data;
the task constraint information comprises information such as task start-stop time, task quantity and the like;
the aerospace equipment data are aerospace equipment data related to the execution of basic tasks and equipment guarantee characteristic data;
the basic task and the related aerospace equipment are corresponding, the corresponding relation between the basic task and the aerospace equipment is established, the aerospace equipment related to the task is determined, the subtask historical data are classified by taking the basic task content and the related aerospace equipment as indexes, and the basic task historical data are obtained.
Specifically, according to the minimum functional configuration of the aerospace equipment, the basic task types can be divided into single-loading tasks completed by single-task aerospace equipment; or subsystem tasks performed for an equipment subsystem consisting of a number of interrelated single aerospace equipment; or a joint system task performed for an equipment joint system consisting of a plurality of interrelated equipment subsystems;
s3, establishing an equipment guarantee characteristic simulation model of the basic task for the basic task historical data;
because the basic tasks include single-load tasks, subsystem tasks, or joint system tasks; the built basic task equipment guarantee characteristic simulation model correspondingly comprises a single-loading task equipment guarantee characteristic simulation model, a subsystem task equipment guarantee characteristic simulation model or a combined system task equipment guarantee characteristic simulation model.
The method comprises the steps that a single-package guarantee characteristic simulation model is established, wherein the single-package guarantee characteristic simulation model comprises single-package availability and task efficiency according to space equipment data and space equipment guarantee characteristic data included in single-package task historical data through task efficiency analysis of a single-package task;
the availability model of the single-loading task is as follows
The efficiency model of the single-loading task is M E1 ＝A 01 [R M1 +(1-R M1 )M 01 ]+(1-A 01 )M 01 ；
In the formula, MTBF 1 Mean time between failures for equipment in a single-load task;
MLDT 1 for equipping averaging in single-load tasksGuaranteeing delay times, including, for example, repair maintenance intervals, preventive maintenance intervals, logistical and administrative delay times for a single package;
R M1 task credibility for equipping in the single-loading task;
M 01 for the maintenance of the equipment in the single-loading task.
The method comprises the steps that a subsystem task equipment guarantee characteristic simulation model is used for establishing a guarantee characteristic simulation model comprising subsystem availability and task efficiency according to space equipment data and space equipment guarantee characteristic data in an equipment subsystem related to subsystem historical task data through task efficiency analysis of subsystem tasks;
the availability model of the subsystem task is as follows:
the subsystem task performance model is: m is M E2 ＝A 02 [R M2 +(1-R M2 )M 02 ]+(1-A 02 )M 02 ；
In the formula, MTBF 2 Is the average time between failures of the equipment subsystem in the subsystem tasks, i.e., the operational time of the aerospace equipment subsystem performing the tasks,
MLDT 2 the average guarantee delay time of the equipment subsystem in the subsystem task, namely the non-working time of the aerospace equipment subsystem for executing the task, such as repair maintenance intervals, preventive maintenance intervals, logistical and management delay time of the equipment subsystem;
for the calculation of the average fault interval time and the average guarantee delay time of the subsystem, reference can be made to an analysis method which is mature in the industry, for example, MTBF adopts Duane model, and MLDT adopts field maintenance rate based calculation model.
R M2 The task reliability of the equipment subsystem in subsystem tasks is the task reliability of the whole equipment subsystem;
M 02 for maintenance of equipment subsystem in subsystem task, it is a certain equipment subsystemMaintenance of the system.
The method comprises the steps that a combined system task equipment guarantee characteristic simulation model is established, wherein the combined system task comprises task performance analysis, and a guarantee characteristic simulation model comprising the combined system availability and task performance is established according to space equipment data and space equipment guarantee characteristic data in an equipment combined system related to historical task data;
the availability model of the joint system task is as follows:
the joint system task performance model is: m is M E3 ＝A 03 [R M3 +(1-R M3 )M 03 ]+(1-A 03 )M 03 ；
In the formula, MTBF 3 The average fault interval time of the joint system in the joint system task is the working time of a certain aerospace equipment joint system for executing the task; not the workable time of a piece of equipment;
MLDT 3 the average guarantee delay time of the combined system in the task of the combined system, namely the non-working time of the combined system of certain spaceflight equipment for executing the task, for example, the delay time including repair maintenance interval, preventive maintenance interval, logistics and management of the combined system;
R M3 the task reliability of the joint system in the joint system task is the task reliability of a certain joint system;
M 03 the maintenance degree of the combined system in the task of the combined system is the maintenance degree of a certain combined system.
And S4, according to the task sequence of the basic task sequence and the forwarding probability of the adjacent tasks, building an equipment guarantee characteristic simulation model based on the aerospace task according to the built basic task equipment guarantee characteristic simulation model.
And (2) dividing the whole space mission into basic mission sequences which are continuous in time and non-overlapping in mission after rough division and subdivision according to the method of the step (S2). The basic task sequence number in the sequence is iEach time node t in the sequence i Representing basic task M i Latest end time point of (1) and basic task M i+1 The latest start time of (a), the time period (T) between nodes i Is a time constraint on the basic task; p (P) i Representing the probability of forwarding an adjacent task, i.e. the probability of availability AS (t i )。
Due to the diversity of tasks, different basic tasks have different task amounts W i Such as the number of miles, the number of shots. It is necessary to convert these task amounts into generalized working time T i Unifying the units of task calendar time;
specifically, generalized operating time T i ＝W i λ, where λ is a conversion coefficient, determined on the basis of statistics according to different task types. For example, the task amount unit corresponding to the chassis system is kilometers, and other functional systems are similar.
Establishing an equipment guarantee characteristic simulation model of an overall task, and representing the equipment guarantee characteristic simulation model through an availability simulation model and a task efficiency simulation model;
wherein the availability simulation model of the overall task is as follows
In the formula, MTBF i Average inter-fault time for the ith basic task contained in the overall task;
MLDT i an average failure delay time for the ith basic task included in the overall task.
The overall task performance simulation is implemented by a statistical method, as shown in fig. 2, and the specific method includes:
1) Initializing setting; setting task success conditions and simulation times of task efficiency of each basic task, and carrying out initial zero setting on a basic task sequence number, a simulation count, a task success count and a task failure count;
2) Adding 1 to the simulation count, calling a basic task with the sequence number of 1, and judging that the basic task is a single-loading task, a subsystem task or a combined system task; according to the established single-loading task equipment guarantee characteristic simulation model, subsystem task equipment guarantee characteristic simulation model or combined system task equipment guarantee characteristic simulation model; performing equipment guarantee characteristic simulation of the basic task to obtain a simulation result;
3) Judging a simulation result according to a set task success condition, if judging that the basic task is successful, entering 4), if judging that the basic task is unsuccessful, performing one-time task failure counting by a task failure counter, stopping the simulation, and returning to 2);
4) Adding 1 to the basic task sequence number, calling the basic task of the next sequence number, judging whether the next basic task can start smoothly, and entering 5) if the next basic task can start smoothly; if the simulation cannot be successfully started, the task failure counter performs task failure counting once, stops the simulation, and returns to the step 2);
5) Performing security feature simulation and simulation result judgment according to the basic task types, if judging that the task is successful, continuously performing type judgment, security feature simulation and simulation result judgment on the basic task in sequence until the last basic task simulation result is that the task is successful, performing task success counting once by a task success counter, ending the simulation, and returning to the step 2); if the basic task is judged to be unsuccessful, the task failure counter counts the task failure once, stops the simulation, and returns to the step 2);
6) And stopping simulation until the simulation count reaches the set simulation times, counting a task success count value and a task failure count value, and performing task efficiency evaluation of the overall aerospace task.
The task success conditions of the basic task are an availability threshold, a task efficiency threshold and a task quantity threshold of the basic task, when the availability and task efficiency of the basic task simulation result exceed the availability and task efficiency thresholds, the task quantity completed in the basic task time reaches the task quantity threshold.
Wherein, the condition for judging whether the next basic task can start smoothly is that the probability P of the transition of the adjacent task i Whether or not it is greater than a smooth start probability thresholdAnd if the value is larger than the successful start probability threshold, the next basic task starts smoothly, otherwise, the simulation is stopped.
Preferably, by the method of the embodiment, subtasks can be obtained by coarse decomposition in task decomposition, and an equipment guarantee characteristic simulation model is established for carrying out equipment guarantee characteristic simulation on each task stage of the whole aerospace task.
The present application is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present application are intended to be included in the scope of the present application.
Claims (1)
1. The equipment guarantee characteristic simulation modeling method based on the aerospace task is characterized by comprising the following steps of:
step S1, importing the acquired aerospace historical task data into a database to form a historical task database;
the historical task data comprise task process data, aerospace equipment data and aerospace equipment guarantee characteristic data;
the task process data includes: task stage, task section, task content, task time, task constraint, task amount, task success condition and processing of emergency in task execution;
the aerospace equipment data includes: equipment basic information, equipment function data, equipment structure data, equipment-related document data, and equipment technical state data;
the aerospace equipment security characteristic data includes: reliability data of aerospace equipment, maintainability data of aerospace equipment and guaranteeing data of aerospace equipment;
wherein the aerospace equipment reliability data comprises: reliability design data, reliability modeling data, fault tree analysis data, reliability block diagram data, fault mode influence analysis data, event tree analysis ETA data and use process reliability data of the aerospace equipment;
the aerospace equipment serviceability data includes: maintainability design data, fault mode influence analysis data, maintenance task data and use process maintainability data of the aerospace equipment;
the aerospace equipment security data includes: the method comprises the following steps of guaranteeing design data, using process guaranteeing data, guaranteeing resource data and guaranteeing task demand data of the aerospace equipment;
s2, performing overall task decomposition on the historical tasks to form a basic task sequence consisting of a plurality of basic tasks; establishing a corresponding relation between a basic task and related aerospace equipment, classifying historical data of a historical task database by taking basic task content and related aerospace equipment as indexes, and obtaining basic task historical data;
the overall task decomposition comprises coarse decomposition and fine decomposition;
in the rough decomposition process, according to task stage information in task process data, dividing a complex task into sub-task sequences which are connected end to end in time and are not overlapped with each other in task; the subtask sequence comprises task constraint information consisting of task start-stop time and task quantity of each subtask, related aerospace equipment data and aerospace equipment guarantee characteristic data; establishing a corresponding relation between the subtasks and the related aerospace equipment, classifying the historical data of the historical task database by taking the subtask content and the related aerospace equipment as indexes to obtain the subtask historical data;
in the sub-division process, dividing the subtasks into basic task sequences which are connected end to end in time and are not overlapped with each other in the task according to the minimum functional configuration of the related aerospace equipment in the subtasks, and extracting attribute information of the basic tasks from the subtask historical data;
wherein the attribute information comprises constraint information of a basic task and aerospace equipment data;
the task constraint information comprises the starting and stopping time and the task quantity of a basic task;
the aerospace equipment data are aerospace equipment data related to basic task execution and equipment guarantee characteristic data;
corresponding basic tasks and related aerospace equipment, establishing a corresponding relation between the basic tasks and the related aerospace equipment, determining the aerospace equipment related to the basic tasks, classifying sub-task historical data by taking basic task content and the related aerospace equipment as indexes, and obtaining basic task historical data;
according to the minimum functional configuration of the aerospace equipment related to the basic task, the basic task type is divided into single-loading tasks completed by single-task aerospace equipment; or subsystem tasks performed for an equipment subsystem consisting of several interrelated single aerospace equipment; or a joint system task performed for an equipment joint system consisting of a plurality of interrelated equipment subsystems;
s3, establishing an equipment guarantee characteristic simulation model of the basic task for the basic task historical data;
the basic tasks comprise a single-loading task, a subsystem task or a combined system task; the built basic task equipment guarantee characteristic simulation model also correspondingly comprises a single-loading task equipment guarantee characteristic simulation model, a subsystem task equipment guarantee characteristic simulation model or a combined system task equipment guarantee characteristic simulation model;
the method comprises the steps that a single-package guarantee characteristic simulation model is established, wherein the single-package guarantee characteristic simulation model comprises single-package availability and task efficiency according to space equipment data and space equipment guarantee characteristic data included in single-package task historical data through task efficiency analysis of a single-package task;
the availability model of the single-loading task is as follows；
The single-loading task efficiency model is as follows；
In the method, in the process of the application,mean time between failures for equipment in a single-load task;
average guarantee delay time for equipment in a single-package task, including repairable maintenance intervals, preventive maintenance intervals and logistical and management delay time of the single package;
task credibility for equipping in the single-loading task;
the maintenance degree of the equipment in the single-loading task;
the method comprises the steps that a subsystem task equipment guarantee characteristic simulation model is established, wherein the guarantee characteristic simulation model comprises subsystem availability and task efficiency according to space equipment data and space equipment guarantee characteristic data in related equipment subsystems in subsystem historical task data through task efficiency analysis of subsystem tasks;
the availability model of the subsystem task is as follows:；
the subsystem task performance model is:；
in the method, in the process of the application,is the average inter-fault time of the equipment subsystem in the subsystem task;
the average guarantee delay time of the equipment subsystem in subsystem tasks comprises repairable maintenance intervals, preventive maintenance intervals and logistic and management delay time of the equipment subsystem;
task reliability of the equipment subsystem in subsystem tasks;
the maintenance degree of the equipment subsystem in subsystem tasks is determined;
the method comprises the steps that a combined system task equipment guarantee characteristic simulation model is established, wherein the combined system task equipment guarantee characteristic simulation model comprises combined system availability and task efficiency according to space equipment data and space equipment guarantee characteristic data in an equipment combined system related to historical task data by performing task efficiency analysis on the combined system task;
the availability model of the joint system task is as follows:；
the joint system task performance model is:；
in the method, in the process of the application,is the average inter-fault time of the joint system in the joint system task;
the average guarantee delay time of the combined system in the task of the combined system comprises repair maintenance intervals, preventive maintenance intervals and delay time of logistics and management of the combined system;
the task reliability of the joint system in the joint system task is obtained;
the maintenance degree of the combined system in the task of the combined system is as follows;
s4, according to the task sequence of the basic task sequence and the forwarding probability of the adjacent tasks, building an equipment guarantee characteristic simulation model based on the aerospace task according to the built basic task equipment guarantee characteristic simulation model; the probability of forwarding adjacent tasks is the available probability of the functional system set required by the next basic task at the starting moment of the basic task;
establishing an equipment guarantee characteristic simulation model of an overall task, and representing the equipment guarantee characteristic simulation model through an availability simulation model and a task efficiency simulation model;
wherein the availability simulation model of the overall task is as followsThe method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Availability for the overall task; />Is the first contained in the overall taskiAverage inter-fault time of individual basic tasks; />Is the first contained in the overall taskiAverage fault delay time of individual basic tasks;
the task efficiency simulation model of the whole task is realized by a statistical method, and comprises the following steps:
1) Initializing setting; setting task success conditions and simulation times of task efficiency of each basic task, and carrying out initial zero setting on a basic task sequence number, a simulation count, a task success count and a task failure count;
2) Adding 1 to the simulation count, calling a basic task with the sequence number of 1, and judging that the basic task is a single-loading task, a subsystem task or a combined system task; according to the established single-loading task equipment guarantee characteristic simulation model, subsystem task equipment guarantee characteristic simulation model or combined system task equipment guarantee characteristic simulation model; performing equipment guarantee characteristic simulation of the basic task to obtain a simulation result;
3) Judging a simulation result according to a set task success condition, if judging that the basic task is successful, entering 4), if judging that the basic task is unsuccessful, performing one-time task failure counting by a task failure counter, stopping the simulation, and returning to 2);
4) Adding 1 to the basic task sequence number, calling the basic task of the next sequence number, judging whether the next basic task can start smoothly, and entering 5) if the next basic task can start smoothly; if the simulation cannot be successfully started, the task failure counter performs task failure counting once, stops the simulation, and returns to the step 2);
5) Performing security feature simulation and simulation result judgment according to the basic task types, if judging that the task is successful, continuously performing type judgment, security feature simulation and simulation result judgment on the basic task in sequence until the last basic task simulation result is that the task is successful, performing task success counting once by a task success counter, ending the simulation, and returning to the step 2); if the basic task is judged to be unsuccessful, the task failure counter counts the task failure once, stops the simulation, and returns to the step 2);
6) Stopping simulation until the simulation count reaches the set simulation times, counting a task success count value and a task failure count value, and performing task efficiency evaluation of the overall aerospace task;
the task success conditions of the basic task are an availability threshold, a task efficiency threshold and a task quantity threshold of the basic task, when the availability and the task efficiency of the basic task simulation result exceed the availability and the task efficiency threshold, the task quantity completed in the basic task time reaches the task quantity threshold;
wherein, the condition for judging whether the next basic task can start smoothly is that the probability of the transition of the adjacent taskP i If the probability is larger than the successful start probability threshold, the next basic task starts smoothly, otherwise, the simulation is stopped.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103745107A (en) * | 2014-01-10 | 2014-04-23 | 北京电子工程总体研究所 | Fault mode-based establishment method for maintenance support simulation system for equipment basic level |
| WO2017028632A1 (en) * | 2015-08-19 | 2017-02-23 | 中国电力科学研究院 | Method of predicting distribution network operation reliability |
| CN106529306A (en) * | 2016-11-16 | 2017-03-22 | 中国电子产品可靠性与环境试验研究所 | System safety assessment method and device |
-
2019
- 2019-02-21 CN CN201910132792.0A patent/CN109657420B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103745107A (en) * | 2014-01-10 | 2014-04-23 | 北京电子工程总体研究所 | Fault mode-based establishment method for maintenance support simulation system for equipment basic level |
| WO2017028632A1 (en) * | 2015-08-19 | 2017-02-23 | 中国电力科学研究院 | Method of predicting distribution network operation reliability |
| CN106529306A (en) * | 2016-11-16 | 2017-03-22 | 中国电子产品可靠性与环境试验研究所 | System safety assessment method and device |
Non-Patent Citations (3)
| Title |
|---|
| 军用飞机可用度概念模型及仿真;赵冰化等;《火力与指挥控制》;20070615(第06期);第1-4页 * |
| 基于作战单元的装备综合保障仿真评估研究;陈辉强等;《系统仿真学报》;20101108(第11期);第1-4页 * |
| 陈辉强等.基于作战单元的装备综合保障仿真评估研究.《系统仿真学报》.2010,(第11期),第1-4页. * |
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