Unmanned aerial vehicle group system reliability calculation method based on incomplete fault coverage model

Abstract

The invention relates to an unmanned aerial vehicle group system reliability calculation method based on an incomplete fault coverage model, and the method comprises the steps: S1, combining multi-stage task features, and listing success probability events meeting function demands in each stage from a subsystem layer; s2, after the earlier stage succeeds, subsystems needing to participate in the subsequent stage and the minimum effective operation quantity of the unmanned aerial vehicle meeting the task success are analyzed; s3, if non-participated subsystems initially exist in a certain stage, the subsystems are irrelevant subsystems, and the reliability of the subsystems in each stage is calculated; and S4, calculating the reliability of the subsequent stage according to S2 and S3, wherein the reliability of the last stage is the reliability of the whole system. According to the method, the situation that the whole system fails due to the fact that part of subsystems are ignored not to participate in a certain stage and uncovered failure is possibly caused is considered, so that the reliability calculation precision is improved, and the method is suitable for multi-stage task systems with high reliability precision requirements such as military, emergency and industrial control.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of software reliability engineering, more particularly, to a UAV swarm system reliability calculation method based on incomplete fault coverage. BACKGROUND

[0002] In a fault-tolerant system, the fault-tolerant mechanism in the complete fault coverage model assumes that component failures can be perfectly identified, located, isolated and recovered. However, in reality, not all component failures can be perfectly identified, located, isolated and recovered by the fault-tolerant mechanism. Then, these component failures that are not identified, isolated or recovered by the fault-tolerant mechanism are called uncovered fault components, and such uncovered faults can directly cause system failure. Therefore, the model considering such component uncovered faults is called an incomplete coverage model.

[0003] With the continuous progress of unmanned aerial vehicle technology, unmanned aerial vehicle swarms have been applied in various fields. Unmanned aerial vehicle swarms make up for the shortcomings of single unmanned aerial vehicles in terms of being unable to independently complete tasks such as communication, data collection, and data backhaul. In addition, the tasks of unmanned aerial vehicle swarms are usually composed of multiple stages, for example, the tasks of unmanned aerial vehicle swarms can include five stages: launch, assembly, reconnaissance, attack, and return, which highlights the phased nature of the task and can be regarded as a multi-stage task system. However, current reliability calculations for unmanned aerial vehicle swarms are mostly based on the assumption of "complete fault coverage", that is, it is assumed that the built-in diagnosis and isolation mechanism of the system can detect faults, isolate failed components, and restore system functions through redundancy replacement or repair at 100%. However, in actual operating environments, unmanned aerial vehicle swarms often face complex interference factors such as electromagnetic interference, extreme temperature and humidity, and sudden airflow changes, resulting in a large number of "uncovered failure" scenarios that cannot be covered by the complete fault coverage model. There are also a small number of reliability calculations for unmanned aerial vehicle swarms based on the "incomplete fault coverage model", but these methods ignore the isolation of subsystems that do not need to participate in work at a certain stage, and these non-working subsystems may experience uncovered failures that affect the system. This method of ignoring non-working subsystems has low accuracy in reliability calculation.

[0004] As a core theory that closely resembles actual failure scenarios, the integration of the incomplete fault coverage model in reliability calculation is a key support for high-precision demand scenarios. Existing research on calculating the reliability of unmanned aerial vehicle swarms ignores the presence of irrelevant subsystems at the beginning of a stage, resulting in significant deviations between the calculated results and actual failure scenarios, making it difficult to meet the precision requirements of high-reliability demand fields such as military operations and emergency rescue. SUMMARY

[0005] The present application aims to provide a UAV fleet system reliability calculation method based on an incomplete fault coverage model, and the proposed method considers whether an uncovered failure occurs in a non-participating subsystem, which will improve the accuracy of system reliability calculation and will be applicable to multi-stage task systems with higher accuracy requirements.

[0006] The present application is a UAV fleet system reliability calculation method based on an incomplete fault coverage model, comprising the following steps:

[0007] S1, in combination with the multi-stage task characteristics, listing the success probability events of each stage that meet the functional requirements from the subsystem level;

[0008] S2, analyzing and calculating the subsystems required to participate in the subsequent stages and the minimum effective number of UAVs that meet the task success;

[0009] S3, if there are non-participating subsystems in a certain stage, such subsystems are irrelevant subsystems, which have uncovered failure risks, and the reliability of such subsystems in each stage is calculated;

[0010] S4, according to the calculation of the reliability of each subsequent stage in S2 and S3, the reliability of the last stage is the reliability of the entire system.

[0011] Further, the specific implementation of S1 is as follows:

[0012] First, let the total number of initially input UAVs be , and the number of UAVs is , each UAV is composed of subsystems, the number of subsystems is , there are stages, and the number of stages is ; it is assumed that all subsystems have consistent parameter settings, and the number of UAVs required to meet at least each stage is , the number of UAVs remaining after participating in each stage is , the number of UAV subsystems required to participate in each stage is , the reliability of the UAV subsystem is , the failure rate of the subsystem is , the coverage factor is , and each subsystem has its independent coverage mechanism, so the probability of subsystem coverage failure is ;

[0013] From the perspective of the subsystem, list the success probability events that meet the task of each stage, as follows:

[0014] The number of subsystems required for the first stage is at least , and the total number of initially input UAV subsystems is So, in the first phase, assuming the mission succeeds, the maximum allowed is... The drone failed due to a subsystem coverage failure, and this The maximum number of drones allowed A subsystem experienced an overlay failure;

[0015] And so on, the... A stage may allow a maximum of [number] attempts while ensuring the success of the task in that stage. One subsystem experienced a coverage failure; the first The stage allows a maximum of [number] stages, provided the task is successful. A subsystem experienced an overwrite failure.

[0016] Furthermore, in S2, the conditions for analyzing and calculating the subsystems required for subsequent stages and the minimum effective operating volume of the UAV to ensure mission success are: only under the condition of success in the previous stage can the events for completing the mission in subsequent stages be analyzed.

[0017] Furthermore, in S2, the number of remaining available drones from the previous stage is set to... Then the total number of drones initially deployed in the next phase is... That is, the first The total number of subsystems initially deployed in a phase depends on the previous phase. ,in Indicates the first The number of unmanned aerial vehicle (UAV) subsystems in each stage.

[0018] Furthermore, in S3, multi-stage task systems contain subsystems that are relevant to the previous stage but irrelevant to the next stage; that is, in the previous stage... The subsystems involved but not required in the later stage The subsystems involved are called phases. Unrelated subsystems.

[0019] Furthermore, in S3, the quantity is The unrelated subsystems, under the premise of ensuring task success without the occurrence of uncovered failures, are in the stage The reliability calculation is expressed as:

[0020]

[0021] in, Indicating that in guaranteeing the first The number of drones allowed to experience coverage failures assuming the mission phase is successful.

[0022] Furthermore, in S4, the reliability calculation for each stage is divided into two parts. The first part is the operation status of the subsystems involved in the stage, including three cases: normal operation, coverage failure, and non-coverage failure. The second part is the operation status of the unrelated subsystems mentioned in step S3 that do not need to be involved in the stage.

[0023] Furthermore, record the first The reliability of the subsystems involved in the phase is Then the first part is represented as:

[0024]

[0025] in, Represented as the first The number of combinations of subsystems involved in a phase that are allowed to experience coverage failures. This indicates the number of coverage failures that occurred in the subsystems involved. Indicates the first Number of available drones remaining in the phase On this basis, ensure the first The number of combinations in which drones can fail while the mission is successfully completed. The number of drones that experienced coverage failures in the factor system;

[0026] The expression in the second part is... expression;

[0027] Therefore, the reliability of the first stage is:

[0028]

[0029] No. The reliability of the stage is:

[0030]

[0031] No. Phase reliability:

[0032] .

[0033] The present invention also provides a reliability calculation device for an unmanned aerial vehicle (UAV) swarm system based on an incomplete fault coverage model, comprising a processor and a memory. The memory is used to store program instructions, and the processor is used to call the program instructions in the memory to execute the reliability calculation method for an UAV swarm system based on an incomplete fault coverage model as described in the above technical solution.

[0034] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for calculating the reliability of an unmanned aerial vehicle swarm system based on an incomplete fault coverage model as described in the above technical solution.

[0035] The beneficial effects of implementing the present invention's method for accurate reliability calculation and analysis of unmanned aerial vehicle (UAV) swarm systems based on an incomplete fault coverage model are as follows:

[0036] This invention improves the accuracy of UAV swarm reliability calculations in multi-stage mission systems by considering irrelevant subsystems that exist from the early stages of the phase. This method can more realistically reflect the system failure risk caused by incomplete fault coverage in actual operations, and is particularly suitable for applications with high precision and reliability requirements, such as military reconnaissance and disaster relief, providing a more reliable theoretical basis for system design and mission planning. Attached Figure Description

[0037] Figure 1 Structural diagram of a specific embodiment of the present invention;

[0038] Figure 2 A schematic diagram of the structure of the drone of the present invention. Detailed Implementation

[0039] The present invention will be further described below with reference to the accompanying drawings and specific examples.

[0040] This invention provides a method for accurate reliability calculation and analysis of unmanned aerial vehicle (UAV) swarm systems based on an incomplete fault coverage model, specifically including the following steps:

[0041] S1. Combining the characteristics of multi-stage tasks, list the success probability events of each stage in meeting functional requirements from the subsystem level.

[0042] S2. Analyze and calculate the subsystems required for subsequent stages and the minimum effective operating quantity of the UAV to ensure mission success;

[0043] S3. If there are subsystems that do not participate in a certain stage at the beginning, such subsystems are irrelevant subsystems and have the risk of failure due to lack of coverage. Calculate the reliability of such subsystems in each stage.

[0044] S4. Calculate the reliability of each subsequent stage based on S2 and S3. The reliability of the last stage is the reliability of the entire system.

[0045] According to the above scheme, the specific implementation method of step S1 is as follows:

[0046] First, let the initial total number of drones be... Its number is Each drone is composed of It consists of several subsystems connected in series, numbered as follows: There are a total of Each stage is numbered as follows: Assuming all subsystems have identical parameter settings, the minimum number of drones required for each stage is: The number of drones remaining after each phase of operation is The number of unmanned aerial vehicle (UAV) subsystems required to participate in each stage is: The reliability of the drone's subsystems is Then the failure rate of the subsystem is Coverage factor is Furthermore, each subsystem has its own independent overlay mechanism, so the probability of an overlay failure in a subsystem is: ;

[0047] From the perspective of subsystems, the success probability events for fulfilling the tasks at each stage are listed below:

[0048] The number of subsystems required for the first phase is at least [number missing]. The total number of drone subsystems initially deployed was So, in the first phase, assuming the mission succeeds, the maximum allowed is... The drone failed due to a subsystem coverage failure, and this The maximum number of drones allowed A subsystem experienced an overlay failure;

[0049] And so on, the... A stage may allow a maximum of [number] attempts while ensuring the success of the task in that stage. One subsystem experienced a coverage failure; the first The stage allows a maximum of [number] stages, provided the task is successful. A subsystem experienced an overwrite failure.

[0050] According to the above scheme, step S2 considers the dependencies between stages, that is, the next stage can only start running if the previous stage is successful. This conditional probability can be expressed as: ,in, This refers to the probability of success in stage h. Let be the probability.

[0051] According to the above scheme, step S3 considers the existence of subsystems that change from related to unrelated between stages. These unrelated subsystems may experience uncovered failures in subsequent stages. That is, the success of the task in the subsequent stage depends on the absence of uncovered failures in these unrelated subsystems. Therefore, the reliability of these unrelated subsystems is:

[0052] According to the above scheme, the reliability calculations for each stage of step S4 are as follows:

[0053] The reliability of the first stage is:

[0054]

[0055] No. The reliability of the stage is:

[0056]

[0057] No. Phase reliability:

[0058]

[0059] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0060] Example: Small UAV swarm reconnaissance mission (n=4, two-stage mission)

[0061] like Figure 1 As shown, this embodiment targets a reconnaissance group consisting of 4 UAVs, performing a two-stage mission of "launch and reconnaissance (first stage) → return (second stage)," which requires that at least 3 UAVs conduct normal reconnaissance in the first stage and at least 2 UAVs return normally in the second stage.

[0062] Based on the relevant definitions of this invention, the core parameters are set as follows:

[0063]

[0064] The participating drones and their subsystems are numbered as follows:

[0065]

[0066]

[0067]

[0068]

[0069] In the first phase of the task, all three functional subsystems need to participate; in the second phase, only... The participation of two types of subsystems (here) (This refers to the drone's serial number).

[0070] The following will be based on Figure 2 The reliability of the system is calculated and analyzed in the following steps:

[0071] S1. Based on the characteristics of a multi-stage task system, list the success probability events for each stage to meet functional requirements from the subsystem level.

[0072] S2. After the initial stage is successful, analyze the component configuration, functional scope and minimum effective workload required for the subsequent stages.

[0073] Under the premise of ensuring the success of the first phase of the mission, the maximum allowed is If a subsystem fails to cover an area, then the second phase, assuming the task succeeds, can have a maximum of [number missing]. A subsystem experienced an overwrite failure.

[0074] S3. If there are subsystems that do not participate in the initial stage of a certain phase, then such subsystems will become irrelevant, and irrelevant subsystems are at risk of failure due to lack of coverage.

[0075] All three types of subsystems need to participate in the first phase, while in the second phase... These types of subsystems do not require participation, then In the second phase, these irrelevant subsystems become irrelevant; that is, the success of the second phase task depends on the absence of uncovered failures in these irrelevant subsystems. The reliability of these irrelevant subsystems is as follows:

[0076]

[0077] S4. Calculate the reliability of subsequent stages and the overall system based on S2 and S3.

[0078] The reliability calculations for the first phase are as follows:

[0079]

[0080] The reliability of the second phase needs to be considered based on the number of drones remaining from the first phase. As calculated above for the first phase, the probability of having 4 usable drones remaining from the first phase is 0.068719, denoted as [missing value]. The probability of having 3 usable drones remaining is 0.209595, denoted as . Therefore, the second stage needs to be analyzed in two different cases, and the calculation process is as follows:

[0081] 1) Three drones remain available in the first phase;

[0082]

[0083]

[0084] 2) Four drones remain available in the first phase;

[0085]

[0086] Therefore, the reliability of the second stage is:

[0087] .

[0088] As the above analysis shows, each stage of the drone swarm is interdependent, meaning that the start of a subsequent stage depends on the success of the previous stage. Therefore, the reliability of the entire drone swarm is also the reliability of the successful completion of the mission in the final stage.

[0089] .

[0090] In existing reliability calculations for multi-stage UAV swarm systems based on incomplete fault coverage models, the existence of unrelated subsystems in the early stages of a stage is ignored. Under this condition of neglect, the final reliability of the UAV swarm system based on the incomplete fault coverage model is 0.175407.

[0091] This patent improves the accuracy of reliability calculations in the aforementioned cases.

[0092] Matters not covered in this invention are common knowledge.

[0093] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A reliability calculation method for an unmanned aerial vehicle (UAV) swarm system based on an incomplete fault coverage model, characterized in that, The method comprises the following steps: S1, combining the characteristics of multi-stage tasks, listing the success probability events of each stage satisfying the functional requirements from the subsystem layer; S2, analyzing and calculating the subsystems required to participate in the subsequent stages and the minimum effective operation amount of the unmanned aerial vehicle satisfying the task success; S3, if there is a subsystem that does not participate in the initial stage, this type of subsystem is irrelevant subsystem, which exists uncovered failure risk, and the reliability of this type of subsystem in each stage is calculated; S4, according to the calculation of S2 and S3, the reliability of each subsequent stage is calculated, and the reliability of the last stage is the reliability of the entire system.

2. The unmanned aerial vehicle group system reliability calculation method based on the incomplete fault coverage model according to claim 1, wherein the specific implementation of S1 is as follows: First, let the initial input of the total number of UAVs , numbered , each UAV is composed of subsystem in series, numbered , a total of stage, numbered ; assuming all subsystems of various parameters are consistent, each stage needs to satisfy at least the number of UAVs , each stage after the remaining number of UAVs participating in the operation is , the number of UAV subsystems required to participate in each stage is , the reliability of the subsystem of the UAV is , the failure rate of the subsystem is , the coverage factor is and each subsystem has its independent coverage mechanism, so the probability of coverage failure of the subsystem is ; From the perspective of the subsystem, the success probability events satisfying the tasks of each stage are listed as follows: The number of subsystems required in the first stage is at least and the total number of initially input unmanned aerial vehicle subsystems is The first stage allows at most unmanned aerial vehicles to fail due to coverage failure of subsystems, and this unmanned aerial vehicles in the first stage allow at most subsystems to fail due to coverage failure. By analogy, the first phase allows at most one subsystem to fail in coverage, provided that the phase task is successful The second phase allows at most two subsystems to fail in coverage, provided that the task is successful The third phase allows at most three subsystems to fail in coverage, provided that the task is successful 3. The method of claim 1, wherein: In S2, the conditions for analyzing and calculating the minimum effective operation amount of the unmanned aerial vehicle satisfying the task success in the subsequent stages are that the events of completing the tasks in the subsequent stages can be analyzed and calculated only under the condition of success in the previous stage.

4. The method of claim 1, wherein: In S2, the number of remaining available UAVs in the previous stage is set as Then the initial number of UAVs in the next stage is That is, the initial number of subsystems in the first stage is dependent on the previous stage, which is where represents the number of UAV subsystems in the first stage.

5. The method of claim 1, wherein in S3, there are subsystems in the multi-stage mission system that are relevant in the previous stage but irrelevant in the next stage, i.e., the subsystems involved in the previous stage but not required in the next stage are irrelevant subsystems in the stage. ​​​ 6. The method of claim 2, wherein: In S3, the number of unrelated subsystems that do not cause uncovered failures, i.e., guarantee task success, is calculated in phase Reliability of S3 is calculated as follows: ； wherein, represents the number of UAVs allowed to occur coverage failure under the premise of ensuring the success of the first phase task.

7. The method of claim 5, wherein the method further comprises: In S4, the reliability calculation of each stage is divided into two parts, the first part is the operation of the subsystem participating in the stage, including normal operation, coverage failure and uncovered failure, and the second part is the operation of the irrelevant subsystem mentioned in step S3 which does not need to participate in the stage.

8. The unmanned aerial vehicle group system reliability calculation method based on the incomplete fault coverage model according to claim 6, wherein: The first part is represented as: The reliability of the subsystems involved in the phase is The first part is represented as: ； wherein, the number of subsystems involved in the phase that allow the combination of coverage failures to occur, the number of subsystems involved that have coverage failures, the number of UAVs remaining available at the end of the phase the number of combinations of UAV failures allowed under the premise of ensuring the success of the mission in the phase the number of UAVs that have coverage failures due to subsystems; The expression of the second part is also expression; Therefore, the reliability of the first stage is: ； No. The reliability of the stage is: ； No. Phase reliability: 。 9. An unmanned aerial vehicle swarm system reliability computation apparatus based on an incomplete fault coverage model, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the unmanned aerial vehicle group system reliability calculation method based on the incomplete fault coverage model according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the unmanned aerial vehicle group system reliability calculation method based on the incomplete fault coverage model according to any one of claims 1 to 7.

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