CN113962309A - Unmanned ship reliability testing and evaluating method - Google Patents

Unmanned ship reliability testing and evaluating method Download PDF

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Publication number
CN113962309A
CN113962309A CN202111242930.4A CN202111242930A CN113962309A CN 113962309 A CN113962309 A CN 113962309A CN 202111242930 A CN202111242930 A CN 202111242930A CN 113962309 A CN113962309 A CN 113962309A
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failure
simulation
time
unmanned ship
reliability
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武朔晨
方晓彤
刘柏
李占
彭迪
刘树林
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China Institute Of Marine Technology & Economy
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China Institute Of Marine Technology & Economy
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    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
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    • G—PHYSICS
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    • G01M10/00—Hydrodynamic testing; Arrangements in or on ship-testing tanks or water tunnels
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Abstract

The unmanned ship reliability testing and evaluating method provided by the embodiment of the invention comprises a system and equipment composition for collecting the unmanned ship to be evaluated, and a lowest failure agreed level is combed based on task events of the unmanned ship to be evaluated; decomposing a fault tree of the unmanned ship task event to be evaluated to an equipment level based on system and equipment composition; setting the maximum working failure time and simulation times of a reliability test simulation model and failure distribution function characteristic parameters of each basic event of a fault tree, setting the initialization simulation times to be 0, simulating through the reliability test simulation model, randomly sampling failure events of the basic events of the simulation times, and sequencing according to the failure time; counting the failure time of the system after simulation of the simulation times, comparing the failure time with the maximum working failure time, and determining the occurrence probability of failure events; and recording failure time, counting failure distribution of the system, and determining average fault interval time and task reliability of the system.

Description

Unmanned ship reliability testing and evaluating method
Technical Field
The invention relates to the technical field of fault tree analysis and mathematical statistics, in particular to a method for testing and evaluating the reliability of an unmanned ship.
Background
The unmanned surface vehicle not only needs to face severe environments such as high temperature, high humidity and high sea conditions, but also needs to perform high maneuvering behaviors such as tracking and intercepting in an autonomous or semi-autonomous mode, so that the reliability and the safety of the unmanned surface vehicle become important factors for determining the success of combat missions. The unmanned surface vehicle control system is used as an intelligent unit for autonomously executing tasks such as obstacle avoidance and tracking, autonomous positioning and navigation, task planning and decision-making, and the reliability and safety of the unmanned surface vehicle control system are important problems in unmanned vehicle development work.
The water surface unmanned ship control system is used as a core unit of autonomous behavior to directly determine whether a naval ship can normally sail, once faults or hidden dangers such as abnormal control behavior occur, the whole unmanned ship is in an out-of-control state, a task fails if the faults or hidden dangers occur, and major accidents such as equipment damage, collision with other ships and the like occur if the faults or hidden dangers occur.
Therefore, reliability and safety evaluation research of the unmanned ship control system is carried out, a method, means and specifications for verifying the reliability and safety level of the unmanned ship control system are provided, and technical support can be provided for improving the success rate of equipment tasks, reducing the maintenance cost and the like.
Disclosure of Invention
The embodiment of the invention provides a method for testing and evaluating the reliability of an unmanned ship, which is used for decomposing possible faults of the unmanned ship into equipment level fault probability by adopting a fault tree analysis method (FTA), calculating the Mean Time Between Failures (MTBF) of a system and the task success probability (task reliability R) by adopting a method of combining mathematical statistics and simulation through equipment level test data, and further realizing the reliability test and evaluation of the unmanned ship.
The unmanned ship reliability testing and evaluating method provided by the embodiment of the invention comprises the following steps:
collecting system and equipment composition of the unmanned ship to be evaluated, and combing a lowest failure appointment level based on task events of the unmanned ship to be evaluated, wherein the system and equipment composition comprises a system, the system comprises at least one subsystem, and each subsystem comprises at least one piece of equipment;
decomposing the fault tree of the unmanned ship task event to be evaluated to an equipment level based on the system and equipment composition;
setting the maximum working failure time and simulation times of a reliability test simulation model and failure distribution function characteristic parameters of each basic event of the fault tree, and setting the initialization simulation times to be 0, then, performing simulation through the reliability test simulation model, generating random sampling of failure events of the basic events of the simulation times, and sequencing according to the failure time;
counting the failure time of the system after the simulation of the simulation times, comparing the failure time with the maximum working failure time, and determining the occurrence probability of failure events;
and recording the failure time, counting the failure distribution of the system, and determining the mean fault interval time and the task reliability of the system.
In some embodiments of the present invention, the setting of the maximum working failure time and the simulation times of the reliability test simulation model and the failure distribution function characteristic parameters of each basic event of the fault tree includes:
setting the maximum working failure time of the reliability test simulation model as TmaxThe simulation times are N, and the failure distribution function of each basic event of the fault tree is Fi(t)，
Where i is 1,2, 3 … …, n, and n is the number of subsystems of the system.
In some embodiments of the present invention, the simulating by the reliability testing simulation model, generating a random sampling of failure events of the basic events of the simulation times, and sorting according to failure time includes:
setting S for unmanned ship, then S ═ Z1，Z2，…，Zi，…，ZnIn which Z isi(i 1, 2.., n) indicates that the system consists of n subsystems, then,
the top event T of the fault tree is the failure event of the system S, and the bottom event B of the fault treeiI.e. subsystem ZiIf the sampling time of the jth sub-system is represented as t in the jth sampling, the failure time sampling value of the ith sub-system is represented as tijThen, there are:
tij＝Fi -1(ηij)
wherein eta isijIs the random number of random sampling at the j sampling time of the ith subsystem;
and further determining the j sample, wherein the state of the ith subsystem at the t moment is as follows:
Figure BDA0003319850040000022
determining the state of a system S of the unmanned ship at a moment t;
and further, when the jth sampling is statistically calculated, the failure time of the system is as follows:
Figure BDA0003319850040000031
if the simulation is performed in the jth test, n basic bottom events generated by random sampling are as follows:
Z1，Z2，…，Zi，…，Znthen, the corresponding failure time is t1，t2，…，ti，…，tn；
And sequencing the n failure times according to the failure times, wherein the result is as follows:
Figure BDA0003319850040000037
in some embodiments of the present invention, the counting failure time of the system after performing the simulation for the simulation times, and comparing the failure time with the maximum working failure time to determine the probability of occurrence of the failure event includes:
sequentially combining basic bottom events Zk' put into failure state, corresponding to j sampling, the sampling value of the failure times of the system is recorded as tkI.e. tk＝tkj＝tfkDetecting whether the system S fails simultaneously, and determining based on the detection result
Figure BDA0003319850040000032
If the value of (2) is invalid, 1 is taken, and if the value of (2) is not invalid, 0 is taken, so that:
Figure BDA0003319850040000033
after n times of simulation operation, counting in intervals, wherein the calculation method for counting the distribution condition of the system failure number is as follows:
setting the maximum working failure time of the system in the process of executing the task as TmaxDividing into m sub-intervals, and counting the system interval (t)r-1，tr) The internal failure number is:
Figure BDA0003319850040000034
tr-1＜tk＜tr
t≤trthe number of failures for this process is:
Figure BDA0003319850040000035
tk≤tr
probability of occurrence of failure event F of the sections(t) is
Figure BDA0003319850040000036
In some embodiments of the invention, the determining the mean time between failure and the mission reliability of the system comprises:
computing a system failure probability distribution ps(tr) Comprises the following steps:
Figure BDA0003319850040000041
(tr-1＜t＜tr)，
the mean time between failure MTBF of the system is:
MTBF＝E(ξ)
Figure BDA0003319850040000042
the system task reliability R is as follows:
Figure BDA0003319850040000043
the unmanned ship reliability testing and evaluating method provided by the embodiment of the invention has the following advantages: the reliability of the unmanned ship is tested and evaluated based on a fault tree analysis method (FTA) and mathematical statistics, the fault tree analysis method (FTA) decomposes possible faults of the unmanned ship into equipment level fault probability, and system Mean Time Between Failures (MTBF) and task success probability (task reliability R) are calculated by combining the mathematical statistics and simulation method through equipment level test data, so that the reliability test and evaluation of the unmanned ship are realized.
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FIG. 1 is a schematic flow chart of a method for testing and evaluating the reliability of an unmanned ship according to an embodiment of the present invention;
fig. 2 is a diagram illustrating decomposition of a task event fault tree into device levels in the unmanned ship reliability testing and evaluating method according to the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be further described with reference to the accompanying drawings and detailed description.
The phrases "in one embodiment," "in another embodiment," "in yet another embodiment," "in an embodiment," "in some embodiments," or "in other embodiments" may be used in this specification to refer to one or more of the same or different embodiments in accordance with the invention.
Specific embodiments of the present invention are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the invention, which can be embodied in various forms. Well-known and/or repeated functions and configurations have not been described in detail so as to avoid obscuring the invention in unnecessary or unnecessary detail based on the user's historical actions. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriately detailed structure.
The embodiment of the invention provides a method for testing and evaluating the reliability of an unmanned ship, which comprises the following steps of:
collecting system and equipment composition of the unmanned ship to be evaluated, and combing a lowest failure appointment level based on task events of the unmanned ship to be evaluated, wherein the system and equipment composition comprises a system, the system comprises at least one subsystem, and each subsystem comprises at least one piece of equipment;
decomposing the fault tree of the unmanned ship task event to be evaluated to an equipment level based on the system and equipment composition;
setting the maximum working failure time and simulation times of a reliability test simulation model and failure distribution function characteristic parameters of each basic event of the fault tree, and setting the initialization simulation times to be 0, then, performing simulation through the reliability test simulation model, generating random sampling of failure events of the basic events of the simulation times, and sequencing according to the failure time;
counting the failure time of the system after the simulation of the simulation times, comparing the failure time with the maximum working failure time, and determining the occurrence probability of failure events;
and recording the failure time, counting the failure distribution of the system, and determining the mean fault interval time and the task reliability of the system.
When the reliability of the unmanned ship is tested and evaluated by adopting the technical content provided by the invention, a fault tree analysis method (FTA) is adopted for analysis, which is a common method for analyzing the reliability of a certain system, on one hand, the analysis method can qualitatively analyze certain indexes which cannot be quantified, on the other hand, the analysis method can also analyze indexes which can be quantified by the unmanned ship, and in addition, the analysis method mainly establishes main reasons and indirect reasons of each behavior event of system failure and establishes a logical relationship from the main reasons and the indirect reasons, so that potential accidents of each subsystem can be searched in each task event of the unmanned ship, some diagnoses can be provided in the use and maintenance stage in the stage process of executing other tasks by the unmanned ship, and a reasonable and quantitative basis is provided for improving the design of the unmanned ship.
During the process of fault tree analysis of the unmanned ship, the fault tree construction directly influences the qualitative and quantitative analysis results of the task event. And selecting an event that the unmanned ship fails to execute a certain task as a top event, constructing a fault tree, using other called subsystems as a bottom event and an intermediate event, and establishing the relationship between the called subsystem and the task through the relationship of a logic gate.
Aiming at qualitative analysis, the unmanned ship needs to find the minimum cut set causing failure of a certain task event, so that the unmanned ship management personnel can be helped to find potential faults in the task process, and the task link can be redesigned, so that the degree that a certain weak link influences the task in the task execution process is reduced. However, there are many methods for solving the minimal cut set with task failure, such as solving the minimal cut set by an uplink and downlink method. However, the method of solving in the uplink is adopted herein. The algorithm has the main idea that: in the fault tree of a certain kind of tasks for a given unmanned ship, several events are combined through several logic gates, starting from the underlying event. From bottom to top, the elimination of redundant events is completed through a Boolean algorithm in the expansion process, so that the bottom layer event or bottom layer system equipment with failure in the task process is obtained. For example, in a certain task traveling process, the minimum cut set corresponding to the reliability of the unmanned ship is the sum of a series of bottom layer probabilities formed by a plurality of minimum cut sets.
The task of quantitative analysis is to utilize a fault tree of the unmanned ship as a calculation model, and evaluate the reliability of a certain type of tasks when the system goes out by solving the reliability degree of a top event, namely the task, under the condition that the occurrence probability of failure of a bottom event, namely subsystem equipment is known.
Specifically, x may bei(t) as the state of the subsystem i at the time t, and then expressed by adopting a binary distribution, wherein the state is as follows:
Figure BDA0003319850040000061
in the same principle, in this embodiment, a binary variable Φ (X) is used to represent the state of the task T at time T, and since the task state is completely determined by the subsystem state, the state variable value of the task is also completely determined by the subsystem state variable value that completes the task, and then:
Figure BDA0003319850040000062
assuming that there are k minimal cut sets in the fault tree of the unmanned ship trip mission, each minimal cut set can be expressed as:
Figure BDA0003319850040000063
the structural function of the fault tree is:
Figure BDA0003319850040000064
if the probability of occurrence of the top event is defined as g ═ P { phi (X) ═ 1 }; since φ (X) takes only 0 or 1, g is recorded as:
Figure BDA0003319850040000065
further, in some embodiments of the present invention, the setting of the maximum working failure time and the simulation times of the reliability test simulation model and the failure distribution function characteristic parameters of each basic event of the fault tree includes:
setting the maximum working failure time of the reliability test simulation model as TmaxThe simulation times are N, and the failure distribution function of each basic event of the fault tree is Fi(t)，
Where i is 1,2, 3 … …, n, and n is the number of subsystems of the system.
In this embodiment, the simulating by the reliability test simulation model to generate a random sampling of failure events of the basic events of the simulation times, and sorting the failure events according to failure time includes:
setting S for unmanned ship, then S ═ Z1，Z2，…，Zi，…，ZnIn which Z isi(i 1, 2.., n) indicates that the system consists of n subsystems, then,
the top event T of the fault tree is the failure event of the system S, and the bottom event B of the fault treeiI.e. subsystem ZiIf the sampling time of the jth sub-system is represented as t in the jth sampling, the failure time sampling value of the ith sub-system is represented as tijThen, there are:
tij＝Fi -1(ηij)
wherein eta isijIs the random number of random sampling at the j sampling time of the ith subsystem;
further, when the jth sample is determined, the state of the ith subsystem (bottom event) at time t is:
Figure BDA0003319850040000071
determining the state of a system S of the unmanned ship at a moment t;
and further, when the jth sampling is statistically calculated, the failure time of the system is as follows:
Figure BDA0003319850040000072
if the simulation is performed in the jth test, n basic bottom events generated by random sampling are as follows:
Z1，Z2，…，Zi，…，Znthen, the corresponding failure time is t1，t2，…，ti，…，tn；
And sequencing the n failure times according to the failure times, wherein the result is as follows:
Figure BDA0003319850040000073
further, in this embodiment, the counting failure time of the system after the simulation of the simulation times, and comparing the failure time with the maximum working failure time to determine the probability of occurrence of the failure event includes:
sequentially combining basic bottom events Zk' put into failure state, corresponding to j sampling, the sampling value of the failure times of the system is recorded as tkI.e. tk＝tkj＝tfkDetecting whether the system S fails simultaneously, and determining based on the detection result
Figure BDA0003319850040000081
Taking the value of (1) if the value is invalid, and taking the value of (0) if the value is not invalid;
specifically, the base background event Z may be preceded1' put to a failure state
Figure BDA00033198500400000810
And the rest basic events are not invalid at the moment, checking whether the system S is invalid at the same time, and determining whether the system S is invalid or not according to the judgment result
Figure BDA0003319850040000082
The value is 1; if the system does not fail, the event Z of the basic bottom is processed2Put into a failure state
Figure BDA0003319850040000089
Checking is repeated until the basic event Z by checking again whether the system S is disabledk' failure occurs if the unmanned ship subtask is completed at this time, i.e., the system is in a failure state, then
Figure BDA0003319850040000083
1, and the sample value of the number of system failures at the j-th sample is recorded as tkAnd it takes t as the valuek＝tkj＝tfkAnd ending the jth operation. The following can be obtained:
Figure BDA0003319850040000084
after n times of simulation operation, counting in intervals, wherein the calculation method for counting the distribution condition of the system failure number is as follows:
setting the maximum working failure time of the system in the process of executing the task as TmaxDividing into m sub-intervals, and counting the system interval (t)r-1，tr) The internal failure number is:
Figure BDA0003319850040000085
tr-1＜tk＜tr
t≤trthe number of failures for this process is:
Figure BDA0003319850040000086
tk≤tr
probability of occurrence of failure event F of the sections(t) is
Figure BDA0003319850040000087
(t≤tr) Further, it is possible to obtain:
Figure BDA0003319850040000088
in this embodiment, the determining the mean time between failures and the task reliability of the system includes:
computing a system failure probability distribution ps(tr) Comprises the following steps:
Figure BDA0003319850040000091
(tr-1＜t＜tr)，
the mean time between failure MTBF of the system is:
MTBF＝E(ξ)
Figure BDA0003319850040000092
the system task reliability R is as follows:
Figure BDA0003319850040000093
basic part importance W (Z)i) Is defined as:
Figure BDA0003319850040000094
mode importance W of base eventsN(Zi) Is defined as：
Figure BDA0003319850040000095
According to the technical scheme, the unmanned ship reliability testing and evaluating method provided by the embodiment of the application tests and evaluates the reliability of the unmanned ship based on a fault tree analysis method (FTA) and mathematical statistics, the fault tree analysis method (FTA) decomposes possible faults of the unmanned ship into equipment level fault probability, and the average fault interval time (MTBF) and task success probability (task reliability R) of the system are calculated by combining the mathematical statistics and simulation methods through equipment level test data, so that the reliability of the unmanned ship is tested and evaluated.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.

Claims (5)

1. A method for testing and evaluating the reliability of an unmanned ship is characterized by comprising the following steps:
collecting system and equipment composition of the unmanned ship to be evaluated, and combing a lowest failure appointment level based on task events of the unmanned ship to be evaluated, wherein the system and equipment composition comprises a system, the system comprises at least one subsystem, and each subsystem comprises at least one piece of equipment;
decomposing the fault tree of the unmanned ship task event to be evaluated to an equipment level based on the system and equipment composition;
setting the maximum working failure time and simulation times of a reliability test simulation model and failure distribution function characteristic parameters of each basic event of the fault tree, and setting the initialization simulation times to be 0, then, performing simulation through the reliability test simulation model, generating random sampling of failure events of the basic events of the simulation times, and sequencing according to the failure time;
counting the failure time of the system after the simulation of the simulation times, comparing the failure time with the maximum working failure time, and determining the occurrence probability of failure events;
and recording the failure time, counting the failure distribution of the system, and determining the mean fault interval time and the task reliability of the system.
2. The unmanned ship reliability testing and evaluating method according to claim 1, wherein the setting of the maximum working failure time, the simulation times of the reliability testing simulation model and the failure distribution function characteristic parameters of each basic event of the fault tree comprises:
setting the maximum working failure time of the reliability test simulation model as TmaxThe simulation times are N, and the failure distribution function of each basic event of the fault tree is Fi(t)，
Where i is 1,2, 3 … …, n, and n is the number of subsystems of the system.
3. The unmanned ship reliability test and evaluation method of claim 2, wherein the simulating by the reliability test simulation model, generating a random sampling of failure events of the basic events of the simulation times, and sorting by failure time, comprises:
setting S for unmanned ship, then S ═ Z1,Z2,…,Zi,…,ZnIn which Z isi(i-1, 2, …, n) indicates that the system consists of n subsystems, then,
the top event T of the fault tree is the failure event of the system S, and the bottom event B of the fault treeiI.e. subsystem ZiIf the sampling time of the jth sub-system is represented as t in the jth sampling, the failure time sampling value of the ith sub-system is represented as tijThen, there are:
Figure FDA0003319850030000011
wherein eta isijIs the random number of random sampling at the j sampling time of the ith subsystem;
and further determining the j sample, wherein the state of the ith subsystem at the t moment is as follows:
Figure FDA0003319850030000021
determining the state of a system S of the unmanned ship at a moment t;
and further, when the jth sampling is statistically calculated, the failure time of the system is as follows:
Figure FDA0003319850030000022
if the simulation is performed in the jth test, n basic bottom events generated by random sampling are as follows:
Z1，Z2，…，Zi，…，Znthen, the corresponding failure time is t1，t2，…，ti，…，tn；
And sequencing the n failure times according to the failure times, wherein the result is as follows:
Figure FDA0003319850030000023
4. the unmanned ship reliability testing and evaluating method according to claim 3, wherein the counting failure time of the system after the simulation of the simulation times, and comparing the failure time with the maximum operation failure time to determine the occurrence probability of the failure event comprises:
sequentially combining basic bottom events Zk' put into failure state, corresponding to j sampling, the sampling value of the failure times of the system is recorded as tkI.e. tk＝tkj＝tfkDetecting whether the system S fails simultaneously, and determining based on the detection result
Figure FDA0003319850030000024
If the value of (2) is invalid, 1 is taken, and if the value of (2) is not invalid, 0 is taken, so that:
Figure FDA0003319850030000025
after n times of simulation operation, counting in intervals, wherein the calculation method for counting the distribution condition of the system failure number is as follows:
setting the maximum working failure time of the system in the process of executing the task as TmaxDividing into m sub-intervals, and counting the system interval (t)r-1，tr) The internal failure number is:
Figure FDA0003319850030000026
t≤trthe number of failures for this process is:
Figure FDA0003319850030000027
probability of occurrence of failure event F of the sections(t) is
Figure FDA0003319850030000031
5. The unmanned-vessel reliability testing and evaluation method of claim 4, wherein the determining of mean time between failure and mission reliability of the system comprises:
computing a system failure probability distribution ps(tr) Comprises the following steps:
Figure FDA0003319850030000032
the mean time between failure MTBF of the system is:
MTBF＝E(ξ)
Figure FDA0003319850030000033
the system task reliability R is as follows:
Figure FDA0003319850030000034
CN202111242930.4A 2021-10-25 2021-10-25 Unmanned ship reliability testing and evaluating method Pending CN113962309A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114580842A (en) * 2022-01-25 2022-06-03 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） Vehicle dispatch reliability analysis method and device and computer equipment

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114580842A (en) * 2022-01-25 2022-06-03 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） Vehicle dispatch reliability analysis method and device and computer equipment

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