A simulation method for ship mission system under complex constraints

Abstract

The embodiment of the present invention provides a method for simulating a ship mission system under complex constraint conditions, including: setting simulation constraint conditions, generating the initial operating state of the ship mission system, obtaining the operating state of the ship mission system at any time for this simulation task according to the established operating state transfer equation of the ship mission system; judging whether this simulation task has reached the end condition according to the operating state of the ship mission system at any time and the running time of the ship mission system at this time; when this simulation task reaches the end condition, executing the next simulation task until the total number of simulation tasks reaches the number of simulation times; calculating the success rate of all simulation tasks. The embodiment of the present invention models and simulates the success of the ship mission system under various complex constraint conditions, accurately analyzes the main factors affecting the success of the ship mission system, and provides a basis for the availability of the ship mission system.

Description

Technical Field

[0001] The present invention relates to the field of ship equipment, and more specifically, to a method for simulating a ship mission system under complex constraint conditions. Background Art

[0002] The ship mission system will be subject to various constraints and restrictions during the mission, including usage constraints, maintenance constraints and support resource constraints, etc. These constraints and restrictions will affect the success of the mission system.

[0003] Therefore, it is necessary to deeply analyze the main usage constraints, maintenance constraints and support resource constraints that affect the operation of ship mission systems, and study the modeling and simulation of mission system success under these constraints, so as to quantitatively analyze the main factors affecting mission success. Summary of the invention

[0004] The embodiment of the present invention provides a method for simulating a ship mission system under complex constraints that overcomes the above problems or at least partially solves the above problems, and can quantitatively analyze the main factors that affect the success of the ship mission system.

[0005] The embodiment of the present invention provides a method for simulating a ship mission system under complex constraints, including:

[0006] S1, setting initial simulation parameters, wherein the initial simulation parameters at least include usage constraints, maintenance constraints, support resource constraints, end conditions of each simulation task, and simulation times of the ship mission system;

[0007] S2, generating the initial operation state of the ship mission system. For this simulation task, according to the established operation state transfer equation of the ship mission system, the operation state of the ship mission system at any time is obtained;

[0008] S3, judging whether the simulation task has reached the end condition according to the running state of the ship task system at any time and the running time of the ship task system at this time;

[0009] S4, when the simulation task reaches the end condition, the next simulation task is executed, and S2-S4 are repeated until the total number of simulation tasks reaches the simulation number;

[0010] S5, calculate the success rate of all simulation tasks.

[0011] An embodiment of the present invention provides a method for simulating the success of a ship mission system under complex constraint conditions. By modeling and simulating the success of a ship mission system under various complex constraint conditions, the main factors affecting the success of the ship mission system are accurately analyzed, providing a basis for the availability of the ship mission system. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flow chart of a method for simulating the success of a ship mission system under complex constraints provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0014] Figure 1 FIG. 1 is a flow chart of a method for simulating a ship mission system under complex constraints provided by an embodiment of the present invention. Figure 1 As shown, the simulation method includes: S1, setting initial simulation parameters, the initial simulation parameters at least include the use constraints, maintenance constraints, support resource constraints, end conditions of each simulation task and the number of simulations of the ship mission system; S2, generating the initial operation state of the ship mission system, for this simulation task, according to the established operation state transfer equation of the ship mission system, obtaining the operation state of the ship mission system at any time; S3, judging whether this simulation task reaches the end condition according to the operation state of the ship mission system at any time and the running time of the ship mission system at this time; S4, when this simulation task reaches the end condition, executing the next simulation task, repeating S2-S4 until the total number of simulation tasks reaches the number of simulations; S5, calculating the success rate of all simulation tasks.

[0015] It is understandable that the ship mission system will be subject to various constraints and restrictions during the mission, including usage constraints, maintenance constraints, and support resource constraints, which will affect the success of the mission system. Therefore, it is necessary to deeply analyze the main usage constraints, maintenance constraints, and support resource constraints that affect the operation of the ship mission system, and study the modeling and simulation of the mission system success under these constraints, so as to quantitatively analyze the main factors affecting the success of the mission system.

[0016] Based on this, an embodiment of the present invention proposes to simulate the success of a ship mission system under complex constraints, and to set initial simulation parameters, including various complex constraints, the end conditions of each simulation task, and the total number of simulations. When the simulation starts, the initial running state of each simulation task is generated. For any simulation task, the running state of the ship mission system at any time is obtained according to the established running state transfer equation of the ship mission system. At any time, it can be determined whether the task is finished by the running state of the ship mission system and the time the ship mission system has been running at this time. If it is finished, it is recorded whether the task is successful or failed. After the simulation of this task is completed, the next task is simulated until the number of simulation tasks reaches the set total number of simulation tasks.

[0017] Count the number of successes and failures in all simulation tasks, and calculate the success rate of all simulation tasks.

[0018] In a possible implementation manner, it can be understood that during the execution of a mission by a ship mission system, the main factors affecting the operation of the mission system generally include three aspects: usage constraints, maintenance constraints, and support resource constraints.

[0019] Among them, in the process of the ship mission system performing the specified tasks, the operator not only needs to complete the specified tasks efficiently, but also needs to take into account the operation of other tasks of the ship, and often puts forward certain usage constraints or restrictions on the use of some units that make up the mission system. These usage constraints or restrictions on units are often reflected in the usage rules. For example, common mission system usage constraints include:

[0020] (1) Maximum duration of unit status. During the execution of a task, the task system limits the continuous operation time of some units in a certain state. For example, in a redundant task system composed of a main unit and a backup unit, when the main unit fails, the backup unit will take over the corresponding function. However, since the functional accuracy of the backup unit is lower than that of the main unit, in order to meet the task requirements, the maximum operation time of the backup unit is usually specified.

[0021] When some units have a maximum duration, these constraints will affect the state transfer process of the task system. i In state S i The duration exceeds T i,max When the task system enters the current state, it will cause the task system to fail to meet the specified accuracy requirements. When unit A i Transition from other states to state S i , at this time, unit A i Status S i The actual duration is:

[0022]

[0023] Among them, T i (k) It is unit A i In state S i The corresponding life under the condition of unit A i Affected by the maximum duration, it indirectly affects the state transition of the task system.

[0024] (2) Minimum duration constraint of unit state, i.e., limiting the minimum duration of some units in the ship mission system in a certain state, such as the minimum startup time of the inertial navigation device. Similarly, when unit A i In state S i The minimum duration is T i,min When the system enters the current state When unit A i Transition from other states to state S i , at this time, the state S should be generated i The corresponding distribution of random variables T i (k) At this time, unit A i Status S i The actual duration is:

[0025]

[0026] For the maintenance constraint analysis of ship mission systems, in order to effectively improve the success of mission systems, it is necessary not only to repair faulty units in a timely manner, but also to stipulate maintenance requirements for units based on the unit's usage and maintenance characteristics, such as regular maintenance and upkeep of units, regular repairs, etc. These unit maintenance requirements can improve the unit's availability, thereby affecting the success of the mission system. Common system maintenance constraints include:

[0027] (1) Maximum allowable maintenance time constraint of units. In ship systems, some units need to be repaired in a timely manner after failure, that is, the faulty unit must be repaired within a specified time range, otherwise the mission will fail. For such units, a maximum allowable maintenance time limit is often specified.

[0028] If the system contains units with such maintenance constraints, let unit A i The maximum allowable maintenance time is T rmax , add a state S to the system failure state set i-error , indicating that due to unit A i The state caused by failure to successfully repair within the allowed time. When the unit enters the fault state from other states and the system state changes to When the unit is repaired immediately, the repair time is T ir If T ir ≤T rmax , that is, unit A is repaired within the specified maximum allowed time i , which does not affect the subsequent state transfer of the system; if T ir >Trmax, i.e. unit A is not repaired within the specified maximum allowable time i , then the system is in state Lasts at most T rmax duration, then enters fault state S i-error .

[0029] (2) Unit regular maintenance constraints: For important units in the mission system, regular maintenance can be adopted to prevent failures before they occur. After regular maintenance, the unit performance is restored to its original state, reducing the failure rate and improving the success of the mission system.

[0030] In order to effectively maintain the availability of ship equipment, the support resources of ship mission systems must be reasonably allocated to maintain relevant maintenance personnel, technical data, spare parts, support equipment and other support resources to provide support for giving full play to the combat effectiveness of ship equipment. Among the many ship equipment support factors, compared with the maintenance ability of maintenance personnel and the support ability of maintenance equipment, the spare parts support ability is the main factor affecting the availability of equipment / systems and the success of various tasks. Due to the limitations of the internal space environment of the ship, ship equipment is usually repaired by replacing parts. If the required spare parts cannot be obtained during the equipment maintenance process, the equipment cannot be repaired in time, which affects the mission system to complete the specified tasks. For ship mission systems, during long-term maritime missions far away from the mainland, the replenishment of various support resources (especially spare parts for maintenance) is often long and costly, which determines that the spare parts required for equipment maintenance and support should be mainly carried on board. This limited spare parts resource will directly affect the success of the mission system.

[0031] After defining the usage constraints and maintenance constraints of the ship mission system, the mechanism of their effects on mission success is introduced.

[0032] During the operation of the ship mission system, the operation process of the mission system is changed due to the constraints of factors such as use, maintenance, and support resources, which ultimately affect the success of the mission system. Among these factors, use factors and maintenance factors often directly affect the state maintenance and state transfer direction of the mission system, while support resources and other factors mainly affect maintenance activities.

[0033] Assume that the current operating state of the ship mission system is In the ship mission system operation state The number of units in working state and fault state is h (1≤h≤n). It can be considered that these units are the first h units of the ship mission system. The corresponding h units are A 1 ,A 2 ,...,A h , is the operating status of each of the h units of the ship mission system; The operating durations of h units in this operating state are respectively

[0034] Ship mission system in operation The running duration of The relationship between the usage constraint, maintenance constraint, support resource constraint, and the operating duration of the h units in this operating state can be expressed as:

[0035]

[0036] Among them, Use_restrn, Rep_restrn, and Res_restrn represent usage constraints, maintenance constraints, and support resource constraints, respectively.

[0037] It can be seen from the above formula that although the duration of each unit state follows an exponential distribution under unconstrained conditions, the system state is subject to constraints such as use, maintenance, and support resources. The duration of The distribution law no longer obeys the exponential distribution.

[0038] Further analysis shows that although the constraints such as usage constraints, maintenance constraints and support resource constraints affect the state maintenance and state transfer of the task system, they do not affect the inherent life law and maintenance law of the unit, that is, the operation law of each unit is still memoryless. Therefore, the operation state transfer of the task system still has the Markov property, that is, under the constraints of usage, maintenance and support resources, the operation process of the task system actually obeys the Markov update process.

[0039] In a possible implementation manner, S2 includes: constructing an expression equation for the state duration of the ship mission system in the kth operating state; establishing a decision condition for the ship mission system to transfer from the kth operating state to the (k+1)th operating state according to the state duration of the ship mission system in the kth operating state and the state duration of each unit; based on the established decision condition for the transfer of the operating state of the ship mission system, constructing a state transfer matrix between every two operating states in the operating state set of the ship mission system, wherein the state transfer matrix describes the operating state set of the ship mission system and whether transfer can be made between every two operating states.

[0040] It can be understood that the above analysis is performed on the running duration of the task system in various states, and the following analysis is performed on the running state transition process of the task system at different times.

[0041] Assume that the task system consists of n units, denoted as A 1 ,A 2 ,...,A n , where unit A i During the task, a total of m i states, respectively It is assumed that the duration of all units in each state follows an exponential distribution. At this time, the state of the task system can be expressed as S system =(S 1 ,S 2 ,....,S n ). At the same time, according to the success judgment criteria of the task system, the state set of the task system {Se system} is divided into the success state set {Sw system} and the failure state set {Sf system}.

[0042] (1) Simulation representation of unit state. For unit A i For a total of m i The duration of a state is mainly determined by the unit's own performance and maintenance resources. In particular, if unit A i If there is a standby state, the duration of its standby state will be determined by the status of other units. As long as other units can successfully complete the system task, unit A i will not change its state; otherwise, unit A i From standby state to other state to take on system tasks. Therefore, if unit A i There is a spare state, the mth i The state is set as standby state and m i-1 variables They represent the current system state, unit Ai In its 1st, 2nd, ..., mth i-1 The duration of this state. i m i The states are mutually exclusive, so the variable There is at most one non-zero variable, which represents unit A. i is in the state corresponding to the variable; if all variables are 0, it means that unit A i In the mth i The state is the standby state. i If there are no alternate states, the number of variables is equal to the number of states of the unit.

[0043] (2) Simulation representation of usage constraints. Under unconstrained conditions, the state duration of the task system is actually the minimum duration of the current working conditions of all units, and the transfer direction of the task system is determined by the unit that changes its state earliest. Under conditions with usage restrictions, the duration of the units that make up the task system in the system state should also meet the usage constraints. Therefore, the usage constraints can be expressed by the life or maintenance time of the unit. For example, for the collective heading measurement system, in order to maintain the measurement accuracy, the single maximum continuous working time T of the gyrocompass is proposed C,max , the startup time of the inertial navigation device is not less than T s,min At this time, the usage constraints of the task system are:

[0044] Use_restrn={min(T As ,T Bs )≥T s,min ,T C ≤T C,max};

[0045] Among them, T As ,T Bs ,T C They are the start-up time of inertial navigation devices A and B and the single working time of the gyrocompass.

[0046] (3) Simulation representation of maintenance constraints. Relatively speaking, maintenance constraints and support resource constraints not only involve many factors, but also have various forms of constraints. It is necessary to determine the representation method of maintenance constraints and support resource constraints according to the characteristics of different mission systems. For example, for a heading measurement system, from the perspective of improving the availability of the gyrocompass, the gyrocompass is usually regularly inspected, and the inspection interval is T. Cr , that is, when the cumulative trouble-free operation time of the gyrocompass exceeds T Cr When the gyrocompass is in state In working state, then in state At the end, the cumulative working time of the gyrocompass is:

[0047]

[0048] like The gyrocompass is shut down for maintenance. C,op =0, gyrocompass working T C,w Regenerate; if The gyrocompass is not repaired. If the gyrocompass is in the next state If it is still in working condition, the gyrocompass does not need to be repaired.

[0049] (4) Simulation representation of support resource constraints. Support resources are the main constraint factors affecting mission success. Due to the complexity of spare parts configuration schemes, analyzing the impact of each spare part on mission success one by one will not only make the model extremely complex, but also make it difficult to simply convert the military requirements of different missions into support requirements for ship spare parts. As a result, the current configuration of ship-carried spare parts is mainly based on experience, rather than military requirements. This is an important reason why the ship's spare parts support capability is generally low.

[0050] In order to better establish the system mission success model, the embodiment of the present invention equates the ship spare parts to the whole machine backup of the equipment (unit) to simplify the complexity of mission success modeling. Assuming that the mission system consists of n units, the whole machine redundancy of the i-th unit is n i (i=1,2,...,n), then the spare parts resource constraint can be expressed as:

[0051]

[0052] Among them, F i (k) Indicates that the task system is in state Time Unit A i The cumulative number of failures. Obviously, when F i (k) >n i When , the cumulative number of failures of unit i exceeds the redundancy of the whole machine, that is, there are no spare parts available for maintenance. At this time, unit i is always in a faulty state and cannot work.

[0053] When the system is in state At the start time, the state of each unit in this state is obtained. Suppose that h (1≤h≤n) units are in working or maintenance state, and the corresponding state durations are If unit A i Status S i (k) For S ij , then T i (k) =Tij According to the competition model of the task system operation status, the system is in the current state Duration At this time, does the task system enter the next state? depending on:

[0054]

[0055] Indicates unit A L The state change occurs first under the conditions of satisfying the use, maintenance and support resource constraints, and the next state of the system state transition is determined according to the use rules of the mission system. End, that is, the system status At the start time, update the status of all units in the system and their duration. i Entering a new state S ij , then its duration is regenerated as a random variable that obeys the distribution type and parameters corresponding to the new state, that is, T i (k+1) =T ij' , and update T ij =0; if unit A is not in standby state i Keep the current state unchanged, then the state duration of the unit is updated.

[0056] In a possible implementation manner, based on the established judgment condition of the ship mission system operation state transition, the operation state set of the ship mission system is constructed, and the state transition matrix between each two operation states is specifically as follows: system}, let the ship mission system operation state set {Se system There are N running states in total, denoted as Se 1 ,Se 2 ,...,Se N ; According to the work flow of the ship mission system, determine whether the ship mission system can be changed from the running state Se i Directly transfer to the running state Se in one step j , and use a ij represents, where:

[0057]

[0058] In this way, the ship mission system operation state transfer matrix A = (a ij ) N×N , where the elements in the operating state transfer matrix A include 0 and 1, reflecting the possible transition of the system state. Obviously, if the system state Sei is a successful state, the system can transfer from this state to other states, that is, a ij (1≤j≤N) are not all 0; otherwise, the system state is an absorbing state, that is, a ij =0(1≤j≤N).

[0059] The kth operating state experienced by the ship mission system from the start of the mission is the ship mission system operation status set {Se system}, the kth state of the ship mission system We can use the N-dimensional unit row vector x (k) Indicates that, where x (k) =(0,0,...,1,0,...0), the i-th element of the vector is 1, and the other elements are all 0. Using the ship mission system operation state transfer matrix A, determine the state vector x of the ship mission system transferred from the k-th operation state to the (k+1)-th operation state (k+1) For x (k+1) =x (k) ·A; if x (k+1) is a unit vector, indicating the (k+1)th operating state of the ship mission system is unique, the vector x (k+1) The position of the non-zero element in corresponds to the (k+1)th operating state of the ship mission system; if x (k+1) is a zero vector, indicating that there is no (k+1)th operating state, that is, the current kth operating state is the absorbing state of the ship mission system, indicating mission failure; if x (k+1) It is neither a unit vector nor a zero vector, indicating the (k+1)th operating state of the ship mission system. There are multiple possibilities. The selection of the (k+1)th operating state depends on the operating state of the unit that first changes its state among the multiple units constituting the ship mission system. At this time, it is necessary to compare the state durations of these units in the kth state.

[0060] In a possible implementation manner, judging whether the simulation task has reached the termination condition according to the running state of the ship task system at any moment and the running time of the ship task system at that moment includes: determining the current running state of the simulation task and the running time of the ship task system at the current moment according to the initial running state of the simulation task and the running state transfer equation; when the current running state of the simulation task is a fault state or the running time of the ship task system reaches the set task running time, the simulation task ends and records whether the simulation task is successful.

[0061] Among them, when the simulation task ends, if the current running state of the simulation task is a fault state, the simulation task execution fails; if the running time of the simulation task reaches the set task running time, the simulation task execution is successful.

[0062] It is understandable that, assuming the running time of each simulation task is T all , at this time, the task system has been running for T. If T<T all , the system state enters the failure state set {Sf system}, then the task fails; if T = T all , the system state is still in the successful state set {Sw system}, then the task is successful.

[0063] Since the simulation process involves the generation of a large number of random numbers, the results of a single task are also random. When the simulation process is repeated R times, the number of successful tasks R is recorded. s ,but is the frequency of successful tasks obtained by simulation. According to the law of large numbers, when the number of simulations R increases infinitely, the frequency of successful tasks Converges to the task success rate according to probability. Therefore, when the number of simulations R is large enough, It approximates the success rate of the task. Usually, the number of simulations R can be between 10,000 and 100,000. After the simulation is completed, the cumulative number of failures F of unit i is recorded. i (k) , the success rate of all simulation tasks can be calculated, and whether the ship mission system is available can be determined based on the success rate of all simulation tasks.

[0064] The embodiment of the present invention provides a method for simulating a ship mission system under complex constraint conditions, which sets simulation constraint conditions, generates the initial operating state of the ship mission system, and for this simulation task, obtains the operating state of the ship mission system at any time according to the established operating state transfer equation of the ship mission system; determines whether this simulation task has reached the end condition according to the operating state of the ship mission system at any time and the running time of the ship mission system at this time; when this simulation task reaches the end condition, executes the next simulation task until the total number of simulation tasks reaches the number of simulations; and calculates the success rate of all simulation tasks. The embodiment of the present invention models and simulates the success of the ship mission system under various complex constraint conditions, accurately analyzes the main factors affecting the success of the ship mission system, and provides a basis for the availability of the ship mission system.

[0065] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for simulating a ship mission system under complex constraints, characterized in that: include: S1, setting initial simulation parameters, wherein the initial simulation parameters at least include usage constraints, maintenance constraints, support resource constraints, end conditions of each simulation task, and simulation times of the ship mission system; S2, generating the initial operation state of the ship mission system. For this simulation task, according to the established operation state transfer equation of the ship mission system, the operation state of the ship mission system at any time is obtained; S3, judging whether the simulation task has reached the end condition according to the running state of the ship task system at any time and the running time of the ship task system at this time; S4, when the simulation task reaches the end condition, the next simulation task is executed, and S2-S4 are repeated until the total number of simulation tasks reaches the simulation number; S5, calculate the success rate of all simulation tasks; The S2 includes: Constructing the ship mission system The expression equation of the state duration of each operating state; According to the ship mission system in The duration of each running state and the duration of each unit state are established to establish the ship mission system from the first The operating state is transferred to The judgment conditions of the operating state; Based on the established judgment conditions for the transfer of the operating state of the ship mission system, a state transfer matrix between each two operating states in the operating state set of the ship mission system is constructed, wherein the state transfer matrix describes whether the transfer between each two operating states in the operating state set of the ship mission system can be performed; The ship mission system is constructed in The expression equations for the state duration of each running state include: Assume that the current operating state of the ship mission system is , where there are n units in the ship mission system. The number of units in working state and fault state is h, and the corresponding h units are , The operating status of each unit of the ship's mission system; For the ship mission system operating status , the operating durations of h units in this operating state are ; Ship mission system in operation The running duration of The relationship between the usage constraint, maintenance constraint, support resource constraint, and the operating duration of the h units in this operating state can be expressed as: ； in, They represent usage constraints, maintenance constraints, and support resource constraints respectively; The establishment of the ship mission system starts from The operating state is transferred to The judgment conditions for each operating state include: The ship mission system changes from the current running state Transfer to next operating state The judgment conditions are: in, Display unit The state change occurs first under the conditions of satisfying the use constraint conditions, maintenance constraint conditions and guarantee resource constraint conditions, and the next operation state of the ship mission system operation state transfer is determined according to the use rules of the ship mission system; The state transition matrix between each two operating states in the operating state set of the ship mission system is constructed based on the established judgment condition of the operating state transfer of the ship mission system. The state transition matrix between each two operating states includes: Assume the ship mission system operation status set There are N operating states, which are respectively ; According to the work flow of the ship mission system, determine whether the ship mission system can be operated from the running state one by one. Directly transfer to the running state in one step , and use represents, where: Constructing the ship mission system operation state transfer matrix , where the elements in the running state transfer matrix A include 0 and 1; The ship mission system experiences the first Running status Ship mission system operation status collection Elements of the ship's mission system Status Can use N-dimensional unit row vector It indicates that, , the i-th element of the vector is 1 and all other elements are 0; Using the ship mission system operation state transfer matrix A, determine the ship mission system from the first The operating state is transferred to The state vector of the running state for ; Among them, if is a unit vector, indicating the first Running status is the only vector The position of the non-zero elements in corresponds to the (k+1)th operating state of the ship mission system; like is a zero vector, indicating that there is no The current running state The first operating state is the absorption state of the ship mission system, indicating mission failure; like It is neither a unit vector nor a zero vector, indicating that the first Running status There are many possibilities, The selection of an operating state depends on the operating state of the unit that changes state first among the multiple units constituting the ship mission system.

2. The simulation method according to claim 1, characterized in that: The ship mission system includes a plurality of units, and the usage constraint of the ship mission system includes a unit state maximum duration constraint and / or a unit state minimum duration constraint; When a unit state maximum duration constraint is set, the unit Status The actual duration is: ； When a minimum duration constraint is set for a cell state, the cell Status The actual duration is: ； Where i represents the unit number, For unit In Status The corresponding life span, The maximum duration of the unit state is set. The minimum duration of the unit state is set. is the kth running state.

3. The simulation method according to claim 1, characterized in that: The maintenance constraint conditions include a unit maximum allowable maintenance time constraint and a unit periodic maintenance constraint, and the guarantee resource constraint conditions include at least a spare parts guarantee capability constraint.

4. The simulation method according to any one of claims 1 to 3, characterized in that: The step of judging whether the simulation task has reached the end condition according to the running state of the ship task system at any time and the running time of the ship task system at that time includes: According to the initial running state and running state transfer equation of this simulation task, the current running state of this simulation task and the running time of the ship task system at the current moment are determined; When the current running state of the simulation task is a fault state or the running time of the ship task system reaches the set task running time, the simulation task ends and records whether the simulation task is successful.

5. The simulation method according to claim 4, characterized in that: The recording of whether the simulation task is successful includes: When the simulation task ends, if the current running state of the simulation task is a fault state, the simulation task execution fails; If the running time of this simulation task reaches the set task running time, the simulation task is executed successfully.

6. The simulation method according to claim 1, characterized in that: The S5 also includes: According to the success rate of all simulation tasks, it is judged whether the ship mission system is available.

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