Fault simulation method and device of control system, computer equipment and storage medium

Abstract

The invention relates to a fault simulation method and device of a control system, computer equipment and a storage medium. The method comprises the following steps: acquiring a target operation condition corresponding to each component fault simulation model in a control system under a preset fault working condition; for each part fault simulation model, running the part fault simulation model under a target running condition corresponding to the part fault simulation model to obtain a running result of the part fault simulation model; based on the component dynamic interaction model, according to the operation result of each component fault simulation model, determining the fault influence condition between the component fault simulation models; and determining a fault simulation result of the control system under a preset fault working condition according to the fault influence condition between the component fault simulation models and the operation result of each component fault simulation model. By adopting the method, the accuracy of fault determination of the control system can be improved, and the fault detection cost of the control system is reduced.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a fault simulation method, device, computer equipment and storage medium for a control system. Background Art

[0002] As an effective energy source for the goal of "carbon neutrality", nuclear power groups have started the intelligent transformation work, among which the intelligent control system is an important technical feature of intelligent nuclear power. Due to the potential risk of radioactive material release, nuclear power plants have special and strict requirements on system reliability that are different from other industries. Therefore, how to ensure the safety and reliability of the intelligent control system of nuclear power plants is crucial.

[0003] In traditional technology, automated or semi-automated safety analysis is usually achieved by combining a model-based development process with safety analysis technology. Although this method can complete fault determination of the control system, it has the problem of inaccurate fault determination. Summary of the invention

[0004] Based on this, it is necessary to provide a control system fault simulation method, device, computer equipment and storage medium that can accurately determine the fault condition of the control system in order to solve the above technical problems.

[0005] In a first aspect, the present application provides a fault simulation method for a control system, comprising:

[0006] Obtaining target operating conditions corresponding to the fault simulation models of each component in the control system under a preset fault condition;

[0007] For each component failure simulation model, under target operating conditions corresponding to the component failure simulation model, the component failure simulation model is run to obtain an operating result of the component failure simulation model;

[0008] Based on the dynamic interaction model of components and according to the running results of the fault simulation models of each component, the fault impact between the fault simulation models of each component is determined;

[0009] According to the fault influence between the fault simulation models of each component and the operation results of the fault simulation models of each component, the fault simulation results of the control system under the preset fault conditions are determined.

[0010] In one embodiment, the component fault simulation model includes a hardware fault simulation model and a software fault simulation model; under the target operating conditions corresponding to the component fault simulation model, the component fault simulation model is run to obtain the operating result of the component fault simulation model, including:

[0011] In the case where the component fault simulation model is a software fault simulation model, running the software fault simulation model under target running conditions corresponding to the software fault simulation model to obtain running results of the software fault simulation model;

[0012] When the component fault simulation model is a hardware fault simulation model, the triggering method of the target operating condition is determined according to the target operating condition corresponding to the hardware fault simulation model, and the hardware fault simulation model is triggered to run under the target operating condition according to the triggering method to obtain the operating result of the hardware fault simulation model.

[0013] In one embodiment, triggering the hardware fault simulation model to run under target running conditions to obtain the running result of the hardware fault simulation model includes:

[0014] When the trigger mode is a fault directional trigger mode, a directional signal corresponding to the target operating condition is obtained, and the directional signal is input into the hardware fault simulation model to obtain the operating result of the hardware fault simulation model;

[0015] When the trigger mode is a fault random trigger mode, a random signal generated by a random signal generator is obtained, and the random signal is input into a hardware fault simulation model to obtain an operation result of the hardware fault simulation model.

[0016] In one embodiment, obtaining a directional signal corresponding to a target operating condition includes:

[0017] Obtain the directional code corresponding to the target operating condition;

[0018] When the directional code is the first code, the preset standard signal is used as the directional signal corresponding to the directional code;

[0019] When the directional code is the second code, the preset fault signal is used as the directional signal corresponding to the directional code.

[0020] In one embodiment, when the control system includes at least one hardware fault simulation model and at least one software fault simulation model, determining the fault impact between the component fault simulation models based on the component dynamic interaction model and according to the operation results of the component fault simulation models includes:

[0021] Determine the system stress result of the control system according to the operation results of each hardware fault simulation model and the operation results of each software fault simulation model;

[0022] According to the preset failure rate mapping relationship of each component failure simulation model and the system stress result of the control system, the failure influence between the component failure simulation models is determined.

[0023] In one embodiment, determining the system stress result of the control system according to the operation results of each hardware fault simulation model and the operation results of each software fault model includes:

[0024] For each hardware fault simulation model, determining a hardware stress result of the hardware fault simulation model according to the running result of the hardware fault simulation model; and,

[0025] For each software fault simulation model, determining a software stress result of the software fault simulation model according to the running result of the software fault simulation model;

[0026] The sum of each hardware stress result and each software stress result is taken as the system stress result of the control system.

[0027] In a second aspect, the present application also provides a fault simulation device for a control system, comprising:

[0028] A condition acquisition module is used to obtain target operating conditions corresponding to the fault simulation models of various components in the control system under preset fault conditions;

[0029] An operation determination module is used to operate the component failure simulation model for each component failure simulation model under a target operation condition corresponding to the component failure simulation model to obtain an operation result of the component failure simulation model;

[0030] An impact determination module is used to determine the impact of failures between the fault simulation models of each component based on the dynamic interaction model of the components and according to the operation results of the fault simulation models of each component;

[0031] The result determination module is used to determine the fault simulation result of the control system under a preset fault condition according to the fault influence between the fault simulation models of each component and the operation result of the fault simulation model of each component.

[0032] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0033] Obtaining target operating conditions corresponding to the fault simulation models of each component in the control system under a preset fault condition;

[0034] For each component failure simulation model, under target operating conditions corresponding to the component failure simulation model, the component failure simulation model is run to obtain an operating result of the component failure simulation model;

[0035] Based on the dynamic interaction model of components and according to the running results of the fault simulation models of each component, the fault impact between the fault simulation models of each component is determined;

[0036] According to the fault influence between the fault simulation models of each component and the operation results of the fault simulation models of each component, the fault simulation results of the control system under the preset fault conditions are determined.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0038] Obtaining target operating conditions corresponding to the fault simulation models of each component in the control system under a preset fault condition;

[0039] For each component failure simulation model, under target operating conditions corresponding to the component failure simulation model, the component failure simulation model is run to obtain an operating result of the component failure simulation model;

[0040] Based on the dynamic interaction model of components and according to the running results of the fault simulation models of each component, the fault impact between the fault simulation models of each component is determined;

[0041] According to the fault influence between the fault simulation models of each component and the operation results of the fault simulation models of each component, the fault simulation results of the control system under the preset fault conditions are determined.

[0042] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0043] Obtaining target operating conditions corresponding to the fault simulation models of each component in the control system under a preset fault condition;

[0044] For each component failure simulation model, under target operating conditions corresponding to the component failure simulation model, the component failure simulation model is run to obtain an operating result of the component failure simulation model;

[0045] Based on the dynamic interaction model of components and according to the running results of the fault simulation models of each component, the fault impact between the fault simulation models of each component is determined;

[0046] According to the fault influence between the fault simulation models of each component and the operation results of the fault simulation models of each component, the fault simulation results of the control system under the preset fault conditions are determined.

[0047] The fault simulation method, device, computer equipment and storage medium of the control system described above obtain the target operating conditions corresponding to the fault simulation models of each component in the control system under the preset fault conditions; for each component fault simulation model, under the target operating conditions corresponding to the component fault simulation model, run the component fault simulation model to obtain the operating results of the component fault simulation model; based on the component dynamic interaction model, determine the fault impact between the fault simulation models of each component according to the operating results of the fault simulation models of each component; determine the fault simulation results of the control system under the preset fault conditions according to the fault impact between the fault simulation models of each component and the operating results of the fault simulation models of each component. This embodiment sets the fault simulation model to determine the fault simulation results of the control system under the target operating conditions, so that the control system can directly determine the corresponding fault condition when a fault actually occurs, improve the accuracy of fault determination of the control system, and reduce the cost of fault detection of the control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] FIG1 is an application environment diagram of a control system fault simulation method provided by this embodiment;

[0050] FIG2 is a schematic flow chart of a first control system fault simulation method provided by this embodiment;

[0051] FIG3 is a schematic diagram of a software fault simulation model provided by this embodiment;

[0052] FIG4 is a schematic diagram of a hardware fault simulation model provided by this embodiment;

[0053] FIG5 is a schematic diagram of the impact of component failure provided by this embodiment;

[0054] FIG6 is a schematic diagram of a component stress function provided by this embodiment;

[0055] FIG7 is a schematic diagram of a water control system fault simulation provided by this embodiment;

[0056] FIG8 is a schematic diagram of a water level sensor output provided by this embodiment;

[0057] FIG9 is a schematic diagram of a system performance response provided by this embodiment;

[0058] FIG10 is a block diagram of a fault simulation device for a control system provided in an embodiment;

[0059] FIG. 11 is a diagram showing the internal structure of a computer device provided in an embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] The fault simulation method of the control system provided in the embodiment of the present application can be applied to the application environment shown in FIG1. ​​Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The computer device obtains the target operating conditions corresponding to the fault simulation models of each component in the control system under the preset fault condition; for each component fault simulation model, the component fault simulation model is run under the target operating conditions corresponding to the component fault simulation model to obtain the running result of the component fault simulation model; based on the component dynamic interaction model, according to the running results of the fault simulation models of each component, the fault influence between the fault simulation models of each component is determined; according to the fault influence between the fault simulation models of each component and the running results of the fault simulation models of each component, the fault simulation result of the control system under the preset fault condition is determined. Among them, the computer device can be both a terminal and a server. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable device may be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0062] In an exemplary embodiment, as shown in FIG2 , a control system fault simulation method is provided, which is described by taking the method applied to the computer device in FIG1 as an example, and includes the following steps 201 to 204. Among them:

[0063] Step 201 , obtaining target operating conditions corresponding to the fault simulation models of various components in the control system under a preset fault condition.

[0064] The fault condition may be the condition of the control system when the fault occurs. The component fault simulation model may be a simulation model composed of components in the control system, and the fault simulation model may include a hardware fault simulation model and a software fault simulation model. The target operating condition may be the operating condition of the component fault simulation model, and the target operating condition may be a standard operating condition or a fault operating condition.

[0065] Specifically, the operating conditions of each component in the control system under a fault condition are obtained, and the operating conditions are used as target operating conditions corresponding to the fault simulation model of the corresponding component.

[0066] Step 202 : for each component failure simulation model, run the component failure simulation model under the target operating conditions corresponding to the component failure simulation model to obtain the operating result of the component failure simulation model.

[0067] Specifically, for each component failure simulation model, the target operating condition is input into the component failure simulation model, so that the component failure simulation model is operated under the target operating condition, thereby obtaining the operating result of the component failure simulation model.

[0068] In one of the embodiments, when the component fault simulation model is a software fault simulation model, the software fault simulation model is run under target operating conditions corresponding to the software fault simulation model to obtain an operating result of the software fault simulation model.

[0069] Exemplarily, the failure of software (components) in the control system belongs to systematic failure. Software faults are introduced by software design errors and must be triggered under specific input conditions, which are potential faults. Software faults lurk in software components from the beginning and will always exist in the system software until the root cause of the software error is eliminated. Therefore, the software fault simulation model is established based on the input domain and output domain of the software. When the input value of the digital component falls into a specific input range, the software fault is triggered and an erroneous output is given. Since embedded software and hardware are similar, there are many different types of failure modes, such as data calculation loss precision, sign error, boundary data processing error, etc. As shown in the schematic diagram of the software fault simulation model in Figure 3, the software fault simulation model is implemented by a fault trigger function, and the state variables in the fault trigger function can reflect the state changes of the software component. Under default conditions, the state of the state variable in the fault trigger function is a normal state, which means that the software component is in a normal working state. If the component input signal meets a specific input condition, the fault of the software specific mode is triggered. Subsequently, the software fault output is simulated by increasing or decreasing a value based on the existing signal output.

[0070] In another embodiment, when the component fault simulation model is a hardware fault simulation model, the triggering method of the target operating condition is determined according to the target operating condition corresponding to the hardware fault simulation model, and according to the triggering method, the hardware fault simulation model is triggered to run under the target operating condition to obtain the operating result of the hardware fault simulation model.

[0071] The triggering mode may include a fault-oriented triggering mode and a fault-random triggering mode.

[0072] Specifically, the target operating condition corresponding to the hardware fault simulation model is analyzed to determine whether the target operating condition is a directional fault; if the target operating condition is a directional fault, the triggering mode of the target operating condition is determined to be a fault directional triggering mode; if the target operating condition is a random fault, the triggering mode of the target operating condition is determined to be a fault random triggering mode; according to the triggering mode, the hardware fault simulation model is triggered to run under the target operating condition to obtain the running result of the hardware fault simulation model.

[0073] Exemplarily, if the target operating condition is a high component output value fault, the triggering mode of the target operating condition is determined to be a fault-oriented triggering mode; if the actual fault condition of the target operating condition is not limited, the triggering mode of the target operating condition is determined to be a fault-random triggering mode.

[0074] Step 203 : Based on the component dynamic interaction model and according to the operation results of the component fault simulation models, determine the fault impact between the component fault simulation models.

[0075] Specifically, the operation results of the fault simulation models of each component are input into the component dynamic interaction model to obtain the fault impact between the fault simulation models of each component.

[0076] Step 204 , determining a fault simulation result of the control system under a preset fault condition according to the fault influence between the fault simulation models of the components and the operation result of the fault simulation models of the components.

[0077] Specifically, the fault impact conditions between the fault simulation models of each component and the operation results of the fault simulation models of each component are combined, and the combined result is used as the fault simulation result of the control system under the preset fault condition.

[0078] The fault simulation method, device, computer equipment and storage medium of the control system described above obtain the target operating conditions corresponding to the fault simulation models of each component in the control system under the preset fault conditions; for each component fault simulation model, under the target operating conditions corresponding to the component fault simulation model, the component fault simulation model is run to obtain the operating results of the component fault simulation model; based on the component dynamic interaction model, the fault influence between the fault simulation models of each component is determined according to the operating results of the fault simulation models of each component; according to the fault influence between the fault simulation models of each component and the operating results of the fault simulation models of each component, the fault simulation results of the control system under the preset fault conditions are determined. This embodiment sets the fault simulation model to determine the fault simulation results of the control system under the target operating conditions, and can accurately simulate the logic of system control and the evolution of system states under different faults and fault combinations, as well as the dynamic interactions between the components of the system, so that the control system can directly determine the corresponding fault conditions when a fault actually occurs, improve the accuracy of fault determination of the control system, and reduce the cost of fault detection of the control system.

[0079] In one embodiment, according to the triggering mode, the hardware fault simulation model is triggered to run under the target operating conditions to obtain the operating results of the hardware fault simulation model, including: when the triggering mode is a fault directional triggering mode, a directional signal corresponding to the target operating condition is obtained, and the directional signal is input into the hardware fault simulation model to obtain the operating results of the hardware fault simulation model; when the triggering mode is a fault random triggering mode, a random signal generated by a random signal generator is obtained, and the random signal is input into the hardware fault simulation model to obtain the operating results of the hardware fault simulation model.

[0080] In one embodiment, obtaining a directional signal corresponding to a target operating condition includes: obtaining a directional code corresponding to the target operating condition; when the directional code is a first code, using a preset standard signal as the directional signal corresponding to the directional code; when the directional code is a second code, using a preset fault signal as the directional signal corresponding to the directional code.

[0081] Exemplarily, the hardware (components) in the control system are mainly electronic products, and hardware failures are random failures, and the failure of its components has a certain degree of randomness and contingency. Therefore, the process of establishing the hardware fault simulation model is mainly based on randomness, and is implemented through a random number generation function. The random number distribution function is determined by referring to the probability of occurrence of component failure modes in actual engineering experience. As shown in the schematic diagram of the hardware fault simulation model in Figure 4, the hardware fault simulation model includes a component state mode switching model, a manual fault injection model, and a random number sampling model. The component state mode can be represented by manual fault selection or a random sampling function, and the sampling time step is consistent with the simulation sampling time step. The state of system components is represented by digital codes, such as the number "1" represents the normal state of the component, the number "2" represents the high fault mode of the component output value, and the number "3" represents the low fault mode of the component output value. The degree of impact of component failure is measured using a random signal generator. Description, the generated random signal obeys the normal distribution. Where μ represents the mean value, σ represents the mean variance, and u j Represents the number of samples input to the hardware fault simulation model. The control component failure influence degree represents the maximum increment and decrement percentage caused by component failure relative to its normal output, as shown in the schematic diagram of component failure influence in FIG5. The maximum increment and decrement correspond to the positive value on the right and the negative value on the left of the normal distribution function, respectively. The maximum fault output relative percentage is 1. The numerical part of the normal distribution number with an absolute value exceeding 1 is truncated by the limit function, and the maximum ±1 value is retained. In the implementation process, the matching and unification of the component failure influence degree and the component operation / failure mode are achieved through the positive and negative jump form of the absolute value. If the component failure corresponds to the positive output, all negative sampling values ​​automatically take their positive absolute values ​​as additional failure outputs. The random number sampling model is interrelated with the component state mode control model. The component state mode digital code generated by the random number sampling model is used as the input of the multi-port switch controller for switching and selecting mutually exclusive component state modes and fault mode injection. The component failure influence degree is superimposed on the normal signal output value to simulate the impact of the component failure mode on the dynamic behavior of the system.

[0082] In this embodiment, when the trigger mode is a fault directional trigger mode, a directional signal corresponding to the target operating condition is obtained, and the directional signal is input into the hardware fault simulation model to obtain the operating result of the hardware fault simulation model; when the trigger mode is a fault random trigger mode, a random signal generated by a random signal generator is obtained, and the random signal is input into the hardware fault simulation model to obtain the operating result of the hardware fault simulation model. This embodiment can more accurately determine the operating result of the hardware fault simulation model.

[0083] In one embodiment, when the control system includes at least one hardware fault simulation model and at least one software fault simulation model, based on the component dynamic interaction model, the fault impact between the component fault simulation models is determined according to the running results of the component fault simulation models, including: determining the system stress result of the control system according to the running results of each hardware fault simulation model and the running results of each software fault simulation model; determining the fault impact between the component fault simulation models according to the preset failure rate mapping relationship of each component fault simulation model and the system stress result of the control system.

[0084] Specifically, the running results of each hardware fault simulation model and the running results of each software fault simulation model are input into the component dynamic interaction model; the component dynamic interaction model analyzes the running results of each hardware fault simulation model and the running results of each software fault simulation model to obtain the system stress results of the control system, and then determines the fault impact between the component fault simulation models according to the preset failure rate mapping relationship of each component fault simulation model and the system stress results of the control system.

[0085] In one embodiment, a system stress result of a control system is determined based on the running results of each hardware fault simulation model and the running results of each software fault model, including: for each hardware fault simulation model, determining the hardware stress result of the hardware fault simulation model based on the running results of the hardware fault simulation model; and, for each software fault simulation model, determining the software stress result of the software fault simulation model based on the running results of the software fault simulation model; and taking the sum of each hardware stress result and each software stress result as the system stress result of the control system.

[0086] Exemplarily, hardware failures are usually stimulated by certain stress types and stress levels over time, and the occurrence of hardware failure simulation models often leads to changes in generalized stress (such as mechanical stress, electrical stress, thermal stress, liquid force, etc.), causing other related components to bear greater stress, which in turn leads to an increase in failure rate. Therefore, this embodiment mainly determines the system stress results by establishing a mapping relationship between the failure mode of each component and the failure rate of the remaining components. As shown in the schematic diagram of the component stress function in Figure 6, the determination of the system stress results is mainly divided into two types: dynamic interaction stress between hardware, and dynamic interaction stress between software and hardware. First, a relationship model between the failure rate λ(Θ,t) of the hardware failure simulation model and the generalized stress is established, as shown in the following formula: λ(Θ,t)=Λ(Θ)λ 0 (t). Where Θ represents the stress set related to the component failure rate, Λ(Θ) is the stress coefficient that causes the component failure rate to change, which is a function of generalized stress and can be obtained through actual engineering experience or experimental analysis, and λ 0(t) is the failure rate of the component under normal working conditions. This step is implemented by the fcn function module in SIMULINK. Since software failures are potential failures as mentioned above, they are not affected by environmental stress. Then a generalized stress model of the fault simulation model of each component in the control system is established. The general form of the model is shown in the following formula (1-1):

[0087] (1-1)

[0088] Where A(t) and B(t) are model physical parameters, and specific parameter values ​​can be obtained through actual engineering experience or experimental analysis, u(t) is the control signal, and ω(t) is the environmental disturbance. This step is also implemented through the fcn function module in SIMULINK. It should be noted that this embodiment assumes that after a hardware failure, the component cannot spontaneously recover from the fault state to the normal state, so the generalized stress change caused by the hardware failure is a long-term continuous change, and because the software failure is only triggered when a specific input is not time-related, the generalized stress change caused by the software failure is short-term and may have continuous fluctuations.

[0089] In this embodiment, the system stress results of the control system are determined according to the operating results of each hardware fault simulation model and the operating results of each software fault simulation model; based on the preset failure rate mapping relationship of each hardware fault simulation model, the component failure rate corresponding to the corresponding hardware fault simulation model under the system stress result of the control system is determined, which can more accurately determine the system stress results.

[0090] Exemplarily, an example is used to illustrate the implementation of the technical solution of the present application. The main components of the traditional water supply control system include a PI controller, a dynamic compensator, a water level sensor, a water supply flow sensor, a steam flow sensor, and a turbine-driven water supply pump. The control system adopts a three-flux control mode, that is, three measurement signals of water level, water supply flow and steam flow are used for system control. Since the water level of the steam generator is mainly regulated by the water level in practical applications, the action and failure mode of the water supply flow sensor and the steam flow sensor are not considered in this embodiment. In order to meet the needs of intelligent control, this embodiment replaces the PI controller with an intelligent control module based on the BP neural network PID control method. Based on this control logic, a fault simulation diagram of the water supply control system shown in Figure 7 is established. Based on FMEA analysis, the operating status of the system components can be obtained, as shown in the following table. Among them, the dynamic compensator, the water level sensor and the turbine-driven water supply pump are general hardware, and the hardware failure mode is mainly considered. The function of the intelligent control module is mainly implemented based on the intelligent control algorithm, so it is abstracted as a software module, and the software failure mode is mainly considered.

[0091] This embodiment illustrates the fault injection test process through a hypothetical system operating condition. Assume that the system is in the ramp power operation mode, and the power load increases from 70% to 78% full power. The system water level is controlled within ±2 feet of the set value, and the system water level set value in this embodiment is specified as 0. When the system water level exceeds the set water level by +13 feet, a high water level turbine trip failure occurs in the system; when the system water level is lower than the set value by -26 feet, a low water level reactor scram failure occurs in the system. As shown in the output schematic diagram of the water level sensor in Figure 8, the value in (A) in the figure is the output value of the system in the normal state. First, specific component faults or combined faults can be identified through manual fault injection. For example, when injecting the "high output of water level sensor failure" fault, that is, turning the status switch of the water level sensor to a specific fault state mode, and the remaining component modules are modulated to the fault-free input state. As shown in the output schematic diagram of the water level sensor in Figure 8, the value in (B) in the figure is the output value of the system in the fault state. Under the condition that the failure impact degree is 22.25%, the system water level cannot converge to the specified water level. Therefore, it can be judged that the possible impact of "high output of water level sensor failure" is "causing system water level control fluctuations".

[0092] Table 1 System Component Status Modes

[0093]

[0094] At the same time, the impact of different component fault mode combinations on system failure can also be explored through automatic random injection. All hardware component modules of the system are set to the random fault mode. When the input signal of the intelligent control module satisfies -3.3 < u(k) < -3, a software loss of precision fault is triggered. When u(k) = 4.5, a software sign error fault is triggered. As shown in the system performance response schematic diagram in Figure 9, the system performance response when "dynamic compensator jams" occurs at 27s and "feed water pump jams" occurs at 165.6s. The system water level deviates significantly from the set water level. Therefore, it can be judged that the final impact of the combined faults of "dynamic compensator jams", "feed water pump jams" and "intelligent control module software fault" is "causing system water level control deviation". Through the injection analysis of complete single and combined faults of the system, the complete system failure modes and fault impacts can be obtained to assist in the reliable design of the system.

[0095] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0096] Based on the same inventive concept, the embodiment of the present application also provides a control system fault simulation device for implementing the control system fault simulation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more control system fault simulation devices provided below can refer to the limitations of the control system fault simulation method above, and will not be repeated here.

[0097] In an exemplary embodiment, as shown in FIG10 , a fault simulation device for a control system is provided, comprising: a condition acquisition module 10, an operation determination module 11, a fault determination module 12 and a result determination module 13, wherein:

[0098] The condition acquisition module 10 is used to acquire the target operating conditions corresponding to the fault simulation models of each component in the control system under the preset fault conditions;

[0099] An operation determination module 11 is used to operate the component failure simulation model for each component failure simulation model under a target operation condition corresponding to the component failure simulation model to obtain an operation result of the component failure simulation model;

[0100] The impact determination module 12 is used to determine the impact of the faults between the fault simulation models of each component based on the dynamic interaction model of the component and according to the operation results of the fault simulation models of each component;

[0101] The result determination module 13 is used to determine the fault simulation result of the control system under a preset fault condition according to the fault influence between the fault simulation models of each component and the operation result of the fault simulation model of each component.

[0102] In one embodiment, the operation determination module 11 in FIG. 10 further includes:

[0103] The software simulation unit is used to run the software fault simulation model under the target running conditions corresponding to the software fault simulation model to obtain the running result of the software fault simulation model when the component fault simulation model is a software fault simulation model;

[0104] The hardware simulation unit is used to determine the triggering method of the target operating condition according to the target operating condition corresponding to the hardware fault simulation model when the component fault simulation model is a hardware fault simulation model, and trigger the hardware fault simulation model to run under the target operating condition according to the triggering method to obtain the operating result of the hardware fault simulation model.

[0105] In one embodiment, the hardware simulation unit is also used to obtain a directional signal corresponding to a target operating condition when the trigger mode is a fault-directional trigger mode, and input the directional signal into a hardware fault simulation model to obtain an operating result of the hardware fault simulation model; when the trigger mode is a fault-random trigger mode, obtain a random signal generated by a random signal generator, and input the random signal into the hardware fault simulation model to obtain an operating result of the hardware fault simulation model.

[0106] In one embodiment, the hardware simulation unit is also used to obtain the directional code corresponding to the target operating condition; when the directional code is the first code, the preset standard signal is used as the directional signal corresponding to the directional code; when the directional code is the second code, the preset fault signal is used as the directional signal corresponding to the directional code.

[0107] In one embodiment, the fault determination module 12 is also used to determine the system stress results of the control system based on the operating results of each hardware fault simulation model and the operating results of each software fault simulation model; and to determine the fault impact between each component fault simulation model based on the preset failure rate mapping relationship of each component fault simulation model and the system stress results of the control system.

[0108] In one embodiment, the fault determination module 12 is also used to determine, for each hardware fault simulation model, the hardware stress result of the hardware fault simulation model according to the running result of the hardware fault simulation model; and, for each software fault simulation model, determine the software stress result of the software fault simulation model according to the running result of the software fault simulation model; and use the sum of each hardware stress result and each software stress result as the system stress result of the control system.

[0109] Each module in the fault simulation device of the control system can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0110] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG11. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a fault simulation method of a control system is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0111] Those skilled in the art will understand that the structure shown in FIG. 11 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0112] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0113] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0114] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0115] It should be noted that the data involved in this application (including but not limited to data used for analysis, stored data, displayed data, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0116] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0117] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0118] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A control system fault simulation method, characterized in that: The method comprises: Obtaining target operating conditions corresponding to the fault simulation models of each component in the control system under a preset fault condition; For each component failure simulation model, running the component failure simulation model under the target operating conditions corresponding to the component failure simulation model to obtain an operating result of the component failure simulation model; Based on the dynamic interaction model of components and according to the running results of the fault simulation models of each component, the fault impact between the fault simulation models of each component is determined; According to the fault influence between the fault simulation models of each component and the operation result of the fault simulation model of each component, the fault simulation result of the control system under the preset fault condition is determined.

2. The method according to claim 1, characterized in that: The component fault simulation model includes a hardware fault simulation model and a software fault simulation model; and under the target operating conditions corresponding to the component fault simulation model, the component fault simulation model is operated to obtain the operating result of the component fault simulation model, including: In the case where the component fault simulation model is a software fault simulation model, running the software fault simulation model under target running conditions corresponding to the software fault simulation model to obtain a running result of the software fault simulation model; In the case where the component fault simulation model is a hardware fault simulation model, a triggering method of the target operating condition is determined according to the target operating condition corresponding to the hardware fault simulation model, and according to the triggering method, the hardware fault simulation model is triggered to run under the target operating condition to obtain the operating result of the hardware fault simulation model.

3. The method according to claim 2, characterized in that The triggering method triggers the hardware fault simulation model to run under the target running condition, and obtains the running result of the hardware fault simulation model, including: In the case where the trigger mode is a fault directional trigger mode, obtaining a directional signal corresponding to the target operating condition, and inputting the directional signal into the hardware fault simulation model to obtain an operating result of the hardware fault simulation model; In the case where the triggering mode is a fault random triggering mode, a random signal generated by a random signal generator is obtained, and the random signal is input into the hardware fault simulation model to obtain an operation result of the hardware fault simulation model.

4. The method according to claim 3, characterized in that The obtaining of the directional signal corresponding to the target operating condition includes: Obtaining a directional code corresponding to the target operating condition; When the directional code is the first code, using a preset standard signal as a directional signal corresponding to the directional code; In the case where the directional code is the second code, the preset fault signal is used as the directional signal corresponding to the directional code.

5. The method according to claim 1, characterized in that In the case where the control system includes at least one hardware fault simulation model and at least one software fault simulation model, the method of determining the fault impact between the component fault simulation models based on the component dynamic interaction model according to the operation results of the component fault simulation models includes: Determine the system stress result of the control system according to the operation results of each hardware fault simulation model and the operation results of each software fault simulation model; According to the preset failure rate mapping relationship of each component failure simulation model and the system stress result of the control system, the failure influence between the component failure simulation models is determined.

6. The method according to claim 5, characterized in that Determining the system stress result of the control system according to the operation results of each hardware fault simulation model and the operation results of each software fault model includes: For each hardware fault simulation model, determining a hardware stress result of the hardware fault simulation model according to the running result of the hardware fault simulation model; and, For each software fault simulation model, determining a software stress result of the software fault simulation model according to an operation result of the software fault simulation model; The sum of each hardware stress result and each software stress result is taken as the system stress result of the control system.

7. A fault simulation device for a control system, characterized in that: The device comprises: A condition acquisition module is used to obtain target operating conditions corresponding to the fault simulation models of various components in the control system under preset fault conditions; An operation determination module is used to operate each component fault simulation model under a target operation condition corresponding to the component fault simulation model to obtain an operation result of the component fault simulation model; An impact determination module is used to determine the impact of failures between the fault simulation models of each component based on the dynamic interaction model of the components and according to the operation results of the fault simulation models of each component; The result determination module is used to determine the fault simulation result of the control system under the preset fault condition according to the fault influence between the fault simulation models of each component and the operation result of the fault simulation model of each component.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images