CN116108622A - Rail transit signal system reliability analysis method and device and electronic equipment - Google Patents
Rail transit signal system reliability analysis method and device and electronic equipment Download PDFInfo
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Abstract
The invention provides a method and a device for analyzing reliability of a rail transit signal system and electronic equipment, wherein the method comprises the following steps: determining a task function relation model based on a task scene model and a system function model of the target signal system; determining a fault tree through failure analysis based on the task function relation model and the function fault modes of each system; and determining a first fault probability control index of each system function fault mode based on the fault tree and the task reliability quantitative index of each task section. By determining the fault tree, task failure probability control indexes of each task section can be distributed to each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section, a first fault probability control index of each system function fault mode can be determined, the first fault probability control index can represent the reliability requirement of the system function, and the task reliability requirement of the complex track traffic signal system is decomposed to each system function.
Description
Technical Field
The present invention relates to the field of rail transit technologies, and in particular, to a method and an apparatus for analyzing reliability of a rail transit signal system, and an electronic device.
Background
"reliability" is one of the important characteristics of engineering systems, which directly relates to the ability of the equipment to perform functions and to the full life costs and expenses for urban rail transit signal control equipment. With the development of new generation equipment to high informatization, networking and intellectualization, the functions, architecture and behaviors of the equipment and key component systems thereof are more and more complex, the characteristics of complex systems such as scale, nonlinearity, emerging, uncertainty and the like are more and more obvious, and the traditional reliability design analysis method cannot meet the needs of the research and development of complex engineering systems. How to decompose the task reliability requirement of a complex track traffic signal system into various system functions is a problem to be solved urgently in the target industry.
Disclosure of Invention
Aiming at the problems existing in the prior art, the embodiment of the invention provides a method and a device for analyzing the reliability of a rail transit signal system and electronic equipment.
In a first aspect, the present invention provides a method for analyzing reliability of a rail traffic signal system, including:
Determining a task function relation model based on a task scene model and a system function model of a target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure;
determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
Optionally, according to the method for analyzing reliability of a rail traffic signal system provided by the present invention, the determining, based on the fault tree and task reliability quantitative indicators of each task profile, a first fault probability control indicator of each system functional fault mode includes:
Determining task failure probability control indexes of each task section based on task reliability quantitative indexes of each task section;
based on the fault tree and task failure probability control indexes of each task section, respectively executing failure probability control index analysis operation on each task section, and determining an analysis result of each task section, wherein the analysis result comprises one or more second failure probability control indexes corresponding to each target system function fault mode, and the target system function fault mode is a system function fault mode which is determined based on the fault tree and is associated with the task section;
based on the analysis result of each task section, classifying and collecting a plurality of second fault probability control indexes according to the system function fault modes, and determining a fault probability control index set of each system function fault mode;
and determining a first fault probability control index of each system function fault mode based on a fault probability control index set of each system function fault mode, wherein the first fault probability control index is one of the fault probability control index sets with the minimum probability value.
Optionally, according to the method for analyzing reliability of a rail transit signal system provided by the present invention, the performing failure probability control index analysis operation includes:
Acquiring at least one minimum cut set of the task section based on the fault tree, wherein the minimum cut set comprises one or more target system function fault modes;
determining a failure probability control index of each minimum cut set based on the task failure probability control index and a first number, the first number being the total number of the at least one minimum cut set;
determining a second fault probability control index of each target system function fault mode in different minimum cut sets based on the fault probability control index of each minimum cut set and a second number corresponding to each minimum cut set, wherein the second number is the total number of the target system function fault modes in the minimum cut sets;
and determining an analysis result of the task profile based on second fault probability control indexes of the functional fault modes of the target systems in different minimum cut sets.
Optionally, according to the method for analyzing reliability of a rail traffic signal system provided by the present invention, after determining the first failure probability control index of each system functional failure mode based on the failure tree and the task reliability quantitative index of each task section, the method further includes:
determining a fault mode of each system unit based on a system architecture model of the target signal system, wherein the fault mode of each system unit is used for representing fault logic of the system unit;
Based on the fault modes of each system unit, determining a system fault propagation model by analyzing the logic relation of system function failure caused by the system unit fault;
determining a third fault probability control index of each system unit fault mode based on the system fault propagation model and the first fault probability control index of each system functional fault mode;
the system architecture model is determined by modeling the target signal system in a model-based system engineering MBSE modeling manner, and comprises a plurality of system units.
Optionally, according to the method for analyzing reliability of a rail transit signal system provided by the invention, the system unit fault mode includes a state space variable, a unit port variable, trigger event information, a state transition function, a transfer function and a port connection relation function.
Optionally, according to the method for analyzing reliability of a rail traffic signal system provided by the present invention, after the third fault probability control index of each system unit fault mode is determined based on the system fault propagation model and the first fault probability control index of each system functional fault mode, the method further includes;
And determining a fourth failure probability control index of each hardware element failure mode by analyzing the logic relation of the failure of the system unit caused by the hardware element failure mode based on the third failure probability control index of each system element failure mode and each hardware element failure mode.
In a second aspect, the present invention further provides a reliability analysis device for a rail traffic signal system, including:
the first determining module is used for determining a task function relation model based on a task scene model and a system function model of the target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
the second determining module is used for determining a fault tree through failure analysis based on the task function relation model and the function fault modes of the systems, wherein the fault tree is used for representing the logic relation of the task failure caused by the function fault modes of the systems;
the third determining module is used for determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
In a third aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements any one of the above-mentioned rail traffic signal system reliability analysis methods when executing the program.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of reliability analysis of a rail transit signal system as described in any one of the above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program which when executed by a processor implements a method of analyzing the reliability of a rail transit signal system as described in any one of the above.
According to the reliability analysis method, the reliability analysis device and the electronic equipment for the rail transit signal system, the complex target signal system can be modeled through the MBSE, the task scene model and the system function model of the target signal system can be obtained, the task function relation model can be determined based on the task scene model and the system function model, further the logical relation of task failure caused by the system function failure mode can be analyzed based on the task function relation model, so that a fault tree can be determined, further task reliability quantitative indexes of all task sections can be based on the fault tree and all task section, task failure probability control indexes of all task sections are distributed to all system function failure modes, first fault probability control indexes of all system function failure modes can be determined, the first fault probability control indexes can represent reliability requirements of system functions, and task reliability requirements of the complex rail transit signal system are decomposed to all system functions.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for analyzing reliability of a rail transit signal system according to the present invention;
FIG. 2 is a second flow chart of the reliability analysis method of the track traffic signal system according to the present invention;
FIG. 3 is a third flow chart of the reliability analysis method of the track traffic signal system according to the present invention;
FIG. 4 is a system task schematic diagram of an interlock system provided by the present invention;
FIG. 5 is a task decomposition schematic of an interlock system provided by the present invention;
FIG. 6 is a system functional exploded view of an interlock system provided by the present invention;
FIG. 7 is a schematic diagram of a system fault tree of the interlock system provided by the present invention that results in failure of a system task;
FIG. 8 is a schematic diagram of a system fault propagation model of an interlock system provided by the present invention;
Fig. 9 is a schematic structural diagram of a reliability analysis device of a rail transit signal system provided by the invention;
fig. 10 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
In order to facilitate a clearer understanding of various embodiments of the present invention, some relevant background knowledge is first presented as follows.
In the related art, the reliability requirement decomposition method uses Mean Time Between Failures (MTBF) as a main line, which simply understands the reliability of the system as the sum of the reliability of the constituent units, ignores the complex characteristics of the complex system, such as the coupling property, the emergence property and the like, is insufficient for representing the reliability requirement of the complex system, and cannot be implemented in the design process of the complex system and components.
Model-based system engineering (MBSE) is one of the complex system design methods. Compared with the traditional system engineering, the MBSE highly emphasizes the application of the 'normalized' model in the whole equipment development process, solves the problem that the traditional system engineering cannot implement the landing on one hand, overcomes the defects of the existing digital development technology in the aspects of demand analysis and architecture design on the other hand, and is widely applied to the fields of aerospace, rail transit and the like.
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a schematic flow chart of a method for analyzing reliability of a track traffic signal system according to the present invention, where, as shown in fig. 1, the method for analyzing reliability of a track traffic signal system includes:
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
Specifically, to achieve decomposition of task reliability requirements of a complex rail transit signal system into system functions, a complex target signal system may be modeled by an MBSE, a task scene model and a system function model of the target signal system may be obtained, the task scene model may include a plurality of task profiles, the task scene model may characterize a relationship between the task profiles, the system function model may include a plurality of system functions, the system function model may characterize a relationship between the system functions, and a mapping relationship between the task profiles and the system functions (e.g., analyzing which system functions the task profiles depend on) may be analyzed based on the task scene model and the system function model to determine a task function relationship model.
And 102, determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure.
Specifically, after determining the task functional relationship model, the logical relationship of the system functional failure mode resulting in task failure may be analyzed based on the task functional relationship model to determine a failure tree.
It will be appreciated that the system failure mode is a manifestation of system failure. For example, the system function may be an external network communication function, and the external network communication function failure mode may be a network card failure or a communication timeout, etc.; for example, the system function may be a system initialization function, and the system initialization function failure mode may be a serial port failure or a CAN bus failure, or the like.
It can be appreciated that after determining the task functional relationship model, the system functional failure mode can be taken as a bottom event, the task section failure can be taken as a top event, and the logical relationship between the task section failure and the system functional failure mode can be analyzed based on the task functional relationship model, so that a failure tree can be determined.
Specifically, after determining the fault tree, the task failure probability control index of each task section may be assigned to each system function fault mode based on the fault tree and the task reliability quantitative index of each task section, so that a first fault probability control index of each system function fault mode may be determined, and the first fault probability control index may represent a reliability requirement of a system function.
Alternatively, the task unreliability quantitative indicator (i.e., the task failure probability control indicator) of each task section may be determined based on the task reliability quantitative indicator of each task section.
According to the reliability analysis method for the track traffic signal system, the complex target signal system can be modeled through the MBSE, the task scene model and the system function model of the target signal system can be obtained, the task function relation model can be determined based on the task scene model and the system function model, further the logical relation of task failure caused by the system function fault model can be analyzed based on the task function relation model to determine a fault tree, further task failure probability control indexes of each task section can be distributed to each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section, the first fault probability control indexes of each system function fault mode can be determined, the first fault probability control indexes can represent the reliability requirements of system functions, and the task reliability requirements of the complex track traffic signal system are decomposed to each system function.
Optionally, according to the method for analyzing reliability of a rail traffic signal system provided by the present invention, the determining, based on the fault tree and task reliability quantitative indicators of each task profile, a first fault probability control indicator of each system functional fault mode includes:
Determining task failure probability control indexes of each task section based on task reliability quantitative indexes of each task section;
based on the fault tree and task failure probability control indexes of each task section, respectively executing failure probability control index analysis operation on each task section, and determining an analysis result of each task section, wherein the analysis result comprises one or more second failure probability control indexes corresponding to each target system function fault mode, and the target system function fault mode is a system function fault mode which is determined based on the fault tree and is associated with the task section;
based on the analysis result of each task section, classifying and collecting a plurality of second fault probability control indexes according to the system function fault modes, and determining a fault probability control index set of each system function fault mode;
and determining a first fault probability control index of each system function fault mode based on a fault probability control index set of each system function fault mode, wherein the first fault probability control index is one of the fault probability control index sets with the minimum probability value.
Specifically, after determining the fault tree, the task unreliability quantitative indicator (i.e., the task failure probability control indicator) of each task section may be determined based on the task reliability quantitative indicator of each task section, and then the failure probability control indicator analysis operation may be performed for each task section to determine the analysis result of each task section.
It will be appreciated that performing failure probability control indicator analysis operations for a certain task profile may include: based on the fault tree, determining a system function fault mode (namely a target system function fault mode) associated with the task profile, further, distributing task failure probability control indexes of the task profile to each target system function fault mode based on the fault tree, and after distributing, enabling one target system function fault mode to correspond to one or more second fault probability control indexes, further, determining an analysis result of the task profile.
Specifically, after the analysis result of each task section is determined, the system function fault mode may classify and collect the plurality of second fault probability control indexes, and determine the fault probability control index set of each system function fault mode.
It may be understood that, for a certain system functional failure mode a, the analysis result of the task section B may include one second failure probability control index (named as index 1) corresponding to the system functional failure mode a, and the analysis result of the task section C may include two second failure probability control indexes (named as index 2 and index 3) corresponding to the system functional failure mode a, so that the failure probability control index set of the system functional failure mode a includes index 1, index 2 and index 3.
Specifically, in determining the fault probability control index set of each system function fault mode, each index in the fault probability control index set may be compared to determine a first fault probability control index of each system function fault mode, where the first fault probability control index is one of the fault probability control index sets having the smallest probability value.
It will be appreciated that, for a certain system functional failure mode a, the failure probability control index set of the system functional failure mode a includes index 1, index 2, and index 3, and if index 3 is one of index 1, index 2, and index 3 with the smallest probability value, the first failure probability control index of the failure mode a is index 3.
Therefore, by executing the failure probability control index analysis operation on each task section, the analysis result of each task section can be determined, and then the failure probability control index set of each system function failure mode can be determined, and the first failure probability control index of each system function failure mode is screened out, wherein the first failure probability control index can represent the reliability requirement of the system function.
Optionally, according to the method for analyzing reliability of a rail transit signal system provided by the present invention, the performing failure probability control index analysis operation includes:
Acquiring at least one minimum cut set of the task section based on the fault tree, wherein the minimum cut set comprises one or more target system function fault modes;
determining a failure probability control index of each minimum cut set based on the task failure probability control index and a first number, the first number being the total number of the at least one minimum cut set;
determining a second fault probability control index of each target system function fault mode in different minimum cut sets based on the fault probability control index of each minimum cut set and a second number corresponding to each minimum cut set, wherein the second number is the total number of the target system function fault modes in the minimum cut sets;
and determining an analysis result of the task profile based on second fault probability control indexes of the functional fault modes of the target systems in different minimum cut sets.
Specifically, in order to determine an analysis result of the task profile, at least one minimum cut set of the task profile may be obtained based on the fault tree, where the minimum cut set may be a minimum cut set necessary for causing an event on the top of the fault tree to occur, and one minimum cut set may be one or more target system function fault modes, and thus may be a task failure probability control index and a total number of the minimum cut sets (i.e., a first number), a fault probability control index of each minimum cut set may be determined, and further, based on the fault probability control index of each minimum cut set and a second number corresponding to each minimum cut set (i.e., a total number of target system function fault modes in the minimum cut set), a second fault probability control index of each target system function fault mode in different minimum cut sets may be determined, and thus an analysis result of the task profile may be determined.
Alternatively, based on the fault tree, at least one minimal cut set of the task profile may be obtained by determinant or boolean algebra.
Alternatively, the task reliability quantitative indicator of the task profile may be R i The task unreliability quantitative index (i.e., task failure probability control index) of the task profile may be Q i ＝1-R i Where i represents the number of the task profile.
Based on the fault tree, at least one minimum cut set of the task profile is obtained, and the total cut set number (i.e. the first number) of the at least one minimum cut set can be C i The failure probability control index of each minimum cut set can be P cij ＝Q i /C i Where j represents the number of the smallest cut set.
For a certain minimum cut set, if the total number (second number) of the target system function fault modes included in the minimum cut set is N cij For the minimum cut set, the second failure probability control index of the target system failure mode may be P Fij m ＝P cij /N cij Where m represents the number of the functional failure mode of the target system under the minimum cut set.
Therefore, by acquiring at least one minimum cut set of the task section based on the fault tree, the task failure probability control index can be distributed to each target system function fault mode, the analysis result of the task section can be determined, the fault probability control index set of each system function fault mode can be determined by determining the analysis result of each task section, and the first fault probability control index of each system function fault mode can be screened out, wherein the first fault probability control index can represent the reliability requirement of the system function.
Optionally, according to the method for analyzing reliability of a rail transit signal system provided by the present invention, fig. 2 is a second flow chart of the method for analyzing reliability of a rail transit signal system provided by the present invention, as shown in fig. 2, after determining the first failure probability control index of each system functional failure mode based on the failure tree and the task reliability quantitative index of each task section, the method further includes:
the system architecture model is determined by modeling the target signal system in a model-based system engineering MBSE modeling manner, and comprises a plurality of system units.
Specifically, in order to decompose the task reliability requirement of the complex track traffic signal system into each system unit, the complex target signal system can be modeled through the MBSE, a system architecture model of the target signal system can be obtained, the system architecture model can represent functional characteristics of each system unit and relations among the system units, after determining a first failure probability control index of each system functional failure mode, based on the system architecture model of the target signal system, failure logic can be defined for each system unit to determine each system unit failure mode, further, a logic relation of system functional failure caused by system unit failure can be analyzed, a system failure propagation model can be determined, further, the first failure probability control index of each system functional failure mode can be distributed to each system unit failure mode based on the system failure propagation model, a third failure probability control index of each system unit failure mode can be determined, and the third failure probability control index can represent the reliability requirement of the system unit.
It can be understood that by modeling the target signal system based on the MBSE modeling manner, elements such as an activity diagram, a timing diagram, a state diagram, an internal block diagram and the like (including functional operation, functional timing, system composition and the like) can be determined, and the elements can be extracted through neutral file interfaces such as XMI and the like, so as to establish a multi-level normal function model, namely a system architecture model, which can include a logic architecture model, a physical architecture model and a component architecture model.
It will be appreciated that for a system that is relatively simple in function, the failure of its constituent units may be considered to be approximately independent, with failure of the system often resulting from failure of a single component. However, for complex systems, not only may there be dependencies, logic correlations, or timing correlations between unit faults, but the operating state and configuration of the system often also varies from one task scenario to another. By analyzing the logical relation of system function failure caused by system unit faults based on the fault modes of the system units, a system fault propagation model can be constructed, and the system fault propagation model can describe fault propagation and rules of the system, so that the fault control can be used as a core for reliability analysis.
Therefore, by determining the system fault propagation model, the first fault probability control index of each system functional fault mode can be distributed to each system unit fault mode, the third fault probability control index of each system unit fault mode can be determined, the third fault probability control index can represent the reliability requirement of the system unit, and the task reliability requirement of the complex rail transit signal system can be decomposed to each system unit.
Optionally, according to the method for analyzing reliability of a rail transit signal system provided by the invention, the system unit fault mode includes a state space variable, a unit port variable, a trigger event, a state transition function, a transfer function and a port connection relation function.
Specifically, a complex target signal system can be modeled through the MBSE, a system architecture model of the target signal system can be obtained, the system architecture model can represent functional characteristics of each system unit and relations among the system units, a normal mode of each system unit can be determined through analyzing the system architecture model, and then fault logic can be defined for each system unit according to the normal mode of each system unit so as to determine a fault mode of each system unit, wherein the fault mode of each system unit comprises a state space variable, a unit port variable, trigger event information, a state transfer function, a transfer function and a port connection relation function.
It is understood that the state space variables may represent normal and/or fault states of the system elements; the unit port variable may represent a system unit input port value and an output port value; the trigger event information can represent a trigger event of a jump of the internal state of the system unit and a corresponding event distribution type; the state transition function may represent a logical relationship of the system element performing state transition; the transfer function may represent a logical relationship that determines an output port value based on the input port value and the state space variable; the port connection relation function may represent a connection relation between the ports of the present system unit and the ports of other system units.
It can be understood that by referring to the normal mode of each system unit, fault logic is defined for each system unit, so that each system unit fault mode can be determined, a transfer function of the system unit fault mode can represent a logic relationship of determining an output port value based on an input port value and a state space variable, a port connection relationship function of the system unit fault mode can represent a connection relationship of a port of the system unit and ports of other system units, and further, based on each system unit fault mode, a system fault propagation model can be constructed by analyzing the logic relationship of system function failure caused by system unit faults.
It can be understood that the reliability analysis method of the rail transit signal system provided by the invention utilizes the description capability of the MBSE design model on the functions, behaviors and states of the complex system, realizes the functional and reliability homologous modeling, and can overcome the defect that the traditional method cannot describe the fault propagation behaviors of the complex system such as polymorphism, fault correlation and the like.
Thus, by determining state space variables, cell port variables, trigger event information, state transfer functions, and port connection relationship functions for each system cell, each system cell failure mode can be determined, which can be used to construct a system failure propagation model.
Optionally, according to the method for analyzing reliability of a rail traffic signal system provided by the present invention, after the third fault probability control index of each system unit fault mode is determined based on the system fault propagation model and the first fault probability control index of each system functional fault mode, the method further includes;
and determining a fourth failure probability control index of each hardware element failure mode by analyzing the logic relation of the failure of the system unit caused by the hardware element failure mode based on the third failure probability control index of each system element failure mode and each hardware element failure mode.
Specifically, in order to decompose the task reliability requirement of the complex track traffic signal system into each hardware element, after determining the third failure probability control index of each system unit failure mode, the logic relationship of the system unit failure caused by the hardware element failure mode may be analyzed based on each hardware element failure mode, and then the third failure probability control index of each system unit failure mode may be allocated to each hardware element failure mode based on the logic relationship, so as to determine the fourth failure probability control index of each hardware element failure mode, where the fourth failure probability control index may represent the reliability requirement of the hardware element.
Therefore, by analyzing the logical relation of the failure of the system unit caused by the failure mode of the hardware element, the fourth failure probability control index of each hardware element failure mode can be determined, the fourth failure probability control index can represent the reliability requirement of the hardware element, and the task reliability requirement of the complex track traffic signal system can be decomposed into each hardware element.
Optionally, after the primary design of the target signal system is completed, a multi-physical simulation model of the target signal system can be established, and the reliability requirements (including the reliability requirements of the functions of each system, the reliability requirements of the units of each system and the reliability requirements of the hardware elements) of the system are virtually verified by adopting a fault simulation injection and formal verification method, so that the design can be improved and optimized through verification results.
It can be understood that multi-physical field modeling is a technical means for performing virtual verification of a complex system at present, mainly adopts mathematical equations to describe physical laws and phenomena of subsystems in different fields, realizes integration of multi-field models according to a topological structure of the physical system and a connection mechanism of each subsystem, and finally calculates response values of each parameter of the system by solving differential equations, which is also called a system virtual prototype model.
Therefore, depending on the integrated simulation model provided by the MBSE, a multi-physical simulation model approaching to a real use scene and environmental conditions can be constructed, the reliability of the system can be fully verified before the physical construction, and each link of the system reliability design is further improved.
Optionally, fig. 3 is a third flow chart of the reliability analysis method of the rail traffic signal system provided by the present invention, as shown in fig. 3, the rail traffic signal system may be modeled by using an MBSE modeling manner, where the modeling process may include a requirement analysis stage, a system function analysis stage, a logic architecture analysis stage, a physical architecture analysis stage, a component architecture analysis stage, and a verification stage.
As shown in fig. 3, the reliability analysis method of the rail transit signal system provided by the invention can correspond to each stage of the MBSE modeling process:
(1) Task reliability requirements can be determined in a demand analysis stage;
(2) Determining fault modes of all system functions in a system function analysis stage, determining fault trees, and distributing task reliability requirements to all system functions based on the fault trees to determine the reliability requirements of all system functions;
(3) In the logic architecture analysis stage, determining a fault mode of each system logic unit, determining a fault propagation model corresponding to the logic architecture, and distributing the reliability requirement of each system function to each system logic unit based on the fault propagation model to determine the reliability requirement of each system logic unit;
(4) In the physical architecture analysis stage, determining a fault mode of each system physical unit, determining a fault propagation model corresponding to a physical architecture, and distributing the reliability requirement of each system logic unit to each system physical unit based on the fault propagation model to determine the reliability requirement of each system physical unit;
(5) In the component architecture analysis stage, determining a fault mode of each system component unit, determining a fault propagation model corresponding to the component architecture, and distributing the reliability requirement of each system physical unit to each system component unit based on the fault propagation model to determine the reliability requirement of each system component unit;
(6) In the verification stage, a fault simulation injection and formal verification method can be adopted based on a multi-physical simulation model of the rail transit signal system to virtually verify the reliability requirements of the system (including the reliability requirements of the functions of each system, the reliability requirements of the units of each system and the reliability requirements of the hardware elements).
The following is an alternative example of the present invention, but is not limiting.
The method takes an interlocking system in an urban rail transit signal system as an object, and combines technical processes of system MBSE demand analysis, functional analysis, architecture design and the like to perform multi-level fault mode identification and reliability requirement analysis, so that the technical scheme and the application process of key technology of the method are described.
(1) Reliability requirements of the interlock system;
the basic reliability of the interlocking system is generally represented by average fault-free interval time, the task reliability is generally represented by task reliability, and the magnitude is generally not lower than 0.99; while interlock systems are generally required to have "fail-safe" capabilities as safety critical systems.
(2) Determining a reliability requirement of a system function of the interlock system;
and identifying the top-level function of the system according to the use task scene model and the system function model of the interlocking system, and constructing a task function relation model which is used for representing the mapping relation between each task section and each system function.
Fig. 4 is a schematic diagram of a system task of the interlocking system provided by the present invention, and as shown in fig. 4, a task scene model includes several types of tasks including system power-on start, system platform initialization, input processing, application business processing, and output processing.
Fig. 5 is a task decomposition schematic diagram of the interlocking system provided in the present invention, as shown in fig. 5, for different types of tasks, performing multi-level task decomposition, decomposing a system platform initialization task into task sections, and defining specific input/output and influencing factors under each task section.
Fig. 6 is a schematic diagram illustrating system functional decomposition of the interlocking system provided by the present invention, and as shown in fig. 6, a system functional model describes interactions and interdependencies between top functions of the system, including an external network communication function, an internal network communication function, an input two-way/two-way function, a device state acquisition processing function, an approach control function, a device driving processing function, an output two-way/two-way function, and the like.
After the task scene model and the system function model are obtained, a task function relation model is constructed by analyzing the mapping relation between each task section and each system function.
FIG. 7 is a schematic diagram of a system fault tree of the interlocking system, which causes a system task failure, and as shown in FIG. 7, a fault tree is determined through failure analysis based on a task function relationship model, wherein the fault tree is used for representing a logic relationship of each system function fault mode causing the task failure.
Based on the fault tree and the task reliability quantitative index of each task section, a first fault probability control index of each system function fault mode can be determined.
(3) Determining a reliability requirement of a system unit of the interlock system;
fig. 8 is a schematic diagram of a system fault propagation model of an interlocking system according to the present invention, as shown in fig. 8, after determining a first fault probability control index of each system functional fault mode, based on a system architecture model of the interlocking system (including a logic architecture model, a physical architecture model and a component architecture model of the interlocking system), fault logic may be defined for each system unit to determine each system unit fault mode, and further, a logic relationship of system functional failure caused by a system unit fault may be analyzed, and a system fault propagation model may be determined. Wherein SF represents a system function, LU represents a logical unit, PU represents a physical unit, and CU represents a component unit.
After determining the system fault propagation model of the interlocking system, the first fault probability control index of each system functional fault mode can be distributed to each system unit fault mode based on the system fault propagation model, the third fault probability control index of each system unit fault mode can be determined, and the third fault probability control index can represent the reliability requirement of the system unit.
(4) Determining a reliability requirement of a hardware element of the interlock system;
after determining the third failure probability control index of each system unit failure mode, a logic relationship of the system unit failure caused by the hardware unit failure mode may be analyzed based on each hardware unit failure mode, and then the third failure probability control index of each system unit failure mode may be allocated to each hardware unit failure mode based on the logic relationship, so as to determine a fourth failure probability control index of each hardware unit failure mode, where the fourth failure probability control index may represent a reliability requirement of the hardware unit.
(5) Simulating and verifying the reliability of the system;
after the primary design of the interlocking system is finished, a physical simulation model of the interlocking system can be established, the reliability requirements (including the reliability requirements of the functions of each system, the reliability requirements of the units of each system and the reliability requirements of the hardware elements) of the system are virtually verified by adopting fault simulation injection and formal verification methods, and the design can be improved and optimized through verification results.
According to the reliability analysis method for the track traffic signal system, the complex target signal system can be modeled through the MBSE, the task scene model and the system function model of the target signal system can be obtained, the task function relation model can be determined based on the task scene model and the system function model, further the logical relation of task failure caused by the system function fault model can be analyzed based on the task function relation model to determine a fault tree, further task failure probability control indexes of each task section can be distributed to each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section, the first fault probability control indexes of each system function fault mode can be determined, the first fault probability control indexes can represent the reliability requirements of system functions, and the task reliability requirements of the complex track traffic signal system are decomposed to each system function.
The reliability analysis device of the rail transit signal system provided by the invention is described below, and the reliability analysis device of the rail transit signal system described below and the reliability analysis method of the rail transit signal system described above can be correspondingly referred to each other.
Fig. 9 is a schematic structural diagram of a reliability analysis device of a rail transit signal system provided by the present invention, as shown in fig. 9, the device includes: a first determination module 901, a second determination module 902, and a third determination module 903, wherein:
the first determining module is used for determining a task function relation model based on a task scene model and a system function model of the target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
the second determining module is used for determining a fault tree through failure analysis based on the task function relation model and the function fault modes of the systems, wherein the fault tree is used for representing the logic relation of the task failure caused by the function fault modes of the systems;
the third determining module is used for determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
wherein the task scenario model and the system function model are determined by modeling the target signal system in a model-based system engineering MBSE modeling manner,
the task scene model includes a plurality of the task profiles, and the system function model includes a plurality of 5 of the system functions.
The reliability analysis device of the rail transit signal system provided by the invention can model a complex target signal system through MBSE, can acquire a task scene model and a system function model of the target signal system, and can be based on the task scene model and the system function model
Determining a task function relation model, further analyzing a logical relation of task failure caused by a system 0 function failure mode based on the task function relation model to determine a failure tree, and further enabling the task to be based
Task reliability quantitative indexes of each task section in a fault tree and the task section are distributed to each system function fault mode, so that a first fault probability control index of each system function fault mode can be determined, and the first fault probability control index can represent the system function fault mode
The reliability requirement of the system function is realized, and the task reliability 5 requirement of the complex track traffic signal system is decomposed into the system functions.
Fig. 10 is a schematic structural diagram of an electronic device according to the present invention, and as shown in fig. 10, the electronic device may include: processor 1010, communication interface (Communications Interface) 1020, memory 1030, and communication
To perform a method of analyzing reliability of a rail transit signal system, the method comprising:
task scene model and system function model based on target signal system, and task work is determined
The energy relation model is used for representing the mapping relation between each task section and each system function 5;
determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure;
determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
Further, the logic instructions in the memory 1030 described above may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of executing the method for analyzing reliability of a rail transit signal system provided by the above methods, the method comprising:
Determining a task function relation model based on a task scene model and a system function model of a target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure;
determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method for analyzing reliability of a rail transit signal system provided by the above methods, the method comprising:
Determining a task function relation model based on a task scene model and a system function model of a target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure;
determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the above technical solution is essentially or at present
The technical contribution may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk
Disk, etc., comprising instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the various embodiments or portions of the methods described herein.
Finally, it should be noted that: the above examples are only for illustrating the technical scheme of the present invention, and 0 is not a limitation thereof; although the present invention has been described in detail with reference to the foregoing embodiments, it is to be understood that
The person of ordinary skill in the art will appreciate that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for analyzing reliability of a rail transit signal system, comprising:
determining a task function relation model based on a task scene model and a system function model of a target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
determining a fault tree through failure analysis based on the task function relation model and each system function fault mode, wherein the fault tree is used for representing a logic relation of each system function fault mode causing task failure;
determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
2. The method for analyzing the reliability of the rail transit signal system according to claim 1, wherein determining the first failure probability control index of each system failure mode based on the failure tree and the task reliability quantitative index of each task profile includes:
Determining task failure probability control indexes of each task section based on task reliability quantitative indexes of each task section;
based on the fault tree and task failure probability control indexes of each task section, respectively executing failure probability control index analysis operation on each task section, and determining an analysis result of each task section, wherein the analysis result comprises one or more second failure probability control indexes corresponding to each target system function fault mode, and the target system function fault mode is a system function fault mode which is determined based on the fault tree and is associated with the task section;
based on the analysis result of each task section, classifying and collecting a plurality of second fault probability control indexes according to the system function fault modes, and determining a fault probability control index set of each system function fault mode;
and determining a first fault probability control index of each system function fault mode based on a fault probability control index set of each system function fault mode, wherein the first fault probability control index is one of the fault probability control index sets with the minimum probability value.
3. The method for analyzing reliability of a rail transit signal system according to claim 2, wherein the performing failure probability control index analysis operation includes:
Acquiring at least one minimum cut set of the task section based on the fault tree, wherein the minimum cut set comprises one or more target system function fault modes;
determining a failure probability control index of each minimum cut set based on the task failure probability control index and a first number, the first number being the total number of the at least one minimum cut set;
determining a second fault probability control index of each target system function fault mode in different minimum cut sets based on the fault probability control index of each minimum cut set and a second number corresponding to each minimum cut set, wherein the second number is the total number of the target system function fault modes in the minimum cut sets;
and determining an analysis result of the task profile based on second fault probability control indexes of the functional fault modes of the target systems in different minimum cut sets.
4. The method for analyzing the reliability of a rail transit signal system according to claim 1, further comprising, after the determining of the first failure probability control index for each system failure mode based on the failure tree and the task reliability quantitative index for each task profile:
determining a fault mode of each system unit based on a system architecture model of the target signal system, wherein the fault mode of each system unit is used for representing fault logic of the system unit;
Based on the fault modes of each system unit, determining a system fault propagation model by analyzing the logic relation of system function failure caused by the system unit fault;
determining a third fault probability control index of each system unit fault mode based on the system fault propagation model and the first fault probability control index of each system functional fault mode;
the system architecture model is determined by modeling the target signal system in a model-based system engineering MBSE modeling manner, and comprises a plurality of system units.
5. The method of claim 4, wherein the system unit fault modes include state space variables, unit port variables, trigger event information, state transition functions, transfer functions, and port connection relationship functions.
6. The method according to claim 4 or 5, characterized by further comprising, after the determining of the third failure probability control index for each system unit failure mode based on the system failure propagation model and the first failure probability control index for each system functional failure mode;
And determining a fourth failure probability control index of each hardware element failure mode by analyzing the logic relation of the failure of the system unit caused by the hardware element failure mode based on the third failure probability control index of each system element failure mode and each hardware element failure mode.
7. A track traffic signal system reliability analysis device, comprising:
the first determining module is used for determining a task function relation model based on a task scene model and a system function model of the target signal system, wherein the task function relation model is used for representing the mapping relation between each task section and each system function;
the second determining module is used for determining a fault tree through failure analysis based on the task function relation model and the function fault modes of the systems, wherein the fault tree is used for representing the logic relation of the task failure caused by the function fault modes of the systems;
the third determining module is used for determining a first fault probability control index of each system function fault mode based on the fault tree and task reliability quantitative indexes of each task section;
the task scene model and the system function model are determined by modeling the target signal system through a model-based system engineering MBSE modeling mode, the task scene model comprises a plurality of task profiles, and the system function model comprises a plurality of system functions.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the rail transit signal system reliability analysis method of any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the rail transit signal system reliability analysis method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the rail traffic signal system reliability analysis method according to any one of claims 1 to 6.
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| CN116579669B (en) * | 2023-07-12 | 2024-03-26 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Reliability evaluation method, reliability evaluation device, computer equipment and storage medium thereof |
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