CN114528688A

CN114528688A - Method and device for constructing reliability digital twin model and computer equipment

Info

Publication number: CN114528688A
Application number: CN202210014678.XA
Authority: CN
Inventors: 杨洪旗; 聂国健; 刘宇婕; 胡宁; 赖喆; 潘勇; 张杰毅; 杨延超
Original assignee: China Electronic Product Reliability and Environmental Testing Research Institute
Current assignee: China Electronic Product Reliability and Environmental Testing Research Institute
Priority date: 2022-01-07
Filing date: 2022-01-07
Publication date: 2022-05-24

Abstract

The application relates to a method and a device for constructing a reliability digital twin model and computer equipment. The method comprises the following steps: acquiring an initial digital prototype model of a product; determining a fault mode of each component in the initial digital prototype model, determining a component reliability model of each component based on the fault mode, and associating each component reliability model with the corresponding component in the initial digital prototype model to obtain an initial reliability digital twin model; acquiring actual measurement data obtained by actually measuring a product; carrying out fault analysis on actual measurement data corresponding to the model input parameters by using an initial reliability digital twin model to obtain a model fault analysis result; and updating the initial reliability digital twin model by combining the model fault analysis result and the actual measurement fault analysis result to obtain the reliability digital twin model. The reliability digital twin model constructed by the method can be used for evaluating the reliability of the product and meeting the forward design work requirement of the product.

Description

Method and device for constructing reliability digital twin model and computer equipment

Technical Field

The present application relates to the field of reliability technologies, and in particular, to a method and an apparatus for constructing a reliable digital twin model, a computer device, a storage medium, and a computer program product.

Background

With the rapid development of the internet of things and artificial intelligence technology, the product production has the development trend of systematization, unmanned, universalization, intellectualization, precision and clustering. While the requirement on the production of the product is higher and higher, the corresponding research and development period is shorter and shorter, so that the research and development mode of the product is developed towards digitization, modeling, automation and intelligence. Under the promotion of the development trend and the engineering requirements, a digital design mode with dual driving of a model and data is generated, and a digital twin provides an ideal solution for a research and development mode with a life cycle model and data fusion real-time driving.

The digital twin can be connected with real world objects, and by constructing a digital twin model corresponding to the physical entity and carrying out visualization, debugging, experience, analysis and optimization on the digital twin model, the comprehensive technical strategy for the performance and the running performance of the physical entity is improved.

However, in the existing product digital twin model construction method, the digital twin-based product function model construction method is the most mature, and the main idea is to provide a construction method of each module function model according to the characteristics of a product physical entity module, a virtual entity module and an interaction channel module, and construct an overall function model through the interaction relationship among the modules. The digital twin model constructed in the way only represents the function relation between the functions of the product, cannot analyze and evaluate the reliability of the product, and cannot meet the forward design work requirement of the product.

Disclosure of Invention

In view of the above, it is necessary to provide a method, an apparatus, a computer device, a computer readable storage medium, and a computer program product for constructing a digital twin model that can be towed by a product failure.

In a first aspect, the present application provides a method for constructing a reliability digital twin model, the method comprising:

acquiring an initial digital prototype model of a product;

determining a failure mode of each component in the initial digital prototype model, determining a component reliability model of each component based on the failure mode, and associating each component reliability model with the corresponding component in the initial digital prototype model to obtain an initial reliability digital twin model containing each component reliability model;

acquiring actual measurement data obtained by actually measuring the product;

using the initial reliability digital twin model to perform fault analysis on actual measurement data corresponding to model input parameters in the initial reliability digital twin model to obtain a model fault analysis result;

and updating the initial reliability digital twin model by combining the model fault analysis result and the actually measured fault analysis result obtained by actually measuring to obtain a reliability digital twin model.

In one embodiment, the component reliability model comprises a failure physics model;

said determining a component reliability model for each of said components based on said failure modes comprises:

determining a fault mechanism of each component, and acquiring an initial fault mechanism model corresponding to each fault mechanism based on each fault mechanism;

and determining a fault physical model of each component according to the historical operation data of each component and an initial fault mechanism model corresponding to the fault mechanism of each component.

In one embodiment, the component reliability model comprises a fault propagation model;

classifying failure behaviors of internal components of each assembly when the internal components fail, and determining failure types of the failure behaviors, wherein the failure types comprise assembly input failure, assembly self failure and assembly output failure;

and logically combining the failure types of the internal components of each assembly through a logic gate to generate a fault transmission model of each assembly.

In one embodiment, the component reliability model comprises a failure state behavior model;

analyzing the faults of the assemblies to obtain fault generation reasons corresponding to the assemblies;

determining a fault reduction control measure corresponding to each component according to the fault generation reason;

and generating a failure state behavior model of each component based on the failure generation cause and the failure reduction control measure.

In one embodiment, the component reliability model comprises a maintenance and assurance policy model;

acquiring corresponding maintenance information when each component fails;

and generating a maintenance support strategy model of each component based on the maintenance information.

In one embodiment, the updating the initial reliability digital twin model by combining the model fault analysis result and the actually measured fault analysis result obtained by actually measuring to obtain a reliability digital twin model includes:

comparing the model fault analysis result with the actual measurement fault analysis result;

determining the deviation condition of related parameters in the initial reliability digital twin model according to the comparison result;

and updating the initial reliability digital twin model based on the deviation condition of the related parameters to obtain the reliability digital twin model.

In one embodiment, the method further comprises:

acquiring product refinement information and product characteristic information of the next stage of the product;

and updating the reliability digital twin model at the current stage according to the product thinning information and the product characteristic information to obtain the reliability digital twin model at the next stage.

In a second aspect, the present application provides a reliability digital twin model building apparatus, the apparatus comprising:

the initial digital prototype model acquisition module is used for acquiring an initial digital prototype model of the product;

an initial reliability digital twin model building module, configured to determine a failure mode of each component in the initial digital prototype model, determine a component reliability model of each component based on the failure mode, and associate each component reliability model with a corresponding component in the initial digital prototype model, to obtain an initial reliability digital twin model including each component reliability model;

the product actual measurement data acquisition module is used for acquiring actual measurement data obtained by actually measuring the product;

the model fault analysis result generation module is used for carrying out fault analysis on actual measurement data corresponding to model input parameters in the initial reliability digital twin model by using the initial reliability digital twin model to obtain a model fault analysis result;

and the reliability digital twin model building module is used for updating the initial reliability digital twin model by combining the model fault analysis result and the actually-measured fault analysis result obtained by actually measuring to obtain a reliability digital twin model.

In a third aspect, the present application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when the processor executes the computer program.

In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method described above.

According to the reliability digital twin model construction method, the reliability digital twin model construction device, the reliability digital twin model construction computer equipment, the storage medium and the computer program product, firstly, the failure mode of each component is determined by taking each component in the initial digital prototype model of the product as a basic unit, the component reliability model of each component is determined based on the failure mode, the component reliability model of each component is associated to the initial digital prototype model of the product, so that the initial reliability digital twin model containing the component reliability model of each component is obtained, and then the initial reliability digital twin model is updated according to actually measured data generated by actually measuring the product, so that the reliability digital twin model is obtained. Because the initial reliability digital twin model is constructed on the basis of the component reliability model of each component of the product during construction, the updated reliability digital twin model can accurately map all elements of the product by taking a fault as a center in the use process, truly reflect the reliability characteristics, behaviors and fault forming process of the product, evaluate the reliability of the product and meet the forward design work requirement of the product.

Drawings

FIG. 1 is a schematic flow chart diagram of a method for constructing a reliability digital twin model in one embodiment;

FIG. 2 is a flowchart illustrating the component reliability model step of determining components based on failure modes in one embodiment;

FIG. 3 is a flowchart illustrating the component reliability model step for determining components based on failure modes in another embodiment;

FIG. 4 is a flowchart illustrating the step of determining a component reliability model for each component based on failure modes in another embodiment;

FIG. 5 is a flowchart illustrating the step of determining a component reliability model for each component based on failure modes in another embodiment;

FIG. 6 is a flowchart illustrating a method for constructing a reliability digital twin model according to another embodiment;

FIG. 7 is a block diagram showing an apparatus for constructing a reliability digital twin model according to an embodiment;

FIG. 8 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

In one embodiment, as shown in fig. 1, a method for constructing a reliability digital twin model is provided, which is applied to a terminal for illustration, and it is understood that the method is also applied to a server, and is also applied to a system comprising the terminal and the server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the steps of:

step 102, an initial digital prototype model of the product is obtained.

The initial digital prototype model of the product is a digital model which can reflect the geometric characteristics, physical characteristics and logical connection relation of all components in the product. Specifically, according to the functional, logical or physical characteristics of the product in the current development stage, researchers use corresponding software tools to construct a digital prototype model corresponding to the product according to certain steps, and the digital prototype model is stored in a database in advance. When a reliability digital twin model of a product needs to be constructed, a digital prototype model corresponding to the product is directly obtained from a database and is used as an initial digital prototype model of the product.

In one embodiment, the initial digital prototype model is constructed in a manner that includes:

and constructing a geometric feature model of the product according to the three-dimensional geometric parameters of the product.

Specifically, the product geometric feature model mainly describes three-dimensional geometric parameters, assembly relationships, structural relationships and the like of the product, wherein the three-dimensional geometric parameters of the product include, but are not limited to, the shape, size, position and the like of the product. Different from a logic architecture model, the geometric feature model of the product is closer to a physical entity visually, and the actual composition and the connection relation of the product are described in more detail. It can be understood that the product geometric feature model can be obtained by modeling by adopting three-dimensional modeling software such as CATIA, SolidWorks and the like.

And constructing a physical characteristic model of the product according to the physical characteristics of the product.

Specifically, the product physical characteristic model refers to a professional characteristic model covering multiple disciplines and multiple fields. Such as mechanical structure, engineering material, kinematic law, structural strength, stiffness, fatigue, damage, pneumatics, fluids, etc. characteristics in the mechanical field; electromagnetic, heat dissipation, electric stress, control and other characteristics in the field of electronic and electric appliances, and multidisciplinary, cross-domain thermosetting coupling, heat flow coupling, fluid-solid coupling and other characteristics. It is understood that the product physical property model can be obtained by modeling with finite element analysis software such as Abaqus, ANSYS, Hypermesh, and the like.

And generating an initial digital prototype model of the product based on the geometric feature model of the product and the physical characteristic model of the product.

And 104, determining the fault mode of each component in the initial digital prototype model, determining a component reliability model of each component based on the fault mode, and associating each component reliability model with the corresponding component in the initial digital prototype model to obtain an initial reliability digital twin-organism model containing each component reliability model.

Wherein, each component in the initial digital prototype model is the minimum unit which needs to be analyzed when the product is subjected to fault analysis. For example, when a mobile phone product is subjected to fault analysis, the basic unit can be a display screen, an information processing module, a power supply module and the like. If the information processing module in the mobile phone is used as a product to perform fault analysis, the basic units can be a signal receiving unit, a signal processing unit, a signal sending unit and the like. It will be appreciated that each component has its corresponding component name and ID code which is used to provide a recognition and localization for later association of the component reliability model of each component into the initial digital prototype model.

The failure mode is a basic expression form when each component fails. Failure modes include hardware failures and functional failures. Specifically, for components that are lower in hierarchy. While for high-level components, both hardware and functional failures may exist. For example, the signal receiving unit, the signal processing unit and the signal transmitting unit, which are components of the signal processing module, are prone to have hardware faults. The components of the mobile phone product, i.e., the display screen, the signal processing module, the power supply module, etc., may have hardware faults and functional faults at the same time. It can be understood that a failure mode in which the output of the lower-level cell is unstable and the function of the upper-level cell cannot be realized can be regarded as a functional failure mode. Therefore, when the failure mode of the component is determined to be functional failure, only the logical relationship between hardware failures of the hierarchical unit needs to be represented.

The component reliability model is a digital model which can represent the occurrence reason of each component fault and a series of activities caused after the component fault occurs. It will be appreciated that activities that may result after a fault include, but are not limited to, fault delivery, fault detection, fault repair and assurance, system status changes, and the like.

Specifically, the method comprises the steps of determining a fault mode of each component by taking each component in an initial digital prototype model as a basic unit, carrying out fault analysis on each component based on the fault mode corresponding to each component, and determining a component reliability model of each component according to a fault analysis result. And (3) the component reliability model of each component is coded according to the name and the ID of each component and is related to the initial digital prototype model of the product to obtain an initial reliability digital twin model.

In one embodiment, the association relationship between each component and the failure mode is pre-stored in a database, and the corresponding failure mode can be obtained from the database according to the name and the ID code of each component.

In one embodiment, if the component has no pre-stored association relationship with the failure mode in the database, the analysis is performed according to the working principle of the component to determine the failure mode of the component.

And 106, acquiring actual measurement data obtained by actually measuring the product.

Specifically, a sensor and a data acquisition system are used for collecting relevant environmental parameters, product states and behavior data in the operation process of the product real object system, actual measurement data of the product are obtained, and the actual measurement data of the product are obtained.

In one embodiment, after the actual measurement data of the product in the operation process of the product real object system is collected by using the sensor and the data collection system, the collected data needs to be preprocessed. Specifically, the method comprises the steps of carrying out abnormal data removal, error data correction, repeated data removal, data smoothing, data normalization, useful data characteristic searching and the like on the directly acquired data through preprocessing methods such as data cleaning, data transformation, data reduction and the like.

And 108, using the initial reliability digital twin model to perform fault analysis on actual measurement data corresponding to the model input parameters in the initial reliability digital twin model to obtain a model fault analysis result.

Specifically, a product real object is used, a corresponding test running environment is built based on a reliability system engineering software platform, a related sensor and a data acquisition and processing system of the initial reliability digital twin model, and a mapping relation between actual measurement data of the product and related input parameters of the initial reliability digital twin model is established. And inputting actual measurement data corresponding to the model input parameters in the initial reliability digital twin model into the initial reliability digital twin model, performing fault analysis, and determining a fault analysis result obtained by virtual simulation analysis as a model fault analysis result. It is understood that the input parameters may be a task time of the product, a test point position of the product or the component in each time period, a number of maintenance support sites, reliability parameters of the product, and the like.

In one embodiment, the reliability system engineering software platform comprises interfaces to MBSE software, product design systems, simulation systems, project management systems, and the like.

And step 110, updating the initial reliability digital twin model by combining the model fault analysis result and the actually measured fault analysis result obtained by actual measurement to obtain a reliability digital twin model.

The actual measurement fault analysis result is obtained by running and testing the product real object in the built test running environment, and represents the actual fault analysis result of the product real object.

Specifically, the recorded model fault analysis result is compared with the actually measured fault analysis result, and the initial reliability digital twin model is updated according to the comparison result to obtain the reliability digital twin model.

In the reliability digital twin model building method, firstly, each component in an initial digital prototype model of a product is taken as a basic unit, a fault mode of each component is determined, a component reliability model of each component is determined based on the fault mode, the component reliability model of each component is associated to the initial digital prototype model of the product, so that an initial reliability digital twin model containing the component reliability model of each component is obtained, and then the initial reliability digital twin model is updated according to actually measured data generated by actually measuring the product, so that the reliability digital twin model is obtained. Because the initial reliability digital twin model is constructed on the basis of the component reliability model of each component of the product during construction, the updated reliability digital twin model can accurately map all elements of the product by taking a fault as a center in the use process, truly reflect the reliability characteristics, behaviors and fault forming process of the product, evaluate the reliability of the product and meet the forward design work requirement of the product.

In one embodiment, as shown in FIG. 2, the component reliability model includes a failure physics model; determining a component reliability model for each component based on the failure modes, comprising the steps of:

step 202, determining a failure mechanism of each component, and acquiring an initial failure mechanism model corresponding to each failure mechanism based on each failure mechanism.

The failure mechanism of the component refers to a failure physical process of the component causing failure when the component fails in operation. Each failure mechanism has its corresponding failure mechanism model. It can be understood that, in this embodiment, each fault mechanism and the fault mechanism model corresponding to the fault mechanism are stored in the database in advance in an associated manner, and after the fault mechanism of the component is determined, the fault mechanism model corresponding to the fault mechanism can be directly obtained from the database as the initial fault mechanism model.

Specifically, a fault mechanism corresponding to each component is analyzed and determined according to the operation process of each component, a prestored fault mechanism model is obtained from a database according to the fault mechanism corresponding to each component, and the fault mechanism model is used as an initial fault mechanism model. Common failure mechanism models include an interconnection thermal fatigue life, a low cycle fatigue model, a high cycle fatigue model, a crack propagation model, a diffusion model, an Arrhenius (Arrhenius) model, an raining (Eying) model and the like.

And step 204, determining a fault physical model of each component according to the historical data of each component and the initial fault mechanism model corresponding to the fault mechanism of each component.

And the historical data of each component is historical operating data of each component. Specifically, each fault mechanism model has corresponding model parameters, and specific values of the model parameters are related to corresponding components and operating data of the components, so that after the initial fault mechanism model is obtained, the model parameters of the corresponding initial fault mechanism model need to be determined according to historical data of the components, and finally, the fault physical model of each component is obtained.

In one embodiment, if the failure mechanism of a certain component does not have a corresponding failure mechanism model, the corresponding failure mechanism model is constructed by using a modeling language according to a large amount of historical failure data of the component, and the failure mechanism model is determined as a failure physical model of the component.

In the embodiment, the failure mechanism of each component is determined through analysis, the corresponding initial failure mechanism model is obtained based on each failure mechanism, and meanwhile, the initial failure mechanism model is updated according to the historical operating data of each component, so that the failure physical model corresponding to each component is obtained. Because the fault physical model is constructed based on the fault mechanism of each component, the fault physical model can accurately describe the failure behavior rule movement of each component under the action of the physical processes of machinery, electronics, heat, chemistry and the like, and can provide a basis for the improvement, classification and use of product materials and elements, the reliability evaluation, design optimization, maintenance and the like of products in actual use.

In one embodiment, as shown in FIG. 3, the component reliability model includes a fault propagation model; determining a component reliability model for each component based on the failure modes, comprising the steps of:

step 302, classifying failure behaviors of internal components of each component during failure, and determining failure types of the failure behaviors, wherein the failure types comprise component input failure, component self failure and component output failure.

Each component can be composed of at least one internal part, and when each component has a fault, the failure types of the internal parts of the component, which have failure behaviors, are different, wherein the failure types comprise component input failure, component self failure and component output failure. The component input failure refers to the failure behavior that external things cannot be input into the component; the failure of the component is the failure behavior that the internal parts of the component are damaged and cannot work; a component output failure is a failure relief in which the component fails to transmit the contents inside to the outside.

Taking a main case with a component as a computer as an example, the main case internally comprises a plurality of components, such as a power supply interface, an interface with a display screen, a USB interface, a network port, a processor, a memory and the like, and the failure of component input refers to abnormal power supply input, keyboard input or incapability of transmitting network transmission data to the USB interface or the network port and the like; the failure of the component itself refers to memory failure, processor failure, power input interface failure and the like; the component output failure means that the combed information cannot be transmitted to a display screen or cannot be sent out through a network port due to the main case.

Specifically, when each component has a fault, the failure behaviors of internal components of the component are analyzed, the failure behaviors are classified, and the failure type of the failure behaviors is determined, wherein the failure type comprises component input failure, component self failure and component output failure.

And step 304, logically combining the failure types of the internal components of each assembly through a logic gate to generate a fault transmission model of each assembly.

Specifically, the failure types of the internal components of each component are subjected to logic combination through a logic gate by adopting a graphical modeling method represented by the logic gate, so that a fault transmission model corresponding to each component is generated.

In one embodiment, the logic gate includes and, or, not, select, and vote logic.

In the above embodiment, the failure types of the internal components of each component are classified and logically combined through the logic gates, so as to obtain the failure transmission model of each component. Therefore, when a certain component sends a fault, the fault transmission model can effectively evaluate the overall influence possibly generated by the fault, and the forward design work requirement of the product is met.

In one embodiment, as shown in FIG. 4, the component reliability model includes a failure state behavior model; determining a component reliability model for each component based on the failure modes, comprising the steps of:

and 402, analyzing the faults of the components to obtain the fault generation reasons corresponding to the components.

Specifically, when each component has a fault, the corresponding fault generation reason is provided, and fault analysis is performed on the fault possibly generated by each component to obtain the reason that each component may have the fault. For example, the possible faults generated by the display screen of the mobile phone include that the display screen cannot display a page, the color of the display page of the display screen is distorted, and the possible faults generated by the display screen are analyzed by faults, and the possible reasons for the faults include a fault of a display screen interface, a fault of a display element of the display screen, aging of the display screen, and the like.

And step 404, determining a fault reduction control measure corresponding to each component according to the fault generation reason.

The fault reduction control measures are measures required in the process of eliminating component faults, and include but are not limited to measures such as failure detection, maintenance guarantee activities, function reconstruction and the like. It will be appreciated that the fault mitigation control measures correspond to fault causes, each of which has its corresponding fault mitigation control measure. If the failure cause of the display screen is the failure of the display screen interface, the corresponding failure reduction control measures include, but are not limited to, detecting the display screen interface, determining the failure behavior type of the display screen interface, and maintaining the specific maintenance measures of the display screen interface. Specifically, a fault reduction control measure corresponding to each component is determined according to the fault generation reason of each component.

At step 406, a failure state behavior model for each component is generated based on the cause of the failure and the failure mitigation control measures.

Specifically, modeling is performed according to a fault occurrence reason corresponding to a fault which may occur in each component and a fault reduction control measure corresponding to the fault occurrence reason, so as to generate a failure state behavior model of each component.

In one embodiment, a method obtained by a state machine diagram is adopted, modeling is carried out according to a fault generation reason corresponding to a fault possibly generated by each component and a fault reduction control measure corresponding to the fault generation reason, and a failure state behavior model of each component is generated.

In the above embodiment, the failure state behavior model of each component is established with the cause of the failure and the failure reduction control measure as inputs. Therefore, the failure state behavior model can represent the complete state conversion process of the product assembly, which is caused by assembly failure, failure detection, maintenance and guarantee activities or function reconstruction due to various reasons, and finally the assembly recovers to a normal state, and the complete state conversion process comprises the representation of the assembly state, the state detection relation, the failure transmission relation, the maintenance and guarantee activities and the like. When a product sends a fault, the failure state behavior model can provide a complete processing scheme for the product from the fault to the recovery, so that the reliability of the product can be more comprehensively evaluated, and the forward design work requirement of the product is further met.

In one embodiment, as shown in FIG. 5, the component reliability model includes a maintenance and assurance strategy model; determining a component reliability model for each component based on the failure modes, comprising the steps of:

step 502, obtaining corresponding maintenance information when each component has a fault.

The maintenance information is information generated by decomposing maintenance work when each component has a failure into work words or work procedures, and is stored in a database in advance.

Specifically, in the research and development process, the maintenance guarantee strategy considering the failure mechanism and corresponding real-time running state forms a guarantee scheme matched with the product guarantee by means of a product reliability digital twin technology, decomposes the maintenance guarantee work into sub-works or sub-processes, and determines the maintenance, test and guarantee resource requirements corresponding to each sub-work or sub-process as maintenance information. And acquiring corresponding maintenance information when each component fails.

Step 504, generating a maintenance support strategy model of each component based on the maintenance information.

Specifically, the maintenance information is used as input information, and a maintenance support strategy model of each component is constructed.

In one embodiment, the maintenance and assurance policy model for each component is constructed using the SysML Specification modeling language.

In one embodiment, the maintenance and assurance policy model includes a maintenance test assurance activity model and an assurance organization model.

Specifically, the maintenance test guarantee activity model describes the activity processes of fault detection, fault maintenance, resource allocation and the like after the functional failure occurs. The detection activities mostly adopt a BIT (build-in test) design, and can be directly expanded in an activity behavior model of a functional model, and fault maintenance and guarantee activities and the like are required to be executed by external participants of the system and expanded in the activity behavior model of the external participants. The support organization model comprises maintenance sites, maintenance personnel and support resource models, belongs to an external interactive system component of an equipment system, and mainly adopts a 'participant' (meta-model type Actor) in a SysML model to carry out modeling, wherein each maintenance site comprises the maintenance personnel and the support resources, the maintenance sites have the attributes of maintenance level, personnel number, spare part type, spare part number and the like, and the maintenance support relationship of a specific maintenance organization and a product is embodied in a maintenance support activity model.

In the embodiment, the maintenance support strategy model is generated according to the corresponding maintenance information when each component generates a fault, maintenance test support activities and support organization activities after the product generates functional failure can be represented, when the product sends the fault, a complete processing scheme for how the product performs maintenance support processing can be given, the product can be more comprehensively evaluated in reliability, and the forward design work requirement of the product is further met.

In one embodiment, the updating the initial reliability digital twin model according to the model fault analysis result and the actually measured fault analysis result obtained by actually measuring to obtain the reliability digital twin model includes:

comparing the model fault analysis result with the actual measurement fault analysis result; determining the deviation condition of related parameters in the initial reliability digital twin model according to the comparison result; and updating the initial reliability digital twin model based on the deviation condition of the related parameters to obtain the reliability digital twin model.

The relevant parameters are design parameters when the initial reliability digital twin model is constructed, such as test points of each designed component, maintenance sites and the like.

Specifically, the model fault analysis result is a fault analysis structure obtained by inputting product measured data into the constructed initial reliability digital twin model; and the actual measurement fault analysis result is a real fault analysis result of the product obtained after the product real object actually generates faults in the built operation environment and the faults are analyzed. And comparing the two to obtain the deviation condition of the related parameters of the initial reliability digital twin model. And adjusting the values of related parameters in the initial reliability digital twin model according to the parameter deviation condition, and updating the initial reliability digital twin model to obtain the reliability digital twin model of the product.

In one embodiment, in the product design stage, the comparison can be performed according to the model fault analysis result and the actual measurement fault analysis record, whether a design weak link exists or not is judged, and if the design weak link exists, the product design scheme is optimized according to the comparison result.

In the above embodiment, the initial reliability digital twin model is updated according to the failure analysis result of the entity product by comparing the actually measured failure analysis result with the model failure analysis result. The finally generated reliability digital twin model can be ensured to accurately map all the elements of the product, the forming process of the reliability characteristics, behaviors and faults of the product is truly reflected, and the forward design work requirement of the product is met.

In one embodiment, the reliability digital twin model construction method further comprises: acquiring product refinement information and product characteristic information of a next stage of a product; and updating the reliability digital twin model at the current stage according to the product refinement information and the product characteristic information to obtain the reliability digital twin model at the next stage.

In particular, in the actual production process, the actual update speed of the product is very rapid along with the development progress of the product. On the basis that the reliability digital twin model of the product at the current stage is constructed, if the product at the next stage is obtained by product refinement on the basis of the product at the current stage, when the reliability digital twin model of the product at the next stage is constructed, firstly, the product refinement information and the product characteristic information at the next stage are obtained, the reliability digital twin model at the current stage is refined and corrected according to the product refinement information and the product characteristic information, and the reliability digital twin model at the current stage is updated to obtain the reliability digital twin model at the next stage. It can be understood that the modeling process and method in the next-stage reliability digital twin model are similar to those in the above embodiments, and are not described herein again.

By using the method in the embodiment, under the condition that the product in the next stage is obtained by refining the product on the basis of the product in the previous stage, the reliability digital twin model in the current stage is refined and corrected on the basis of the product refining information and the product characteristic information in the next stage, so that the reliability digital twin model in the next stage can be quickly obtained. The construction speed of the digital twin model with reliability at the next stage is greatly accelerated, the workload of research and development personnel is reduced, and the research and development cost in the product research and development process is saved.

In one embodiment, as shown in fig. 6, a method for constructing a reliability digital twin model is provided, where the method is applied to a terminal device, and a database is provided on the terminal device, and the database stores an initial model to be used and related data to be used for constructing the reliability digital twin model in advance. The equipment is provided with CATIA, SolidWorks, Abaqus, ANSYS, Hypermesh and other related software.

Firstly, establishing an initial digital prototype model of the product, wherein the initial digital prototype model of the product is a digital model capable of reflecting geometric characteristics, physical characteristics and logical connection relations of all components in the product. Specifically, according to the three-dimensional geometric parameters of the product in the current development stage, researchers adopt three-dimensional modeling software such as CATIA (computer-aided three-dimensional Interactive application), SolidWorks and the like to establish a geometric characteristic model of the product; and establishing a product physical characteristic model by using finite element analysis software such as Abaqus, ANSYS, Hypermesh and the like according to the physical characteristics of the product. And establishing an initial prototype digital model of the product based on the product geometric characteristic model and the product physical characteristic model.

And then, analyzing and representing the reliability characteristics and behavior rules of the product by taking each component in the initial prototype digital model as a basic unit and taking the fault as a center, analyzing the occurrence of the product fault and a series of activities caused after the fault occurs in all aspects, including fault transmission, fault detection, fault maintenance and guarantee, system state change and the like, and establishing a reliability model of each component corresponding to each component according to the analysis result, wherein the reliability model of each component comprises a fault physics submodel, a fault transmission submodel, a failure state behavior submodel and a maintenance and guarantee strategy submodel. And associating each component reliability model with the corresponding component in the initial digital prototype model. Specifically, system interfaces of software used for building the fault sub-model, such as CATIA, Abaqus, ANSYS, Rhapside and the like, are opened by means of an informatization platform, a system engineering modeling language or a formal modeling language is used, each component reliability model is merged into an initial digital prototype model, and a product initial reliability digital twin-organism model merged with reliability elements is built. It can be understood that the fault physical model, the fault transmission model, the state behavior model and the maintenance and safeguard strategy model established by the method are all embedded into the product function, logic architecture or physical characteristic models of the corresponding stages, so that only the initial digital prototype model of the product can be seen in the surface form.

Acquiring actual measurement data obtained by actually measuring a product, and performing fault analysis on the actual measurement data corresponding to model input parameters in the initial reliability digital twin model by using the initial reliability digital twin model to obtain a model fault analysis result; and updating the initial reliability digital twin model by combining the model fault analysis result and the actually measured fault analysis result obtained by actual measurement to obtain the reliability digital twin model.

And finally, updating the reliability digital twin model at the current stage according to the product refinement information and the characteristic information at the next stage to obtain the reliability digital twin model at the next stage.

It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the application also provides a reliability digital twin model building device for realizing the reliability digital twin model building method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the reliability digital twin model construction device provided below can be referred to the limitations on the reliability digital twin model construction method in the above, and details are not repeated herein.

In one embodiment, as shown in fig. 7, there is provided a reliability digital twin model building apparatus 700, including: an initial digital prototype model obtaining module 701, an initial reliability digital twin model building module 702, a product measured data obtaining module 703, a model fault analysis result generating module 704 and a reliability digital twin model building module 705, wherein:

an initial digital prototype model obtaining module 701, configured to obtain an initial digital prototype model of the product.

An initial reliability digital twin model building module 702 is configured to determine a failure mode of each component in the initial digital prototype model, determine a component reliability model of each component based on the failure mode, and associate each component reliability model with a corresponding component in the initial digital prototype model to obtain an initial reliability digital twin model including each component reliability model.

The product measured data acquiring module 703 is configured to acquire actual measured data obtained by actually measuring a product.

And the model fault analysis result generation module 704 is used for performing fault analysis on actual measurement data corresponding to the model input parameters in the initial reliability digital twin model by using the initial reliability digital twin model to obtain a model fault analysis result.

And the reliability digital twin model constructing module 705 is configured to update the digital twin model according to the model fault analysis result and the actually measured fault analysis result obtained through actual measurement to obtain a reliability digital twin model.

The reliability digital twin model building device comprises the steps of firstly determining a fault mode of each component by taking each component in an initial digital prototype model of a product as a basic unit, determining a component reliability model of each component based on the fault mode, and associating the component reliability model of each component into the initial digital prototype model of the product, so as to obtain an initial reliability digital twin model containing the component reliability model of each component, and then updating the initial reliability digital twin model according to actually measured data generated by actually measuring the product, so as to obtain the reliability digital twin model. Because the digital twin model is constructed on the basis of the component reliability model of each component of the product during construction, the updated reliability digital twin model can accurately map all elements of the product by taking a fault as a center in the use process, truly reflect the reliability characteristics, behaviors and fault forming process of the product, evaluate the reliability of the product and meet the forward design work requirement of the product.

In one embodiment, the component reliability model includes a failure physics model; the initial reliability digital twin model building module 702 further comprises: determining a fault mechanism of each component, and acquiring an initial fault mechanism model corresponding to each fault mechanism based on each fault mechanism;

and determining a fault physical model of each component according to the historical operating data of each component and the initial fault mechanism model corresponding to the fault mechanism of each component.

In one embodiment, the component reliability model includes a fault propagation model; initial reliability digital twin model building module 702 further comprises: classifying failure behaviors occurring when internal components of each assembly fail, and determining failure types of the failure behaviors, wherein the failure types comprise assembly input failure, assembly self failure and assembly output failure;

In one embodiment, the component reliability model includes a failure state behavior model; the initial reliability digital twin model building 702 module further comprises: analyzing faults of the components to obtain fault generation reasons corresponding to the components;

and generating a failure state behavior model of each component based on the failure generation reason and the failure reduction control measure.

In one embodiment, the component reliability model includes a maintenance and assurance policy model; the initial reliability digital twin model building 702 module further comprises: acquiring corresponding maintenance information when each component fails; and generating a maintenance support strategy model of each component based on the maintenance information.

In one embodiment, the reliability digital twin model building module 705 further comprises: comparing the model fault analysis result with the actual measurement fault analysis result;

In one embodiment, the reliability digital twin model building apparatus further comprises: the next-stage reliability digital twin model building module is used for acquiring product refinement information and product characteristic information of the next stage of the product;

and updating the reliability digital twin model at the current stage according to the product refinement information and the product characteristic information to obtain the reliability digital twin model at the next stage.

The various modules in the above-mentioned reliability digital twin model building device can be realized in whole or in part by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, and the computer device may be a terminal device in the present application, and its internal structure diagram may be as shown in fig. 8. The computer device comprises a processor, a memory, a communication interface, a display screen and an input device which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile 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 an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of reliable digital twin model construction. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

acquiring an initial digital prototype model of a product;

determining a fault mode of each component in the initial digital prototype model, determining a component reliability model of each component based on the fault mode, and associating each component reliability model with the corresponding component in the initial digital prototype model to obtain a digital twin model containing each component reliability model;

acquiring actual measurement data obtained by actually measuring a product;

and updating the initial reliability digital twin model by combining the model fault analysis result and the actually measured fault analysis result obtained by actual measurement to obtain the reliability digital twin model.

In one embodiment, the processor, when executing the computer program, further performs the steps of:

the component reliability model comprises a failure physics model; determining a component reliability model for each component based on the failure modes, comprising:

the component reliability model comprises a fault delivery model; determining a component reliability model for each component based on the failure modes, comprising:

In one embodiment, the processor when executing the computer program further performs the steps of:

the component reliability model includes a failure state behavior model; determining a component reliability model for each component based on the failure modes, comprising:

analyzing faults of the components to obtain fault generation reasons corresponding to the components;

the component reliability model comprises a maintenance and guarantee strategy model; determining a component reliability model for each component based on the failure modes, comprising:

acquiring corresponding maintenance information when each component fails;

acquiring product refinement information and product characteristic information of a next stage of a product;

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

acquiring an initial digital prototype model of a product;

determining a fault mode of each component in the initial digital prototype model, determining a component reliability model of each component based on the fault mode, and associating each component reliability model with the corresponding component in the initial digital prototype model to obtain an initial reliability digital twin model containing each component reliability model;

acquiring actual measurement data obtained by actually measuring a product;

In one embodiment, the computer program when executed by the processor further performs the steps of:

the component reliability model comprises a failure state behavior model; determining a component reliability model for each component based on the failure modes, comprising:

acquiring corresponding maintenance information when each component fails;

In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:

acquiring an initial digital prototype model of a product;

acquiring actual measurement data obtained by actually measuring a product;

acquiring corresponding maintenance information when each component fails;

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for constructing a reliability digital twin model is characterized by comprising the following steps:

acquiring an initial digital prototype model of a product;

acquiring actual measurement data obtained by actually measuring the product;

2. The method of claim 1, wherein the component reliability model comprises a failure physics model;

3. The method of claim 1, wherein the component reliability model comprises a fault delivery model;

4. The method of claim 1, wherein the component reliability model comprises a failure state behavior model;

5. The method of claim 1, wherein the component reliability model comprises a maintenance assurance policy model;

acquiring corresponding maintenance information when each component fails;

6. The method according to any one of claims 1 to 5, wherein updating the initial reliability digital twin model in combination with the model fault analysis result and the actually measured fault analysis result obtained by actually measuring to obtain a reliability digital twin model comprises:

7. The method according to any one of claims 1 to 5, further comprising:

8. A reliability digital twin model building apparatus, comprising:

and the reliability digital twin model building module is used for updating the initial reliability digital twin model by combining the model fault analysis result and the actually-measured fault analysis result obtained by actual measurement to obtain a reliability digital twin model.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.