Digital twinborn model construction method for special vehicle equipment

Abstract

The invention discloses a digital twinborn model construction method for special vehicle equipment, and relates to the technical field of vehicle equipment safeguard, and the method comprises the steps: obtaining the physical environment information of an equipment object based on a sensor network disposed on the equipment object; constructing an equipment digital twin according to the physical environment information of the equipment object; the equipment digital twinning body comprises twinning body objects of all part units in all single machines at all moments within the set total service time, and all the twinning body objects comprise a geometric shape model, a mechanism characteristic model and a task behavior model; and adopting the equipment digital twin to monitor the geometric shape, mechanism characteristics and task behaviors of the equipment object in real time within the set total service time. According to the invention, the accuracy and timeliness of monitoring the running state of the vehicle equipment can be improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle equipment support technology, and in particular to a method for constructing a digital twin model for special vehicle equipment. Background Art

[0002] With the further development of informatization, vehicle equipment can play a huge role in rescue and other tasks. In tasks where the vehicle equipment is large in scale, the task time and space scope is wide, and the information changes rapidly, there are often problems such as harsh equipment living environment and complex support needs. At present, the vehicle equipment guarantee mode has problems such as opaque operating status, inaccurate fault tracing, and untimely operation and maintenance. It is urgent to improve the intelligence level of equipment operation and maintenance, enhance the precise execution of mission actions, and enhance the efficient coordination of support resources. Summary of the invention

[0003] The purpose of this application is to provide a method for constructing a digital twin model for special vehicle equipment, which can improve the accuracy and timeliness of monitoring the operating status of vehicle equipment.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] This application provides a method for constructing a digital twin model for special vehicle equipment, including:

[0006] Based on the sensor network arranged on the equipment object, the physical environment information of the equipment object is obtained;

[0007] Constructing a digital twin of equipment according to the physical environment information of the equipment object; the digital twin of equipment includes a twin object of each component unit in each single machine at each time within the set total service time, and each twin object includes a geometric shape model, a mechanism characteristic model and a task behavior model;

[0008] The digital twin of the equipment is used to monitor the geometric shape, mechanical characteristics and mission behavior of the equipment object in real time within the set total service time.

[0009] Optionally, the equipment digital twin is represented as:

[0010]

[0011] Among them, DT T represents the digital twin of the equipment, T represents the set total service time, J represents the number of component units, I represents the number of single machines, represents the twin object of the jth component unit in the i-th single machine at time t, and They respectively represent the geometric shape model, mechanism characteristic model and task behavior model of the j-th component unit in the ith single machine at time t.

[0012] Optionally, the geometric shape model includes geometric features, performance features and kinematic pairs of the component unit, the geometric features include holes, grooves and threads, the performance features include materials, tolerances and chamfers, and the kinematic pairs include rotational pairs, helical pairs and translation pairs.

[0013] Optionally, the equipment digital twin also includes a multi-body motion model of the equipment digital twin constructed according to the motion pairs of each component unit.

[0014] Optionally, constructing a multi-body motion model of the digital twin of the equipment according to the motion pairs of each component unit specifically includes:

[0015] According to the geometric characteristics and performance characteristics of the equipment object, the assembly relationship between each component unit and the constraint relationship between each component unit are established;

[0016] Define and reconstruct the rigid body and flexible body of each component unit, and define the physical properties of each component unit after reconstruction;

[0017] Assigning the assembly relationship, the constraint relationship and the physical characteristics of each component unit after reconstruction to the geometric model of the equipment object, and establishing a digital twin geometric model in a three-dimensional driving engine;

[0018] Kinematic features or dynamic features are added to the digital twin geometric model, the motion form of the equipment object is simulated and verified, and the digital twin geometric model that has passed the simulation verification is used as the multi-body motion model.

[0019] Optionally, the physical properties include stiffness, damping and coefficient of friction.

[0020] Optionally, the geometric model of the equipment object is a STEP format model.

[0021] Optionally, constructing a digital twin of the equipment according to the physical environment information of the equipment object specifically includes:

[0022] Determine the failure mode of each component unit in the digital twin of the equipment by using a failure mode impact and criticality analysis method;

[0023] Determining the failure phenomenon generated by each component unit in the equipment object according to the influence of the failure mode of each component unit on the equipment object;

[0024] Determine the failure mode of each component unit and the failure mechanism corresponding to each failure mode according to the failure phenomenon of each component unit;

[0025] The mechanism characteristic model of each component unit is constructed according to the failure mode, the failure phenomenon and the failure mechanism of each component unit.

[0026] Optionally, the equipment digital twin also includes the correlation between the failure mode of each single machine and the failure mechanism of each component unit in the single machine.

[0027] Optionally, the task behavior model includes task behavior and dynamic state behavior during the execution of the task behavior, the task behavior is represented by a process sequence, and the dynamic state behavior is used to map the behavior state of the equipment object in real time based on physical environment information collected by the sensor network.

[0028] According to the specific embodiments provided in the present application, the present application discloses the following technical effects: the present application provides a method for constructing a digital twin model for special vehicle equipment, and constructs a digital twin of the equipment according to the physical environment information of the equipment object; the digital twin of the equipment includes the twin objects of each component unit in each single machine at each moment within the set total service time, and each twin object includes a geometric shape model, a mechanism characteristic model and a task behavior model. The geometric shape, mechanism characteristics and task behavior of the equipment object are monitored in real time through the digital twin of the equipment, so as to realize the monitoring of the equipment object in three dimensions of geometric shape, mechanism characteristics and task behavior, thereby improving the accuracy of equipment status monitoring, and improving the timeliness of equipment status monitoring through the synchronization between the digital twin of the equipment and the equipment object. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 A flowchart of a method for constructing a digital twin model for special vehicle equipment provided in one embodiment of the present application.

[0031] Figure 2 A schematic diagram of the overall architecture of a method for constructing a digital twin model for special vehicle equipment provided in one embodiment of the present application.

[0032] Figure 3 A schematic diagram of the modeling principle of a geometric shape provided in one embodiment of the present application.

[0033] Figure 4 A schematic diagram of the geometric shape modeling process provided in one embodiment of the present application.

[0034] Figure 5 A schematic diagram of the mechanism characteristic modeling process provided in one embodiment of the present application.

[0035] Figure 6 A schematic diagram of the equipment status behavior modeling process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0037] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0038] This application provides a method for constructing a digital twin model for special vehicle equipment, such as Figure 1 As shown, the method for constructing a digital twin model for special vehicle equipment includes steps 101 to 103.

[0039] Step 101: Based on a sensor network arranged on the equipment object, obtain physical environment information of the equipment object.

[0040] Physical environment information includes information such as the vehicle's overall acceleration and speed, as well as status monitoring information of internal components such as the vehicle's engine and gearbox.

[0041] Step 102: Construct a digital twin of equipment based on the physical environment information of the equipment object; the digital twin of the equipment includes a twin object of each component unit in each single machine at each moment within the set total service time, and each twin object includes a geometric shape model, a mechanism characteristic model and a task behavior model.

[0042] Step 103: Use the digital twin of the equipment to monitor the geometric shape, mechanical characteristics and task behavior of the equipment object in real time within the set total service time.

[0043] Starting from the intelligent support needs of equipment, this application uses digital twin technology to build the "physical life form" of weapons and equipment, and conducts modeling from the three dimensions of the appearance, characteristics and behavior of the "life form" to achieve appearance synchronization, characteristic restoration and task accompaniment in the equipment operation and maintenance process. With the help of the twin, the equipment status is perceived, the potential support needs of the equipment are identified, and the various support needs are correlated and matched and judged in combination with the decision-making knowledge base accumulated by the system. By calculating the relevance between the needs and knowledge, the support decision plan to be selected under the corresponding state is determined, and then pushed to the support personnel, and the support personnel are quickly pushed to perform the support task action, providing technical support for the equipment to perform the task support.

[0044] The technical solution of this application mainly involves three aspects: equipment physical entity, equipment digital twin and intelligent operation and maintenance services, such as Figure 2 shown.

[0045] (1) Equipment objects are physical entities. They are composed of physical objects at all levels. Through direct or indirect interactions, they execute their own control instructions and complete actual tasks. Therefore, equipment physical entities refer to equipment objects and their task processes in the physical world. By deploying sensor networks on equipment objects, physical equipment and physical environment information is obtained and transmitted to the digital space through the equipment's own communication bus, thereby ensuring that changes in physical equipment objects can be received in the twin environment.

[0046] (2) Equipment digital twin. In order to realize the interactive linkage and mutual complementation between the digital twin and the physical entity during the operation and maintenance process, the modeling of equipment digital twin mainly considers the three dimensions of "appearance", "characteristics" and "behavior".

[0047] "Appearance" modeling is used to express the size, structure, position, posture and movement process of equipment, and can support the visual expression of the equipment operation process.

[0048] "Characteristic" modeling is aimed at failure problems in the operation and maintenance process, analyzing their failure modes, clarifying the failure mechanisms, and quantitatively describing the inherent mechanisms such as twin degradation and failure through the fault physics model, providing a basis for the intelligent operation and maintenance services of the twin environment.

[0049] "Behavior" modeling is aimed at the dynamic mapping and synchronization of the physical equipment entity behavior of the twin. The study summarizes the behavioral modeling of the digital twin into two aspects: from a macro perspective, equipment behavior refers to the task process of the equipment operation and maintenance process, such as disassembly and assembly process, replacement process, testing process, etc.; from a micro perspective, behavioral modeling refers to the real-time monitorable behavior of components under different working conditions, such as vibration, speed, etc.

[0050] (3) Intelligent operation and maintenance services: Based on the equipment operation and maintenance digital twin, develop an equipment intelligent operation and maintenance guarantee system. Based on the virtual-reality mapping, digital-analog fusion, knowledge integration and other capabilities of the digital twin, provide status monitoring, fault diagnosis, strategy push and health assessment services for the equipment use and operation and maintenance process, and encapsulate them into various interrelated and coordinated functional components, application software and mobile terminals, etc., to support the formation of equipment intelligent operation and maintenance capabilities.

[0051] This application integrates the constructed digital twin with the equipment operation and maintenance process. Taking the maintenance and support process of special vehicle equipment as an example, various equipment operation and maintenance events are used to drive the update and iteration of the twin's "shape, property, and behavior" status.

[0052] Digital twins can replicate, simulate, and integrate the properties, mechanisms, behaviors, functions, and other elements of physical systems. The first step is to establish a highly reliable model with consistent properties. Generally speaking, establishing a digital twin of equipment with high integrity, high precision, and high reliability is an extremely complex system engineering. Therefore, this paper establishes a digital twin of equipment for the specific needs of intelligent operation and maintenance of equipment. It not only considers the overall operation and maintenance status information of the equipment, but also further decomposes the complex structural composition of the equipment, focusing on component units with high failure frequency or long average failure downtime. The digital twin of the equipment is divided according to the equipment structure hierarchy, and the twin modeling of the component level, single machine level, and equipment level is carried out layer by layer.

[0053] In an exemplary embodiment, assume that an equipment object contains I single machines i∈{1,2,...,I}, and the number of parts contained in a single machine is J, j∈{1,2,...,J}, and the total service time of the equipment twin with the equipment is T, t∈{1,2,...,T}, then Represents the twin object of the jth component unit in the i-th single machine at time t, then there is the equipment digital twin DT T Covers the main operation and maintenance status information of the equipment during its service.

[0054] The equipment digital twin is represented as:

[0055] in, It can also include the geometric shape of the unit-level twin object at time t during its service life Mechanism characteristics Task Behavior

[0056] Among them, DT T represents the digital twin of the equipment, T represents the set total service time, J represents the number of component units, I represents the number of single machines, represents the twin object of the jth component unit in the i-th single machine at time t, and They respectively represent the geometric shape model, mechanism characteristic model and task behavior model of the j-th component unit in the ith single machine at time t. Represents the conceptual model of equipment twins for intelligent operation and maintenance.

[0057] The principle of geometric shape modeling is as follows Figure 3 As shown in the figure, the geometric shape model is a visual field expression of the geometric structure and multi-body motion of the equipment. The geometric model and multi-body motion model are used to express the mechanical assembly structure and motion relationship of the twin model. According to the assembly structure organization form of the equipment, the geometric shape and multi-body motion model of the component unit level, single machine level and equipment level is constructed in a bottom-up manner.

[0058] In the twin modeling environment, standard parts such as bearings and bolts are imported from the aerospace general standard parts library, and customized parts are imported from the three-dimensional models provided by the corresponding research and development units, and geometric parameters such as stretching, rotation, scanning, and array are defined. Three aspects are mainly considered in component-level appearance modeling, namely geometric features, performance features, and kinematic pairs. That is, the geometric appearance model includes the geometric features, performance features, and kinematic pairs of the component unit, the geometric features include holes, grooves, and threads, the performance features include materials, tolerances, and chamfers, and the kinematic pairs include rotational pairs, helical pairs, and translation pairs.

[0059] The geometric shape model of the component unit is expressed as

[0060] Among them, Ge i,j Mp represents the geometric characteristics of the jth component unit in the i-th single machine. i,j represents the performance characteristics of the jth component unit in the i-th single machine, Represents the kinematic pair of the jth component unit in the i-th single machine at time t.

[0061] against The corresponding assembly features covered (such as surface overlap, coaxiality, parallelism, distance, tangency, etc.) realize the assembly of component units at the model level, and gradually accumulate to form a single-machine-level appearance model. With equipment-level appearance model Sh t. Generally speaking, the geometric model of the equipment in the detailed design stage has been fully constructed by 3D modeling software. In the process of twin construction, the 3D model is loaded in Unity and UE4 visual driver engine through the STEP model interaction standard, and the model is reloaded by calling the program script. The boundary details of the object are described by the combination of unified boundary representation and CSG (Constructive Solid Geometry) to achieve accurate modeling of complex shapes. At the same time, the hybrid method of constructive solid geometry is used to realize the fusion of data structure and model, and the data structure is realized by custom scripts or the scalable data storage mechanism of the engine is used to realize model reconstruction.

[0062] Since the twin body needs to complete the mapping of the appearance and motion level for the physical object, in order to accurately reflect the motion characteristics and motion process of the equipment itself, it is necessary to further Features complete the multi-body motion modeling and simulation of the twin body. The digital twin process is as follows Figure 4 shown.

[0063] The equipment digital twin also includes a multi-body motion model of the equipment digital twin constructed according to the motion pairs of each component unit.

[0064] In an exemplary embodiment, Figure 4 As shown in Figure 2, the construction of the multi-body motion model specifically includes the following steps:

[0065] 1) According to the geometric characteristics and performance characteristics of the equipment object, the assembly relationship between each component unit and the constraint relationship between each component unit are established, the relevant entities, joints and constraint relationships of the geometric shape model of each component unit are clarified, and the forces, torques and loads acting between different units or at the joints are analyzed. The geometric model of the equipment object is a STEP format model.

[0066] 2) Construction and connection of rigid-flexible coupled multi-body models: Define and reconstruct the rigid and flexible bodies of each component unit, modify and add key components after model drive settings and motion simulation and when the multi-body model verification results do not meet the actual situation, and define the physical properties of each component unit after reconstruction. The physical properties include stiffness, damping and friction coefficient.

[0067] 3) Assigning the assembly relationship, the constraint relationship and the physical properties of each component unit after reconstruction to the geometric model of the equipment object, and establishing a digital twin geometric model in the three-dimensional driving engine, specifically including: taking over the constructed STEP format model and assembly constraint relationship, and establishing a digital twin geometric model in the three-dimensional driving engine.

[0068] 4) Add kinematic features or dynamic features to the digital twin geometric model in the twin modeling environment to truly reflect the actual connection relationship between the various components of the equipment, and select the corresponding solver to solve and simulate various key motion forms of the model, and output time series data such as force, torque, displacement, velocity, acceleration, etc.

[0069] 5) The motion form of the equipment object is simulated and verified, and the digital twin geometric model verified by simulation is used as the multi-body motion model, specifically including: if a kinematic simulation of a vehicle is implemented during an exercise mission, a kinematic model of the vehicle needs to be established, and parameters such as the vehicle speed, steering angle, and endurance need to be considered. Assuming that the vehicle is traveling on a flat road, the steering motion of the vehicle is described according to the Ackerman steering geometry principle. According to the specific geometric relationship between the front and rear wheels, straight-line and turning simulations are performed. The position and posture of the vehicle at each moment are obtained over time, and whether it is reasonable is determined based on the analysis of the changes. When the result does not meet the theoretical calculation, the connection relationship, physical properties, material parameters, and rigid-flexible body settings are modified in the twin modeling environment; when the verification result is met, the construction of the twin multi-body motion model is completed.

[0070] Mechanistic Characteristic Model It is an expression of the inherent mechanism characteristics such as degradation and failure that occur during the use of equipment. In the equipment operation and maintenance process, the equipment intelligent operation and maintenance digital twin can be used as a "container" for the accumulation of fault modes and fault mechanisms, and the qualitative analysis of fault modes, identification of fault mechanisms and quantitative results are solidified in the twin. Combined with the understanding of the fault problems in the historical use of equipment, a fault physical model is established to achieve a qualitative description of the fault mode and a quantitative solution of the fault mechanism, and an explicit expression of the association between the fault mode and the mechanism is established in the intelligent operation and maintenance twin model.

[0071] In an exemplary embodiment, the construction of the mechanism characteristic model specifically includes: determining the failure mode of each component unit in the digital twin of the equipment using a failure mode impact and criticality analysis method; determining the failure phenomenon generated by each component unit in the equipment object based on the impact of the failure mode of each component unit on the equipment object; determining the failure mode generated by each component unit and the failure mechanism corresponding to each failure mode based on the failure phenomenon generated by each component unit; and constructing the mechanism characteristic model of each component unit based on the failure mode, the failure phenomenon and the failure mechanism of each component unit.

[0072] The mechanism characteristic model is expressed as:

[0073] in, and are the first jThe failure phenomenon, failure mode and failure mechanism of each component unit at time t.

[0074] 1) Qualitative analysis of failure modes.

[0075] The digital twin needs to accurately express the comprehensive impact of various failure modes on the use and function of the equipment. Due to the complexity of the equipment's own functions, composition structure and working principle, the failure mode effects and criticality analysis method (FMECA) is generally used for weapons and equipment to determine the possible failure modes of each unit in the system. Finally, analyze its impact on the system and related fault phenomena from bottom to top So as to carry out targeted treatment.

[0076] The qualitative analysis process for equipment failure modes is as follows: Figure 5 First, it is necessary to collect relevant information about weapons and equipment, conduct in-depth analysis and clarify their life profile, mission profile and environmental profile, and clarify the failure phenomena of different units according to the agreed level, function and mission type of weapons and equipment. The failure criteria and severity are defined, and then the failure modes of the system as a whole, each unit and component are analyzed separately. Analysis, failure mode impact analysis, failure mechanism and influencing factor analysis, and finally sort out the key failure modes and their corresponding failure mechanisms

[0077] The equipment digital twin also includes the correlation between the failure mode of each single machine and the failure mechanism of each component unit in the single machine.

[0078] 2) Fault mechanism identification.

[0079] Taking a certain type of equipment system as an example, the equipment units mainly include three types: structural products (such as cabin, rudder, heat protection cover, etc.), electromechanical products (such as steering gear, etc.) and electronic products (such as inertial navigation, computer, etc.). Combining the historical fault mode and mechanism identification structure, the equipment mechanism characteristic twin model constructed covers the fault mode and mechanism association The association between various failure modes and failure mechanisms is shown in Tables 1 to 3. Indicates i Single machine t Failure mode at the moment.

[0080] Table 1 Correlation table between structural failure modes and failure mechanisms

[0081]

[0082] Table 2 Correlation table between electromechanical failure modes and failure mechanisms

[0083]

[0084]

[0085] Table 3 Correlation table between electronic failure modes and failure mechanisms

[0086]

[0087] In an exemplary embodiment, the task behavior model includes task behavior and dynamic state behavior in the process of executing the task behavior, wherein the task behavior is represented by a process sequence, and the dynamic state behavior is used to map the behavior state of the equipment object in real time based on the physical environment information collected by the sensor network. On the one hand, from the perspective of the task process, the task behavior model describes the operating state behavior of different component units of the equipment at different times in accordance with the predetermined process sequence.

[0088] The task behavior model is expressed as: Among them, t Indicates the mission behavior performed by the equipment, including the specific use process in equipment training, technical preparation, transportation and withdrawal. Represents the dynamic state behavior of equipment components and units during mission behavior.

[0089] 1) Task “Behavior”.

[0090] The digital twin of equipment for intelligent operation and maintenance mainly models task behaviors through process definition. t It is to model the detailed process sequence, which can be expressed as: Ta t = <ta 1 ,ta 2 ,...,ta n >. Among them, k represents the kth task behavior, n is the number of task behaviors, 1≤k≤n.

[0091] Generally speaking, the types of equipment operation and maintenance support tasks mainly include technical preparation support and maintenance and repair support. The specific operation and maintenance tasks have completed the process definition in the equipment support design process. Taking the test support process of a certain type of equipment as an example, it mainly goes through task processes such as power-on self-test, plug-in and unplug connection, test status preparation, subsystem testing, and general inspection testing.

[0092] 2) State "behavior".

[0093] Status "Behavior" It is an expression of the real-time operating status of the equipment during the operation and maintenance mission, while the sensor monitoring data is the most objective description of the equipment's behavior status, because the dynamic synchronization of physical equipment and twin equipment can be achieved through real-time mapping of status data. The status of equipment changes over time during the execution of the task, and the status changes of different units and components are not consistent. Single equipment changes at different times t, different units i and components (component units) j, and in different task conditions ta k The data structure collected below has typical spatiotemporal characteristics.

[0094] In order to ensure the consistency of product dimensional twins, according to the division of component level, single machine level and equipment level, an equipment status behavior data organization and modeling technology based on spatiotemporal data model is proposed.

[0095] Among them, St T To set the dynamic state behavior within the total service time.

[0096] The physical state changes corresponding to the equipment are described through a unified data model, and the data is updated and synchronized in each node of the constructed twin object, thereby driving the update and synchronization of the twin state with the actual physical state, such as Figure 6 As shown, Figure 6 It includes three monitoring points, namely, one-axis monitoring point, two-axis monitoring point and three-axis monitoring point. Each monitoring point monitors four monitoring moments, namely, t 1 ,t 2 ,t 3 and t 4 The monitoring information of the first-axis monitoring point at each monitoring moment includes parameters such as the temperature, particle concentration, vibration and oil pressure of components such as the exhaust manifold, supercharger, converter and muffler; the monitoring information of the second-axis monitoring point at each monitoring moment includes parameters such as the temperature, pressure, noise and oil pressure of components such as the cylinder head, cylinder block, combustion chamber and piston; the monitoring information of the second-axis monitoring point at each monitoring moment includes parameters such as the temperature, hydraulic pressure and remaining amount of the water jacket, water pump, fan and water tank.

[0097] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0098] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for constructing a digital twin model for special vehicle equipment, characterized in that: The method for constructing a digital twin model for special vehicle equipment includes: Based on the sensor network arranged on the equipment object, the physical environment information of the equipment object is obtained; Constructing a digital twin of equipment according to the physical environment information of the equipment object; the digital twin of equipment includes a twin object of each component unit in each single machine at each time within a set total service time, and each twin object includes a geometric shape model, a mechanism characteristic model and a task behavior model; The digital twin of the equipment is used to monitor the geometric shape, mechanical characteristics and mission behavior of the equipment object in real time within the set total service time.

2. The method for constructing a digital twin model for special vehicle equipment according to claim 1, characterized in that: The equipment digital twin is represented as: Among them, DT T represents the digital twin of the equipment, T represents the set total service time, J represents the number of component units, I represents the number of single machines, represents the twin object of the jth component unit in the i-th single machine at time t, and They respectively represent the geometric shape model, mechanism characteristic model and task behavior model of the j-th component unit in the ith single machine at time t.

3. The method for constructing a digital twin model for special vehicle equipment according to claim 2, characterized in that: The geometric shape model includes the geometric features, performance features and kinematic pairs of the component unit, the geometric features include holes, grooves and threads, the performance features include materials, tolerances and chamfers, and the kinematic pairs include rotational pairs, helical pairs and translation pairs.

4. The method for constructing a digital twin model for special vehicle equipment according to claim 3, characterized in that: The equipment digital twin also includes a multi-body motion model of the equipment digital twin constructed according to the motion pairs of each component unit.

5. The method for constructing a digital twin model for special vehicle equipment according to claim 4, characterized in that: The multi-body motion model of the equipment digital twin is constructed according to the motion pairs of each component unit, specifically including: According to the geometric characteristics and performance characteristics of the equipment object, the assembly relationship between each component unit and the constraint relationship between each component unit are established; Define and reconstruct the rigid body and flexible body of each component unit, and define the physical properties of each component unit after reconstruction; Assigning the assembly relationship, the constraint relationship and the physical characteristics of each component unit after reconstruction to the geometric model of the equipment object, and establishing a digital twin geometric model in a three-dimensional driving engine; Kinematic features or dynamic features are added to the digital twin geometric model, the motion form of the equipment object is simulated and verified, and the digital twin geometric model that has passed the simulation verification is used as the multi-body motion model.

6. The method for constructing a digital twin model for special vehicle equipment according to claim 5, characterized in that: The physical properties include stiffness, damping and coefficient of friction.

7. The method for constructing a digital twin model for special vehicle equipment according to claim 5, characterized in that: The geometric model of the equipment object is a STEP format model.

8. The method for constructing a digital twin model for special vehicle equipment according to claim 2, characterized in that: Building a digital twin of the equipment according to the physical environment information of the equipment object specifically includes: Determine the failure mode of each component unit in the digital twin of the equipment by using a failure mode impact and criticality analysis method; Determining the failure phenomenon generated by each component unit in the equipment object according to the influence of the failure mode of each component unit on the equipment object; Determine the failure mode of each component unit and the failure mechanism corresponding to each failure mode according to the failure phenomenon of each component unit; The mechanism characteristic model of each component unit is constructed according to the failure mode, the failure phenomenon and the failure mechanism of each component unit.

9. The method for constructing a digital twin model for special vehicle equipment according to claim 8, characterized in that: The equipment digital twin also includes the correlation between the failure mode of each single machine and the failure mechanism of each component unit in the single machine.

10. The method for constructing a digital twin model for special vehicle equipment according to claim 2, characterized in that: The task behavior model includes task behavior and dynamic state behavior in the process of executing the task behavior. The task behavior is represented by a process sequence, and the dynamic state behavior is used to map the behavior state of the equipment object in real time based on the physical environment information collected by the sensor network.

Images