CN116243670A - Digital twinning-based electromechanical product assembly process dynamic model construction method - Google Patents
Digital twinning-based electromechanical product assembly process dynamic model construction method Download PDFInfo
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Abstract
The invention discloses a dynamic model construction method for an electromechanical product assembly process based on digital twinning, and relates to the field of digital twinning. According to the invention, the self-growth process of the reference tree analyzes the final assembly production mode of the complex electromechanical product from the dimensions of working procedures, production behaviors, production factors and data, analyzes the evolution process of mass data in the final assembly process of the complex electromechanical product, fully describes the final assembly process of the complex electromechanical product, provides data support for digital twin model driving, is beneficial to virtual-real mapping and subsequent data storage analysis, and facilitates the digital management of the final assembly production line of the complex electromechanical product.
Description
Technical Field
The invention relates to the technical field of digital twinning, in particular to a method for constructing a dynamic model of an electromechanical product assembly process based on digital twinning.
Background
The digital twin technology aims at mapping the whole life cycle of physical entities in the real world in a virtual space in a digital mode, describing the attribute characteristics such as behaviors, rules and the like, carrying out production scheduling simulation by utilizing the collected real-time data, and supporting the accelerated transformation of the manufacturing industry to intelligence and digitization. The model and data dual drive is the basis for implementing digital twin technology landing.
The assembly process of the complex electromechanical product is a complex structure body integrating multiple dimensions, multiple fields, multiple technologies and multiple devices, the assembly environment, the assembly flow and the process are relatively complex, and different stations and procedures correspond to different devices, resources and processes. From the production and manufacturing level, the existing digital twin model construction method is mostly concentrated on single-layer secondary production elements such as people, machines, objects, production lines and the like, so that the attribute characteristics of physical entities are difficult to comprehensively and accurately describe from the aspects of multiple fields and disciplines. Although there is also a global systematic digital twin model construction method, the granularity division is not fine enough and lacks the actual contrast effect, and it is difficult to fully describe the actual production process.
Disclosure of Invention
The invention aims to solve the technical problems that: the method for constructing the dynamic model of the assembly process of the electromechanical product based on digital twinning is provided to overcome the defects of the prior art. The method can fully describe the final assembly process of the complex electromechanical product, provide data support for the digital twin model drive, facilitate the subsequent data storage and analysis, and improve the rationality and the high efficiency of the development of the corresponding digital twin model.
The invention solves the technical problems by adopting the following technical scheme:
a method for constructing a dynamic model of an electromechanical product assembly process based on digital twinning comprises the following steps:
step 1, analyzing actual characteristics of the electromechanical product assembly process, and building formal expressions related to the electromechanical product assembly process on the basis of working procedures around the assembly characteristics and the process flow;
step 2, regarding the working procedure as a combination of a plurality of production behaviors, determining a logic relation among the production behaviors under the working procedure, and establishing a formal expression related to the assembly working procedure;
step 3, determining associated production elements based on production behaviors in each procedure in the final assembly process of the electromechanical product, establishing data source nodes with different granularities, determining the logic relationship of the data source nodes, and further advancing modeling work;
step 4, determining data information contained in each production element data source node, and establishing a formal expression related to the production element data source node;
and step 5, associating and corresponding the electromechanical product assembly process with the tree self-growth process, and expressing the relation among the electromechanical product assembly flow, the procedure, the production behavior, the production element data source node and the data value by using the tree self-growth logic.
Compared with the prior art, the invention has the remarkable advantages that:
according to the invention, the self-growth process of the reference tree analyzes the production mode of the final assembly of the complex electromechanical product from the dimensions of working procedures, production behaviors, production factors and data, analyzes the evolution process of mass data in the final assembly process of the complex electromechanical product, is beneficial to virtual-real mapping and subsequent data storage analysis, and facilitates the digital management of the final assembly line of the complex electromechanical product.
Drawings
FIG. 1 is a schematic diagram of a dynamic model of a self-growing tree-based assembly process of a complex electromechanical product according to the present invention
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention relates to a method for constructing a dynamic model of a final assembly process of a complex electromechanical product based on digital twinning. The method comprises the following steps:
and 1, analyzing actual characteristics of the assembly process of the complex electromechanical product, and building a formal expression related to the assembly process of the complex electromechanical product on the basis of working procedures around the assembly characteristics and the process flow.
The complex electromechanical product assembly process can be formally characterized as:
wherein RAP is i Representing the general assembly flow of a complex electromechanical product, comprising K procedures in total, wherein AP i,k Representing the kth procedure in the final assembly flow of the complex electromechanical product, and a matrix R AP Representing the logical relationship existing between the assembly processes, R AP (a, b) represents matrix R AP The values of the elements in row a and column b include an unconnected (∈) and a serial orderRelationship (≡).
And 2, based on the step 1, the process is regarded as a combination of a plurality of production behaviors, the logic relation among the production behaviors under the process is determined, and a formal expression related to the process is established.
The assembly process may be formally characterized as:
in the formula, AA i,k,l Representing the first production behavior under the kth procedure (such as clamping jaw tool clamping workpiece, transplanting tool clamping tray, screw machine feeding and the like under the assembly procedure of the array panel in the assembly process of a certain radar product), and totally comprising L production behaviors, wherein a matrix R AA Representing the logical relationship existing between the production behaviors, R AA (c, d) represents matrix R AA The values of the elements in the c rows and d columns include an unconnected (∈), a serial sequential relationship (∈), and a parallel relationship (→). The parallel relationship means that different production behaviors are performed concurrently at the same time in a certain process, for example, in the process of assembling a radar product, the filter assembly and the TR assembly in the process of assembling the array plane electromechanical hybrid assembly are performed simultaneously. The serial sequence relation represents that different production behaviors are sequentially carried out according to logic, for example, in the high-frequency box splicing process of the assembly of a certain radar product, the splicing and the leveling of the side block high-frequency box can be carried out only after the leveling of the middle block high-frequency box is finished.
And 3, on the basis of the step 2, determining production elements related to the production elements based on production behaviors of the complex electromechanical product in each procedure in the final assembly process, establishing data source nodes with different granularities, determining the logic relationship of the data source nodes, and further advancing modeling work.
The production behaviour can be formally characterized as:
in DS i,k,l,m Representing an mth production element data source node associated with an mth production act at a kth process, comprising a total of M production element source nodes, wherein the matrix R DS Representing the logical relationship existing between the data source nodes of each production element, R DS (e, f) represents matrix R DS The values of the elements in e rows and f columns include an unconnected (∈), a parallel relationship (→) and a subordinate relationship
When a data source node of a certain production element cannot accurately describe or map a corresponding production behavior, the production element can be divided into sub-components with smaller granularity according to the composition structure of the production element, and then the corresponding data source node is acquired, so that each production behavior can be accurately described or mapped. For example, when mapping the assembly behaviors of an industrial robot, a single industrial robot data source node is difficult to describe the whole assembly behaviors, and the industrial robot data source node needs to be subdivided into a plurality of secondary production element data source nodes such as 1-6 axis nodes, screw machine nodes, press-fit cylinder nodes and the like of the industrial robot, so that the perception and integration of the whole industrial robot overall data are further realized. Wherein, the source nodes of the production elements which are subdivided into the same level belong to parallel relations, and the source nodes of the secondary production element data can be further subdivided until the requirements are met.
And 4, on the basis of the step 3, determining data information contained in each production element data source node, and establishing a formal expression related to the production element data source node.
The production element data source node may be formally modeled as:
in DV i,k,l,m Represents an mth production element data source node DS associated with an mth production act at a kth process i,k,l,m In which DV is a time-invariant data ID Representing the identity number DV of the production element under the digital twin model of the complex electromechanical product final assembly line TY Specific category information representing the production element, DV AT Attribute information representing the production element (such as an axis working range of the industrial robot and the like),
representing the source node DS of the production element data i,k,l,m At t p A data value of the time of day.
And 5, on the basis of the steps, associating and corresponding the assembly process of the complex electromechanical product with the tree self-growth process, and expressing the relationship among the assembly flow, the working procedure, the production behavior, the production element data source node and the data value of the complex electromechanical product by using the tree self-growth logic. The tree trunks correspond to the complex electromechanical product assembly flow, the branches correspond to working procedures included in the complex electromechanical product assembly flow, the branches correspond to production behaviors under all working procedures, the branches correspond to data source nodes of all production elements under the production behaviors, and the leaves correspond to data values under the data source nodes.
Modeling process based on the steps, RAP is performed i As the trunk of the self-growing tree, the growth process of the trunk from bottom to top represents the assembly process of the complex electromechanical product; AP (Access Point) i,k The crotch of the self-growing tree represents the working procedure in the assembly process of the complex electromechanical product, the growth process of the crotch is embodied in that the working procedure is changed continuously along with the time migration, the former working procedure in the assembly process is added continuously after the former working procedure is finished, namely, the RAP is collected i The internal elements are continuously increased, fromAP i,k Evolved into AP i,1 ,…,AP i,k ,…AP i,K Is a process of (1); AA (AA) i,k,l The tree branch represents the production behavior under the assembly process, the growth process of the tree branch is similar to that of a crotch, the production behavior is changed continuously along with the migration of time, and a new production behavior is added after the execution of the current behavior is finished until all the processes are finished, namely the assembly { AA } i,k,1 ,…,AA i,k,l ,…,AA i,k,L An extension process from none to some; DS (DS) i,k,l,m For branches of self-growing tree, representing production element data source nodes associated with production behaviors, the data source nodes are increased continuously along with time migration change, namely the set { DS } i,k,l,1 ,…,DS i,k,l,m ,…,DS i,k,l,M The expansion process of the data source nodes of each production element is divided into finer data source nodes, namely DS according to the requirement i,k,l,m Evolving into a set { DS ] i,k,l,m,1 ,…,DS i,k,l,m,n ,…,DS i,k,l,M,N Process of }.
The tree leaves of the self-growing tree represent the production element data source nodes at t p The growth process of the leaf can be embodied as that the data value of the data source node is continuously increased along with the migration of time, and the DS is integrated i,k,l,m The elements of (2) are from->
Expansion to
Is a process of (2).
FIG. 1 is a schematic diagram of a dynamic model of the assembly process of a complex electromechanical product based on self-growing trees, illustrating a radar product of a certain type as an example, wherein RAP i For a certain radar assembly flow, AP i,1 For the first process, i.e. the assembly process of the array panel, AA i,1,1 For the first production action in the process, namely tray feeding action, DS i,1,1,1 For the first generation associated with the actionThe production element data source node is the elevator data source node,
at t for the data source node of the hoister 1 Data value of time of day->
At t for the data source node of the hoister 2 Data value, DS of time of day i,1,1,2 For the second production element data source node associated with the action, namely the transplanting fixture data source node,/->
For transplanting the frock data source node at t 1 Data value of time of day->
For transplanting the frock data source node at t 2 A data value of the time of day. />
Claims (7)
1. The method for constructing the dynamic model of the assembly process of the electromechanical product based on digital twinning is characterized by comprising the following steps of:
step 1, analyzing actual characteristics of the electromechanical product assembly process, and building formal expressions related to the electromechanical product assembly process on the basis of working procedures around the assembly characteristics and the process flow;
step 2, regarding the working procedure as a combination of a plurality of production behaviors, determining a logic relation among the production behaviors under the working procedure, and establishing a formal expression related to the assembly working procedure;
step 3, determining associated production elements based on production behaviors in each procedure in the final assembly process of the electromechanical product, establishing data source nodes with different granularities, determining the logic relationship of the data source nodes, and further advancing modeling work;
step 4, determining data information contained in each production element data source node, and establishing a formal expression related to the production element data source node;
and step 5, associating and corresponding the electromechanical product assembly process with the tree self-growth process, and expressing the relation among the electromechanical product assembly flow, the procedure, the production behavior, the production element data source node and the data value by using the tree self-growth logic.
2. The method for constructing a dynamic model of an electromechanical product assembly process based on digital twinning according to claim 1, wherein the electromechanical product assembly process is formally characterized as follows:
wherein RAP is i Representing the general assembly flow of the electromechanical product, comprises K working procedures in total, wherein AP i,k Representing the kth procedure in the final assembly flow of the electromechanical product, and the matrix R AP Representing the logical relationship existing between the assembly processes, R AP (a, b) represents matrix R AP The values of the elements in row a and column b include an unconnected (∈) and a serial sequential relationship (∈).
3. The method for constructing a dynamic model of the assembly process of the electromechanical product based on digital twinning according to claim 1, wherein the formal expression of the assembly process is:
in AP i,k Representing the total flow of the electromechanical productKth procedure in procedure, AA i,k,l Representing the first production behavior under the kth procedure, comprising L production behaviors in total, wherein the matrix R AA Representing the logical relationship existing between the production behaviors, R AA (c, d) represents matrix R AA The values of the elements in the c rows and d columns include an unconnected (∈), a serial sequential relationship (∈), and a parallel relationship (→).
4. The method for constructing a dynamic model of the assembly process of the electromechanical product based on digital twinning according to claim 1, wherein the production behavior is formally characterized as follows:
in the formula, AA i,k,l Representing the first production behavior under the kth procedure, DS i,k,l,m Representing an mth production element data source node associated with an mth production act at a kth process, comprising a total of M production element source nodes, wherein the matrix R DS Representing the logical relationship existing between the data source nodes of each production element, R DS (e, f) represents matrix R DS The values of the elements in e rows and f columns include an unconnected (∈), a parallel relationship (→) and a subordinate relationship
5. The method for constructing the dynamic model of the assembly process of the electromechanical product based on the digital twin according to claim 1, wherein the formalized expression of the production element data source node is as follows:
in DS i,k,l,m Data source node representing mth production element associated with kth production action in kth process, DV i,k,l,m Represents an mth production element data source node DS associated with an mth production act at a kth process i,k,l,m Data not changing with time, DV ID Representing the identity number DV of the production element under the digital twin model of the electromechanical product final assembly line TY Specific category information representing the production element, DV AT Attribute information representing the production element),
representing the source node DS of the production element data i,k,l,m At t p A data value of the time of day.
6. The method for constructing the dynamic model of the assembly process of the electromechanical product based on the digital twin according to claim 1, wherein the trunk corresponds to the assembly process of the electromechanical product, the crotch corresponds to the procedures included in the assembly process of the electromechanical product, the branch corresponds to the production behaviors under each procedure, the branch corresponds to the data source nodes of each production element under the production behaviors, and the leaf corresponds to the data value under the data source nodes.
7. The method for constructing dynamic model of assembly process of electromechanical product based on digital twinning as claimed in claim 1, wherein RAP is i As the trunk of the self-growing tree, the growth process of the trunk from bottom to top represents the final assembly process of the electromechanical product; AP (Access Point) i,k The crotch of the self-growing tree represents the working procedure in the final assembly process of the electromechanical product, the growth process of the crotch is embodied in that the working procedure is changed continuously along with the time migration, and the working procedure at the front part in the final assembly process is finished and the working procedure at the back part is finishedContinuously add from AP i,k Evolved into AP i,1 ,…,AP i,k ,…AP i,K Is a process of (1); AA (AA) i,k,l The tree branch represents the production behavior under the assembly process, the growth process of the tree branch is similar to that of a crotch, the production behavior is changed continuously along with the migration of time, and a new production behavior is added after the execution of the current behavior is finished until all the processes are finished, namely the assembly { AA } i,k,1 ,…,AA i,k,l ,…,AA i,k,L An extension process from none to some; DS (DS) i,k,l,m For branches of self-growing tree, representing production element data source nodes associated with production behaviors, the data source nodes are increased continuously along with time migration change, namely the set { DS } i,k,l,1 ,…,DS i,k,l,m ,…,DS i,k,l,M The expansion process of the data source nodes of each production element is divided into finer data source nodes, namely DS according to the requirement i,k,l,m Evolving into a set { DS ] i,k,l,m,1 ,…,DS i,k,l,m,n ,…,DS i,k,l,M,N A process of };
the tree leaves of the self-growing tree represent the production element data source nodes at t p The growth process of the leaf can be embodied as that the data value of the data source node is continuously increased along with the migration of time, and the DS is integrated i,k,l,m From elements of (2)
Expansion to->
Is a process of (2). />
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| US20210116505A1 (en) * | 2019-10-22 | 2021-04-22 | Wenzhou University | Digital-twin modeling method for automated testing pipeline for circuit breakers |
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