Disclosure of Invention
The invention provides a digital twin construction system engineering method based on a product full life cycle, which is used for solving the problems of incomplete and non-uniform intelligent construction system engineering model in the prior art. The unified management of the construction process taking the standardized product model as the tie is realized, information mistransmission and ambiguity in the construction process are avoided, and the completeness and consistency of the whole construction process information are realized.
In order to achieve the above object, the present invention provides a digital twin construction system engineering method based on a full life cycle of a product, the method comprising the steps of:
step 1, agreeing on connotation and boundaries of digital twin construction and product-driven digital twin construction system engineering.
Step 2, constructing a model-based product system engineering (MBPSE) methodology;
step 3, designing a digital twin construction system engineering overall architecture based on the whole life cycle of the product;
step 4, designing and realizing digital twin of the product;
step 5, establishing a digital twin construction system engineering model based on model nesting;
step 6, modeling a technological process of the digital twin construction system is realized;
and 7, developing and realizing digital twin construction system engineering.
Further, in said step 1, a definition of digital twin construction and product driven digital twin construction system engineering is proposed.
Further, in the step 3, a digital twin construction system engineering overall architecture based on the full life cycle of the product and a dual V model of a digital twin construction system engineering process (DTCMBSE) based on the model are designed.
Further, in the step 4, digital twin of the product is designed and implemented, a virtual production line is constructed through digital twin, and digital twin of the product is highly integrated with multi-model digital twin of related forms of production equipment, production process and production environment, so that high cooperation with factory big data as a main line is completed, and the digital twin technology is implemented to design, process, manufacture, assemble and test the product innovation, and regulate and control all stages of the whole life cycle of product marketing, after-sale service, customer relationship management, warehouse logistics supply chain and scrapping treatment.
Further, in the step 5, the system engineering model is divided into four basic levels, namely L1, L2, L3, and L4, wherein,
l1 is defined as a meta model;
definition of L2 is meta-model;
l3 is defined as a domain-specific model (e.g., construction robot);
l4 is defined as a system model (e.g., a build site).
And nesting the models of all basic layers, and establishing a multi-level scale model from microscopic to macroscopic according to the view angle of system engineering, wherein the model of the upper layer is a containment relationship with the model of the lower layer.
Further, in the step 5, the model types of the digital twin construction system include eight types, namely a building information model, an electromechanical model, an information model, a system architecture model, a scene model, a behavior model, a simulation model and a test model; the digital twin construction system model increases the system coupling degree through model integration and reduces the information repeatability.
Further, in the step 6, a process management software robot is introduced, and the process management software robot is deployed and operated on a process flow line;
the flow management software robot can realize related functions of fault discovery, flow automatic error correction, redundancy backup, parallel connection and trend research and judgment, wherein the parallel connection flow function can increase the reliability of a system.
Further, in the step 6, a process management software robot reliability calculation formula is set:
in the method, in the process of the invention,
k is the number of subsystem components of the building system, i=1, 2, k;
R'i reliability for the ith subsystem;
r is the reliability of the whole construction system;
ti the time required for the ith subsystem to operate in order to build the system;
pi the probability of system failure (system paralysis) caused by the failure (or sudden event disturbance) of the ith subsystem;
θi the average lifetime (or average failure-free operating time) of the ith subsystem.
Further, in the step 7, the step of developing and implementing the digital twin construction system engineering includes shop digital twin, factory digital twin and on-site digital twin.
Compared with the prior art, the invention has the beneficial effects that through the implementation of the invention, the construction engineering can be designed and managed more systematically and scientifically, the construction quality and the management level of the construction engineering are improved, the toughness of the construction engineering is improved, and the manpower and material resources are saved.
Furthermore, the invention uses the built system engineering model as a carrier to associate each related party, thereby improving the communication and cooperation efficiency of each party; the complex engineering management capacity is improved through technical means such as demand traction, model driving, process integration and automatic verification; the unified management of the construction process taking the standardized product model as the tie is realized, the information mistransmission and ambiguity in the construction process are avoided, and the completeness and consistency of the whole construction process information are realized; the whole process data intercommunication and semantic intercommunication of the construction engineering are realized; realizing the safe collection, automatic transmission and data value discovery of the construction data; the flow management software robot application in the intelligent building field is realized.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
The invention provides a digital twin construction system engineering method based on a product full life cycle, which comprises the following steps:
step 1, agreeing on connotation and boundaries of digital twin construction and product-driven digital twin construction system engineering.
Step 2, constructing a model-based product system engineering (MBPSE) methodology;
step 3, designing a digital twin construction system engineering overall architecture based on the whole life cycle of the product;
step 4, designing and realizing digital twin of the product;
step 5, establishing a digital twin construction system engineering model based on model nesting;
step 6, modeling a technological process of the digital twin construction system is realized;
and 7, developing and realizing digital twin construction system engineering.
In step 1, digital twin construction refers to system engineering with "construction" as a goal, MBSE (model-based system engineering) methodology as a guide, "digital twin" as a technology and management means, and "construction industry chain" as a process tie.
The product-driven digital twin construction system engineering is to take building product big data as a whole life cycle clue of an intelligent construction system, take a building product model as a core, apply digital twin technology, realize digital mapping and organic fusion of seven core elements of materials, equipment, environment, information, energy, people and standards by the construction system, form a construction engineering multi-element heterogeneous model system, realize real-time control and system integration of a construction physical space and a construction information space, and realize physically dispersed and logically coordinated virtual-real interaction unified intelligent construction complex system.
Please refer to fig. 1, which is a schematic diagram of four quadrants of the MBPSE model and their relationship.
In the step 2, MBSE (Model-Based Systems Engineering, model-based system engineering) is taken as a methodology guidance, and based on the Model, MBPSE-Model-Based Products Systems Engineering is provided, and Model-based product system engineering is an application of a Model-based method in the field of building product manufacturing engineering, mainly solves the problems of processing, manufacturing, operation and maintenance management of the whole life cycle of the product in digital twin building system engineering, and simultaneously aims at reducing engineering development risk, reducing cost, improving efficiency and improving quality.
MBPSE includes three core concepts: building a model, system thinking and system engineering. Building a model is a graphical, mathematical, or physical representation of a building system that abstracts reality to eliminate some complexity, simplify the representation, abstract out forms or rules.
The MBPSE model describes the problems the system is to solve and the system itself.
MBPSE system engineering is a interdisciplinary and comprehensive method, and utilizes system principles and concepts, and scientific, technical and management methods to enable engineering systems to be successfully realized, used and retired. The various techniques are pooled to ensure that the designed system meets all requirements. The system is focused on the architecture, implementation, integration, analysis and management of the system in its lifecycle. Software, hardware, personnel, procedures and programs of the system are also contemplated.
MBPSE modeling uses four tools: (1) language; (2) a structure; (3) demonstration; (4) demonstration. The MBPSE modeling field covers four system engineering fields: (1) demand/capability; (2) act; (3) architecture/structure; (4) verification and validation.
The terms of the MBPSE language map to parts of speech: (1) noun: participants, roles, components, requirements; (2) verbs: operation activity, function and use case; (3) adjectives: an attribute; (4) adverbs: relationship, demand line, exchange, interface.
The MBPSE model has two aspects: problem aspects and solution aspects are referred to as operations and system angles. The operational perspectives are the perspectives of the user, operator and business person. Representing business processes, targets, organizational structures, use cases, and information flows. The operational end of the model may contain descriptions of the "world present" and future states. The system's perspective is a solution, the system's architecture solves the problems posed at the operational end of the model, describes the system's behavior, structure, data flow between components, and distribution of functionality, describes how the system will be deployed in the real world, and may involve selection and analysis of solutions. Each of these perspectives has two parts, logical and physical. The logical and physical aspects of the separation model are one way to manage the complexity of the system. The logical part of the model will typically not change over time, whereas the physical change is typically caused by technological advances. If the model is constructed correctly, the four quadrants of the logic operation, the physical operation, the logic system and the physical system should be tightly connected. The user should be able to perform system analysis, create a dependency matrix, run simulations, and provide a system view for each stakeholder.
Referring to fig. 2-3, fig. 2 is a schematic diagram of a digital twin construction system engineering overall architecture based on a product full life cycle, and fig. 3 is a schematic diagram of a model-based digital twin construction system engineering flow double V model.
In step 3, from the building element to the high-rise building, it can be regarded as a building product.
The whole life cycle of the building product covers the whole engineering cycle of the digital twin construction system.
The whole life cycle of the building product refers to the time range from birth to death of the building product, and comprises 10 small stages of planning, designing, developing, producing, transporting, constructing, checking and accepting, operating and maintaining, selling and retirement, and 3 large stages of production, construction and operation. The whole process is dependent on data throughout, and the product database is a key component of the digital twin construction data system.
In step 4, the digital twin of the product is a process of high cooperation by taking factory big data as a main line, a virtual production line is constructed through the digital twin, and the digital twin of the product is highly integrated with multi-model digital twin of other forms such as production equipment, production process, production environment and the like.
From product innovation planning, design, manufacturing, assembly, testing, to product marketing, after-sales service, customer relationship management, warehouse logistics supply chain, scrapping, digital twinning techniques extend through the various stages of the full life cycle of the product in the construction process.
The digital twin model can realize standardization, coordination, intelligent design, processing and manufacturing of products, and can realize predictable and preventable guarantee before use.
In the product design stage, digital twin is utilized to improve the accuracy of design and verify the performance of the product in a real environment. Digital twinning at this stage involves: (1) The digital model design, the product virtual prototype meeting the technical specification is developed by using tools such as CAD and the like, various physical parameters of the product are accurately recorded, the physical parameters are displayed in a visual mode, and the accuracy degree of the design is checked by a series of verification means; (2) modeling and simulation: a simulation model of product movement and operation is established through MATLAB Simulink and other tools, and simulation experiments of variable structure, variable parameters, variable load, acceleration and the like are carried out in a simulation system, so that the performance and adaptability of the product under different external environments are verified.
In the product manufacturing stage, production-oriented digital twinning includes process flows, manufacturing equipment, manufacturing workshops, control systems, production environments, management systems, and the like. The digital twin can shorten the period of product design, improve the quality of product design, improve the production efficiency of the product and reduce the production cost of the product.
In the product operation and maintenance stage, maintenance is based on analysis and identification of damage and early stages of damage precursors, and most of guarantee works are converted into damage prediction, prevention and management in the life cycle. In the running process of the product, equipment running information is transmitted to the cloud in real time, equipment running optimization, equipment predictability maintenance and maintenance are carried out, and product design, process and manufacturing iteration optimization are carried out through the equipment running information. Comprising: optimizing operation of equipment, predictively maintaining, repairing and maintaining, designing, and optimizing process and manufacturing iteration.
In step 5, the system engineering model is divided into four basic levels, namely L1, L2, L3 and L4 respectively, wherein,
l1 is defined as a meta model;
definition of L2 is meta-model;
l3 is defined as a domain-specific model (e.g., construction robot);
l4 is defined as a system model (e.g., a build site).
Nesting the models of all basic levels, and establishing a multi-level scale model from microscopic to macroscopic according to the view angle of system engineering, wherein the model of the upper level is an inclusive relationship with the model of the lower level, for example: l3 contains L2.
Model types for digital twin construction systems mainly include eight classes: (1) Building Information Model (BIM): creating models of building elements, structures, materials, etc.; (2) electromechanical model: creating mechanical, electronic, electrical, automatic control and other models; (3) information model: creating models of various fields such as network, communication, software, data and the like; (4) System architecture model: the method comprises a logic architecture model, a functional architecture model and a physical architecture model; (5) scene model: creating a scene description model, a workflow model, a business model and the like; (6) behavior model: a model for describing system element activity events such as a robot, a person and the like; (7) simulation model: a model for performing simulation on the physical world; (8) test model: and testing and verifying the product functions, confirming the product requirements, and predicting and optimizing the product performances.
The digital twin construction system model is an integrated model integrating multidisciplinary and multisypic models, the system coupling degree is increased through model integration, the information repetition degree is reduced, and finally the system-level model optimization is achieved.
Typical features of a model-based digital twin construction system are: 1) Digitizing the model; 2) Automating the production and construction process; 3) The system is less humanized and even unmanned; 4) The management decision is intelligent; 5) The whole process is traceable based on data clues; 6) The toughness of the system is high, and the response is recovered in time; 7) The system has high safety and the knowledge is credible and interconnected.
Referring to fig. 4, which is a schematic diagram of a modeling method for a process flow of a digital twin construction system, in step 6,
the process management software robot is deployed and runs on a process flow line. The flow management software robot has the functions of fault discovery, flow automatic error correction, redundancy backup, parallel connection and trend research and judgment, wherein the parallel connection flow function increases the reliability of the system and improves the overall toughness of the system.
The reliability of the whole construction system is calculated by a weighted accumulation method from the reliability of each component subsystem.
The system is composed of k subsystems. The reliability calculation formula is:
in the method, in the process of the invention,
R'i reliability of the ith subsystem;
r, the reliability of the whole subsystem;
ti the system needs the time of the ith subsystem work;
pi the probability of system failure (system paralysis) caused by the failure (or sudden event disturbance) of the ith subsystem;
θi the average lifetime (or average failure free operating time) of the ith subsystem.
(2) Professional Digital Thread (Digital Thread) technology (i.e., building Digital Thread technology) facing the building field:
the connection and communication between each link of the process flow depend on the construction of digital thread technology.
The digital thread is a core technology of a digital twin system, all data models can be communicated in two directions through the digital thread, the state and parameters of a real physical product are fed back to the digital model through a CPS integrated with an intelligent building system, so that the digital model of each link of a life cycle is kept consistent, and the current and future functions and performances of the system can be dynamically and real-time estimated. The digital thread integrates the model of the whole process of building the engineering life cycle to form a model system. The model system and the actual intelligent building system are further seamlessly integrated and synchronized with an embedded Consumer Physical System (CPS), thereby enabling developers and users to see what actual physical products may happen on the digital twin product. The digital thread runs through the whole life cycle of the product, and can help the product to realize the whole process seamless integration from planning, design, production to operation and maintenance.
As the implementation method of the digital twin construction system engineering technology, the invention fully introduces the design method and the technical module of the industrial control system, applies the industrial control technology to the construction management object in the construction process and establishes the construction system engineering. An industrial control network is generally defined as a network which takes a sensor, an actuator and a measurement and control instrument with communication capability as network nodes, takes a field bus or an Ethernet as a communication medium and is connected into open, digital and multi-node communication so as to complete measurement control tasks. The digital twin construction network should first be a precise building control network with the general function of an industrial control network.
Referring to fig. 5, a schematic diagram of a development implementation path of a digital twin construction system engineering is shown, wherein the development implementation steps of the digital twin construction system engineering include three steps: workshop level digital twinning, factory level digital twinning and field level digital twinning.
(1) Workshop-level digital twinning
The starting point of the digital twin construction system engineering is in a workshop, and an industrial intelligent mode is adopted from a workshop link according to the planning and design concept of the assembly type building. The component production process of the fabricated building is typically discrete manufacturing, and the intelligent assembly shop consists of an on-site layer, a control layer and a management layer.
The key point of constructing a data closed loop of 'field perception-real-time control-intelligent decision-fine management' is to realize the longitudinal integration between the 'equipment layer, unit layer and workshop layer' and the enterprise layer, realize the cross-resource element, interconnection and intercommunication, fusion sharing and system level transverse integration, and cover the end-to-end integration of research and development design, production manufacturing, operation and maintenance.
The main composition system comprises: workshop information management system, workshop manufacturing operation management system, workshop operation visualization system, workshop data SCADA acquisition system.
The production field data are transmitted to other information systems of workshops through processing, a data base is provided for intelligent workshop production management, and finally the ordering and transparency of the intelligent workshop production management and the traceability of production process and quality data are realized.
Workshop logistics management system: the material identification intellectualization, the logistics tracking networking and the logistics information integration are used as targets, and a workshop logistics management system is designed. And the RFID radio frequency identification, the AGV automatic guided vehicle and the RGV rail guided vehicle are comprehensively adopted to realize logistics automation.
And (3) production line: the flexible production line is constructed by taking virtual simulation, on-line monitoring and on-line adjustment as basic functions of a digital twin system, and taking multiple varieties and small batches as characteristics. Product cluster analysis, station layout optimization, process flow reconstruction and production line technology upgrading are realized.
(2) Plant-level digital twinning
Mainly realizes the digital twin of the enterprise management level. And monitoring and controlling each workshop through a factory industrial Internet time digital twin platform.
(3) On-site digital twin
Mainly realizes digital twin on the engineering construction site.
Building a line: the flexible building line is constructed by taking virtual simulation, on-line monitoring and on-line adjustment as basic functions of a digital twin system and taking multi-species and micro-process as characteristics. The construction process optimization, construction process improvement and construction technology upgrading are realized.
The representative techniques employed and the effects achieved are as follows:
the method realizes the safety collection, safety convergence, automatic transmission and data value discovery of the construction data. The automatic data transmission utilizes program software to automatically transmit shared data between different information systems through a building flow management robot and transmit the data through a database trigger. The PLM, ERP, APS, MES system data stored in the SQL Server database is integrated by means of interfaces such as ODBC and API by adopting a means which is convenient to develop and low in cost in the automatic data transmission method. Various processed (encrypted, marked, cleaned and the like) data are converged through a digital twin construction system cloud platform, and the data value discovery is supported through data modeling and data mining after identification data analysis and data format conversion.
And the whole process data intercommunication and semantic intercommunication of the construction engineering are realized. The data identification is built by defining a standard format and the building identification Internet is built, a data barrier between an upstream and a downstream of a building process and between enterprises in the field of industry is opened, the problems of inconsistency, unrealness and falsification in the field information transmission process are solved by means of a building system engineering unified system architecture on the basis, the data intercommunication based on the trusted identification is realized, and the system interconnection and intercommunication in the true sense of technical platform independence are realized from the semantic level.
The flow management software robot application in the intelligent building field is realized. The software robot technology in the artificial intelligence field is organically integrated into the digital twin construction system, so that any link and the whole process in the whole life cycle of the construction product are integrated into the AI, and the intelligent level of the intelligent construction system engineering is integrally improved.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.