1. Abstract in Chinese
As an important enabling technology to realize advanced concepts such as digitization, intelligence, and service, digital twins are currently attracting attention from academia and industry. The model is the foundation and core of the digital twin, and the traditional three-dimensional model of the digital twin cannot meet the current technology development and application requirements. Based on the proposed five-dimensional structural model of digital twins, this paper introduces six basic principles of digital twins driven by digital twins from the perspective of practical application requirements, and uses the digital twin standard system framework to effectively apply digital twin technology. guide. At the same time, digital twin technology has been widely used in all walks of life. This article briefly explains the application of digital twin technology used in six hot areas: aerospace, smart manufacturing, smart city, smart water conservancy, smart grid and transportation. .
Keywords : digital twin; five-dimensional structural model; standard system framework; digital twin application
2. Abstract in English
As an important enabling technology for realizing advanced concepts such as digitization, intelligence and service, digital twin is currently attracting much attention from academia and industry. The model is the foundation and core ofdigital twin, and the traditional 3D model of digital twin can no longer meet the current stage of technology development and application requirements. Based on the proposed five-dimensional structure model of digital twin, this paper introduces the six basic guidelines of digital twin-driven digital twin anduses the framework of digital twin standard system to effectively guide the application of digital twin technology on the ground from the actual applicationrequirements. Digital twin technology has been widely used in various industries, and this paper briefly explains the application of digital twin technology in six popular fields: aerospace, smart manufacturing, smart cities, smart water, smart grid and transportation.
Keywords:digital twin; five-dimensional structural model; standard system framework; digital twin application
3. Introduction
The conceptual model of the digital twin first appeared in 2003. It was proposed by Professor Grieves in the product lifecycle management (PLM) course of the University of Michigan in the United States. It was called the "mirror space model" at that time [1], and later It is also defined as "information mirror model" and "digital twin" [2].
In recent years, digital twin technology has been widely concerned by scholars at home and abroad, and it plays an important role in product development and manufacturing control. According to statistics, up to now, more than 500 researchers from more than 160 institutions in more than 40 countries including the United States, China, and Germany have carried out digital twin theory and application research, and have published relevant research results. At the same time, Siemens, Tesla La Company, ANSYS Company, General Electric Company and other world-renowned companies have carried out the application practice of digital twins in related fields [3].
In foreign countries, digital twin technology was mainly used in the military and aviation fields in the early days. In 2010, the National Aeronautics and Space Administration (NASA) introduced the concept of digital twins for the first time in the space technology roadmap [4], intending to use digital twins to realize the comprehensive diagnosis and prediction functions of the flight system, so as to ensure the realization of the system during the entire service life. Continue to operate safely. The U.S. Air Force Research Laboratory (AFRL) introduced the concept model of using digital twin technology for aircraft structure life prediction in 2011 [5], and gradually extended it to the airframe state assessment research, by establishing a model that includes materials, manufacturing specifications, control, Surrealistic, full-life-cycle computer models of the fuselage with information such as construction process and maintenance, combined with historical flight monitoring data to conduct virtual flights to evaluate the maximum allowable load to ensure airworthiness and safety, thereby reducing the burden of full-life cycle maintenance , increasing aircraft availability.
Due to the promotion of companies such as GE and Siemens, digital twin technology has also developed rapidly in the field of industrial manufacturing in recent years. GE builds assets, systems, and cluster-level digital twins based on the Predix platform. Manufacturers and operators can use digital twins to characterize the entire life cycle of assets, so as to better understand, predict, and optimize the performance of each asset[6] . Siemens AG put forward the concept of "digital twin", and is committed to helping manufacturing enterprises build a production system model that integrates manufacturing processes in the information space, and realize the digitalization of the whole process from product design to manufacturing execution in the physical space [7]. ANSYS proposes to use ANSYS Twin Builder to create a digital twin and quickly connect to the industrial internet of things (IIoT) platform to help users diagnose faults, determine the ideal maintenance plan, and reduce costs due to unplanned downtime , optimize the performance of each asset and generate valid data to improve its next-generation products [8].
Domestic research on digital twin technology is relatively late, but many scholars have carried out a lot of research in recent years. Beijing University of Aeronautics and Astronautics [9] took the lead in integrating digital twin technology into the manufacturing workshop, carried out research on its operation mode, model construction theory and application exploration for the digital twin workshop, and elaborated on its system architecture, operation mode and key technologies for implementation. At the same time, the theory and implementation method of physical information fusion in the workshop are discussed, and the digital twin model construction criterion of "four modernizations and four usability" is proposed. Liu Juan et al. [10] aimed at the application bottleneck of online prediction in the operation state of the production workshop, and proposed a real-time data-driven online prediction method, which combines real-time data with the input characteristics, sample production, and event processing logic constructed based on the operation logic of the event scheduling method. The relationship between the three is used to realize the online prediction system of continuous transient simulation. Liu Zhifeng et al. [11] proposed a scheduling cloud platform based on digital twin technology to predict and diagnose multi-source dynamic disturbance problems by monitoring the real-time status of products and using big data analysis technology to solve the dynamic disturbance problem in the parts manufacturing process. And taking a part intelligent manufacturing workshop as an example, it is demonstrated that the part intelligent manufacturing combined with digital twin technology is the future development direction.
In terms of theory, Zhuang Cunbo et al. [12] summarized the basic connotation of product digital twins in intelligent manufacturing, proposed the architecture of product digital twins, and explained that product digital twins can be used in the product design stage, manufacturing stage and service stage. way of implementation. The digital twin five-dimensional structure model proposed by Tao Fei et al. [13] designed six basic principles for the application of digital twin drivers, and discussed the fusion of physics and information in digital twin technology, and considered how to realize the information world and the physical world. The interactive mapping of is a common technical bottleneck at home and abroad.
As an emerging intelligent technology, digital twin technology has gone through three stages: prediction-prediction, maintenance-prediction, maintenance-service. , to the combination of physical information systems to study complex system prediction and maintenance, and the development of the current human-computer interaction experience platform to realize the development of prediction, maintenance and service functions. The application of digital twin technology in product forecasting, product maintenance, product service, etc. has become more and more mature, providing a clear idea for intelligent manufacturing. In the future, everything in the world will have its digital twin and be connected to each other through the Internet of Things to create huge value.
The structure of this paper is as follows. In the first section, the basic definition of digital twin and the five-dimensional structural model as well as the application criteria driven by the digital twin five-dimensional model are expounded. The second section introduces the digital twin standard system framework, and the third section lists the digital twin technology. The main application areas of DT, Section 4 summarizes the digital twin technology and puts forward suggestions for the future.
4. Definition and model of digital twin
4.1 Definition of digital twin
Digital twin (Digital Twin) is to digitally create a virtual model of a physical entity, with the help of data to simulate the behavior of the physical entity in the real environment, through virtual and real interactive feedback, data fusion analysis, decision-making iterative optimization, etc., to increase or expand the physical entity new abilities. As a technology that makes full use of models, data, intelligence, and integrates multiple disciplines, digital twins are oriented to the entire life cycle of products, and play the role of a bridge and link connecting the physical world and the information world, providing more real-time, efficient, and intelligent services.
The essence of digital twin is the integrated application based on the Internet of Things, sensors, models, data, mapping, and simulation multidisciplinary technologies. The core problem is the management of the entire life cycle of equipment. Digital twin was originally proposed based on the equipment life cycle management scenario, focusing on the digitization of physical equipment. To further generalize this concept, we can digitize all elements of the physical world, such as people, objects, and events, and recreate a one-to-one corresponding virtual world in cyberspace. The physical world and the virtual world coexist, virtual and real blend, and everything can be digital. twins. The schematic diagram of the digital twin concept is shown in Figure 1:
4.2 Digital twin five-dimensional model
(1) The physical entity (PE) is the basis of the digital twin five-dimensional model, which mainly includes the different functions of each subsystem, which jointly support the operation of the equipment and the sensors to collect equipment and environmental data. Accurate analysis and effective maintenance of physical entities are the prerequisites for establishing a digital twin model.
(2) Virtual entities (VE) include geometric models, physical models, behavioral models, and rule models, which describe and characterize physical practice from multiple time scales and multiple spatial scales, forming a complete mapping of physical entities. VR and AR technologies can be used to realize the virtual reality superposition and fusion display of virtual entities and physical entities, and enhance the immersion, authenticity and interactivity of virtual entities.
(3) Service (Ss) Service-oriented packaging of various data, models, algorithms, simulations, results, etc. required for different fields, different levels of users, and different businesses in the digital twin application process, and provided by application software or mobile terminals It is provided to users in the form of App to realize the convenience and on-demand use of services.
(4) Twin data (DD) is the driver of digital twins, which integrates information data and physical data, meets the consistency and synchronization requirements of information space and physical space, and can provide more accurate and comprehensive all-factor/full-process/ Full business data support.
(5) Connection (CN) The connection model includes connection to enable physical entities, virtual entities, and services to maintain interaction, consistency and synchronization during operation, and connection to enable data generated by physical entities, virtual entities, and services to be stored in twin data in real time, and to enable twin Data can drive the operation of the three.
4.3 Application criteria driven by digital twins
Based on the above-mentioned five-dimensional structure model of the digital twin to realize the application driven by the digital twin, firstly analyze the characteristics of the physical entity according to the application object and requirements, then establish a virtual model, build a connection to realize the interaction of virtual and real information data, and use the fusion and analysis of the twin data, Finally, various service applications are provided for users. In order to promote the application of digital twins, digital twin-driven applications can follow the following guidelines:
(1) Cyber-physical fusion is the cornerstone. The intelligent perception and interconnection of physical elements, the construction of virtual models, the fusion of twin data, the realization of connection and interaction, and the generation of application services are all inseparable from cyber-physical fusion. At the same time, cyber-physical integration runs through all stages of the product life cycle and is the foundation of every application. Therefore, without the fusion of information and physics, the application of digital twins is a castle in the air.
(2) The multidimensional virtual model is the engine. The multidimensional virtual model is the core component to realize various functions such as product design, manufacturing, fault prediction, and health management. Driven by data, the multidimensional virtual model turns application functions from theory into reality, and is the "heart" of digital twin applications. Therefore, without a multidimensional virtual model, digital twin applications have no core.
(3) Twin data is the driver. Twin data is the core element of digital twins. It originates from physical entities, virtual models, and service systems. At the same time, it is integrated into various parts after fusion processing to promote the operation of each part. It is the "blood" of digital twin applications. Therefore, without multiple fusion data, the digital twin application loses its source of power.
(4) Dynamic real-time interactive connections are arteries. Dynamic real-time interactive connection connects physical entities, virtual models, and service systems into an organic whole, enabling information and data to be exchanged and transmitted between various parts, which is the "vessel" of digital twin applications. Therefore, without the interactive connection between the various components, just like the human body cuts off the artery, the digital twin application will lose its vitality.
(5) Service application is the purpose. The service provides users with functions such as intelligent applications, precise management, and reliable operation and maintenance generated by digital twin applications in the most convenient form, and at the same time gives users the most intuitive interaction, which is the "five senses" of digital twin applications. Therefore, digital twin application implementation is pointless without service applications.
(6) The physical entity of all elements is the carrier. Whether it is the interactive integration of full-factor physical resources, or the simulation calculation of multi-dimensional virtual models, or data analysis and processing, they are all based on full-factor physical entities, and at the same time, physical entities drive the operation of various parts, enabling digital twins to be realized , is the "skeleton" of the digital twin application. Therefore, without a physical entity, a digital twin application is a tree without roots.
5. Digital twin standard system framework
5.1 Actual requirements of digital twins
In years of theoretical research and application practice of digital twins, the following problems have been found: ① There is a lack of references to digital twin related terms, system architecture, applicable standards and other standards, resulting in different users starting from different application dimensions and technical requirements. Twins have different understandings and understandings, which lead to problems such as communication difficulties, integration difficulties, and collaboration difficulties in the process of digital twin research and application; During the implementation of key digital twin technologies, problems such as difficulty in integration between models, between data, between models and data, and between systems, poor consistency, low compatibility, and difficult interoperability have resulted in the formation of new isolated islands; ③ Lack of applicable guidelines and implementation requirements References to standards such as tools, platforms, etc., in the process of implementing digital twins in related industries/fields, may easily cause confusion for users or enterprises in the use of digital twins. Relevant standards such as digital twin evaluation, security, and management are required to provide reference and guidance for the evaluation and safe use of digital twins.
5.2 Digital twin standard system framework
According to the above-mentioned demand analysis for the digital twin standard system, comprehensively considering the rationality, completeness, systematicness, and usability of the standard system, the digital twin standard system framework as shown in Figure 3 is designed [15], starting from the basic common standards and key technical standards , tool/platform standards, evaluation standards, security standards, and industry application standards to provide standard guidance in six aspects.
(1) Digital twin basic common standards. Including terminology standards, reference architecture standards, and applicable criteria, it focuses on the concept definition, reference frame, applicable conditions and requirements of digital twins, and provides support for the entire standard system.
(2) Key technical standards for digital twins. Including physical entity standards, virtual entity standards, twin data standards, connection and integration standards, and service standards, it is used to guide the research and implementation of digital twin key technologies, ensure the effectiveness of key technologies in digital twin implementation, and eliminate collaborative development. and technical barriers to module interchangeability.
(3) Digital twin tool/platform standards. Including tool standards and platform standards, it is used to standardize the technical requirements of software and hardware tools/platforms such as functions, performance, development, and integration.
(4) Evaluation criteria for digital twins. It includes 4 parts: evaluation guidelines, evaluation process standards, evaluation index standards, and evaluation use case standards, which are used to standardize the testing requirements and evaluation methods of the digital twin system.
(5) Digital twin security standards. Including physical system security requirements, functional security requirements, and information security requirements, it is used to standardize technical requirements such as personnel security operations in the digital twin system, secure storage, management, and use of various information.
Digital twin industry application standard. Considering the technical differences of digital twins in different industries/fields and different scenarios, on the basis of basic common standards, key technical standards, tool/platform standards, evaluation standards, and safety standards, digital twins in machine tools, workshops, satellites, Standardize the implementation of applications in specific industries such as engines, construction machinery and equipment, cities, ships, and medical care.
6. Application of digital twin technology
Digital twin technology breaks through the gap between the physical world and the digital world, realizes the integration of virtual and real in physical information systems, and has been widely expanded in vertical industries such as smart manufacturing, smart construction, smart medical care, and smart cities, resulting in smart operation and maintenance, virtual commissioning, Abnormal diagnosis, risk prediction, decision-making assistance, system optimization and many other application values have become an important starting point to help enterprises digitally transform, improve production efficiency, and promote the development of the digital economy.
As shown in Figure 4, the current digital twin has attracted the attention of more than ten industries and carried out application practices. In addition to being first used in the aerospace field, digital twin technology has also been applied in smart manufacturing, smart city, smart water conservancy, smart grid, transportation, automobile, medical health, construction and other fields in recent years, and has shown great application potential. A brief introduction to some of these areas is given below.
6.1 Aerospace based on digital twin
In the field of aerospace, digital twins have great application potential: ① for the design and development of aircraft. By establishing a digital twin of the aircraft, virtual digital testing and verification can be performed on each component before it is actually processed, and design defects can be found and modified in time, avoiding the high cost and long cycle caused by repeated iterative design. Dassault Aviation [16] used the 3DExperience platform (a virtual development and simulation platform based on the concept of digital twins) to improve the design process of the "Rafale" series of fighter jets and "Falcon" series of business jets, reducing waste by 25%, the first quality improvement Increased by more than 15%; ②Used in the manufacture and assembly of aircraft. In the actual production of various parts of the aircraft, the digital twin of the aircraft and its corresponding production line can be established to track its processing status and reduce downtime by rationally allocating resources, thereby improving production efficiency and reducing production costs. Lockheed Martin applies digital twins to the manufacturing process of the F-35 fighter, and expects to further increase the production speed of the F-35 through real-time feedback of manufacturing data. It is estimated that the current 22-month production cycle of each aircraft shortened to 17 months, while reducing the production cost of $94.6 million per aircraft to $85 million by 2020. In addition, Northrop Grumman [17] used digital twins to improve the inferior product processing process in the production of the F-35 airframe, and shortened the decision-making time for processing defects in the F-35 inlet by 33%; ③Used for the operation and maintenance of the aircraft. Using the digital twin of the aircraft, the damage state of the structure can be monitored in real time, combined with intelligent algorithms to realize the dynamic update of the model, improve the prediction ability of the remaining life, and then guide the change of mission plan, optimize maintenance scheduling, and improve management efficiency.
In the future, digital twin technology will be able to promote the intelligence of various aerospace vehicles, such as smart engines, smart aircraft, and smart space stations. Through the information of the aircraft itself and the surrounding environment collected by the sensors, it can realize its own state awareness, environment awareness and situation awareness, independently plan future mission paths and carry out self-maintenance, which will be able to achieve higher mission success rate, longer service life and lower operating costs. low goals.
At present, the application of digital twins in aerospace still faces some challenges: ①Digital twins are a comprehensive technical system involving multiple fields, which in itself shows the difficulty of its implementation. The technical framework of digital twins and the definition of the model structure of digital twins are still Immature, how to conduct knowledge reasoning and discovery based on digital twins to achieve the ultimate goal of intelligence remains to be studied; ② In terms of key technologies of digital twins, fault diagnosis based on big data and dynamic modeling of complex systems under uncertainty , online real-time analysis and calculation mathematical methods, suitable for aerospace environments, extreme conditions, lightweight, and distributed sensor monitoring technology are current research frontier issues; ③ At the level of digital twin tools, it is still necessary to develop and improve the development of autonomous digital twins Run the integration platform.
6.2 Intelligent manufacturing based on digital twin
As a potential way to realize the interactive integration of the physical world and the information world in intelligent manufacturing, digital twin technology is gradually applied to all aspects of the product life cycle, namely product design, industrial production and manufacturing services. Production efficiency and predictive maintenance of equipment are of great significance.
(1) Application of digital twin technology in product design. Product design is an important link in the product life cycle, and it is also the first step in the application of digital twin technology to intelligent manufacturing [18]. Large-scale, personalized product design has become the ideal design goal pursued by enterprises. Traditional design methods generally have problems such as inaccurate requirements and difficult design collaboration, and the prototype trial production cycle is long and costly, and its performance cannot be feedback and verified in time, which seriously affects the product innovation and market development of enterprises. For this reason, digital twin technology is gradually introduced into it. Digital twin technology enables designers to compare the performance of a virtual product in different environments to ensure that inconsistencies between the actual behavior of the production product and the desired actual values are minimized. At the same time, digital twins can speed up the design cycle by avoiding lengthy testing for evaluating virtual products.
Tao Fei et al. [19] proposed a product design framework (digital twin-driven product design framework, DTPD) based on digital twin technology. The framework focuses on connecting physical products with virtual products, and is mainly applicable to the iterative optimization design of existing products. Most of the selected design methods that make up DTPD have been proved to be more useful for redesigning existing products. SCHLEICHB et al. [20] proposed a comprehensive reference model based on the concept of surface model shape as a digital twin of the physical product for the management of geometric variations during the design and manufacturing process. STARR et al. [21] proposed a new architecture modular design method for cyber physical production systems (CPPS) based on digital twins, by integrating existing production resources and new CPS units into construction tool modules , plant manufacturers can use virtual prototypes to create, verify and optimize the architecture of CPPS.
(2) Application of digital twin technology in industrial production. The industrial production process is a very complex system engineering. Digital twin technology can connect the physical equipment in the physical world with the virtual equipment in the information world. The virtual equipment can reflect the production situation of the physical equipment in real time and control the actual production process. , thereby increasing the flexibility of the production system, improving production efficiency and product quality, and reducing energy and material consumption.
Zhao Haoran et al. [22] proposed a 3D visualized real-time monitoring method for digital twin workshops, studied the data-driven virtual workshop operation mode based on workshop operation logic modeling, realized the dynamic monitoring of the whole process and all elements of the workshop, designed and A prototype system was developed and verified by examples. KNAPPGL et al. [23] established a digital twin model of the additive manufacturing process to predict the temperature field and velocity field, cooling rate, solidification parameters and sediment geometry, thereby reducing the number of trials for adjusting process variables. The experimental results show that the The model can accurately predict the temporal and spatial changes of metallurgical parameters that affect the structure and performance of parts. CORONADOPDU et al. [24] proposed a device data acquisition method based on MES and MTConnect protocol, and used it for production control and optimization.
(3) Application of digital twin technology in manufacturing services. Massive multi-source and heterogeneous data will be generated during the production process of products. Digital twin technology can analyze and process them in real time, so as to obtain more comprehensive and valuable information, and provide fault prediction and health management services for production equipment. At the same time, provide technical guidance and management decision-making services for staff.
Ding Hua et al. [25] proposed a method for predicting the health status of coal shearers driven by the fusion of digital twins and deep learning. Based on multiple physical parameters in physical space, a life prediction model for key parts of digital twins and deep learning was constructed to realize the health status of coal shearers. Real-time status visualization and remaining life prediction of key components provide decision-making guidance for predictive maintenance of coal shearers. Zhang Xuhui et al. [26] proposed an overall model of auxiliary maintenance guidance for electromechanical equipment based on digital twins and mixed reality, and verified its key technologies, which solved the virtual-real fusion, two-way mapping and simulation of physical maintenance space and virtual maintenance space Early warning realizes equipment failure data-driven MR failure maintenance guidance process and provides technical support for on-site maintenance personnel. ZAKRAJSEK AJ et al. [27] proposed a digital twin-based aircraft tire landing wear prediction model to determine the distribution failure probability of sink rate, yaw angle, tire condition, and landing speed. Experimental results demonstrate the potential benefits of the model for aircraft mission decision-making, cost savings and monitoring tire health during landing. KRAFT J et al. [28] proposed a digital twin model of an active engine consisting of a multilevel model of the engine and its components for degradation and failure analysis, as well as prediction of life consumption of key components.
At present, most of the applications of digital twin technology in intelligent manufacturing around the world are focused on fault prediction and health management, and a small part is focused on virtual commissioning, production scheduling, and energy management related to manufacturing workshops. There is a certain gap in the description of the real physical world. At the same time, tools for effectively evaluating digital twin models are lacking.
6.3 Smart city based on digital twin
Digital twin technology has reached the 3.0 era in the construction of smart cities, and the digital twin city already has a preliminary system framework. Below are three examples of application scenarios.
(1) Hangzhou "Urban Brain". At present, Hangzhou City has launched the "Urban Brain" pilot project, which covers an area of more than 50,000 square kilometers. Through the city brain to automatically deploy traffic lights, use smart devices to control traffic lights at 1300 intersections to detect traffic videos of 4500 roads, upload the road data generated in the process to the "city brain", and the "city brain" responds immediately and plans a road The route that can send patients to the destination in the shortest time has greatly improved the efficiency of ambulance rescue, doubled the time for ambulances to arrive at the scene, and effectively escorted patients. At the same time, in the pilot area, by using the "urban brain" to realize the intelligent configuration of traffic lights, the traffic time in this area was shortened by 15.3%[29].
(2) "Smart Xiong'an" planning. Under the leadership of Wu Hequan, academician of the Chinese Academy of Engineering, and Liu Duo, president of the China Academy of Information and Communications Technology, the Institute of Industry and Planning of the China Academy of Information and Communications Technology has designed the overall framework of "Smart Xiong'an" [30], which requires the realization of regional Inter-integration and interaction, synchronous planning and construction at the same speed in the whole process, carry out interaction between the two places, create a digital twin city, and achieve intelligent decision-making execution and data information visualization. The "Xiong'an Planning Outline" puts forward in the field of urban intelligent management: "Insist on simultaneous planning and construction of digital cities and real cities, moderately advance the layout of intelligent infrastructure, and build a world-leading digital city", "Establish and improve a big data asset management system , to create a world-leading digital city with deep learning capabilities" and other construction content [30].
(3) DIGITAL TWIN OF THE CITY OF NEWCASTLE. In the UK, graduate students from Newcastle University, in collaboration with Northumbrian Water, created a digital twin of the city to help the city of Newcastle better respond to emergencies and disasters [31]. The relevant water companies can use the model to generate simulations of events such as exploding pipelines, heavy rain or severe flooding, and predict the impact on urban housing and human activities in the next 24 hours. Chris Kilsby, professor of hydrology and climate change at Newcastle University's School of Engineering, said in an interview with the Guardian: "Digital twins will not only allow cities to respond to such abnormal weather events in real time, but also test countless potential risks. Emergencies of the future.” In such situations, the digital twin of the city will play a very important role, telling us which buildings will be flooded, which infrastructure will be closed, and which hospitals may be affected.
The construction of smart cities is still in the stage of theoretical experiments, and there are only a handful of regions that have truly realized digital twin smart cities. Although this work is being actively promoted across the country, most areas still prefer broadband network construction, IDC and IOT infrastructure construction, and have not introduced the emerging concept of smart cities. Professionals have made practical exploration and evaluation on the feasibility and reliability of the new digital twin city paradigm, and there have been successful benchmarking cases. It is believed that in the near future, the construction of digital twin smart cities will become mature and be promoted rapidly.
6.4 Smart water conservancy based on digital twin
As one of the six implementation paths to promote the high-quality development of water conservancy in the new stage, smart water conservancy construction takes digitization, networking, and intelligence as the main line, and takes digital scenarios, intelligent simulation, and precise decision-making as the path to comprehensively promote calculations and algorithms. , Computing power construction, accelerate the construction of a smart water conservancy system with the functions of forecasting, early warning, rehearsal, and pre-planning, and provide strong support and strong drive for the high-quality development of water conservancy in the new stage. Smart water conservancy is a new generation of information technology, such as cloud computing, Internet of Things, big data, mobile Internet and artificial intelligence, to conduct thorough perception of water conservancy objects and water conservancy activities, comprehensive interconnection, intelligent applications, ubiquitous services, information sharing, and promotion of water conservancy planning. The intelligentization of engineering construction, operation management and social services will drive the new concept and new model of the modernization of the water governance system and governance capabilities.
Smart water conservancy is the most significant symbol of the high-quality development of water conservancy in the new stage. The digital twin watershed is the core and key of smart water conservancy, and the digital twin water conservancy project is an important task for the construction of digital twin watersheds. Two examples of application scenarios are listed below.
(1) The comprehensive application of Ningbo Smart Water Conservancy Overall Smart Governance. In 2021, Ningbo Municipal Water Conservancy Bureau will build a "smart water conservancy" cloud environment relying on the Ningbo Municipal Affairs Cloud and the Municipal Space-Time Cloud Platform to realize data "cloud" sharing and front-end equipment "cloud" management and control, and comprehensively improve the intelligent level of water conservancy management in Ningbo. Successfully completed the task of the Ministry of Water Resources' smart water conservancy pilot project, and achieved the following three important results: ① Realize the dynamic advance forecast of floods in the whole basin and regional waterlogging; ② Realize the transformation of mountain torrent disasters from "monitoring and early warning" to "forecast and early warning"; Joint dispatch and operation of regional water conservancy facilities.
(2) Smart water conservancy digital system of Shuangxikou Reservoir. Shuangxikou Reservoir takes the watershed as the unit, the river system as the meridian, and the water conservancy project as the node. Through the smart water conservancy digital system of Shuangxikou Reservoir, a modern water conservancy infrastructure network platform is built to meet the new requirements of economic and social development in the new era. Make full use of a large number of hydrological real-time and thematic data resources, through various hydrological analysis calculation models and thematic results, greatly improve the timeliness of hydrological analysis and the visualization of analysis results, aiming to let management decision makers intuitively understand the current rainwater conditions and The process of change, the rainwater conditions and results that have occurred in the past and may occur in the future. Realize the three business scenarios of reservoir data information management, reservoir health comprehensive diagnosis and prediction, and reservoir optimal dispatching, and improve reservoir dispatching capabilities.
Although some small progress has been made in smart water conservancy based on digital twins, there are still some challenges and difficulties to be solved in the face of full implementation: ① Weak data foundation; ② Difficult multi-dimensional spatio-temporal analysis of data;
6.5 Smart grid based on digital twin
By integrating digital twin technology into the electric power field, the digital twin model of the electric power ecosystem can be created, and the data of the power grid system can be fully utilized: on the one hand, the mining and utilization of electric power data can benefit power users; on the other hand, it can also become Monitoring the security of the power system is also the core concept of the Internet of Things application in the power field.
During the development of power transmission and transformation projects, it is necessary to invest as much as possible in the means and concepts of digital twins to improve the quality and implementation effect of power transmission and transformation projects in the life cycle. In promoting the practical application of the twin model, it can be invested in quantitative evaluation, construction of fixed-point areas, resource reuse, and evaluation of design feasibility, etc., to realize the intelligentization of big data of power grid resources, improve the quality of power grid planning, and establish full business data of power grids The central interface realizes the intelligent handover of data, etc. Three application scenarios are listed below.
(1) Remote fault diagnosis and auxiliary decision-making applications. Traditional patrol inspections mainly rely on staff to go to the site to conduct patrol inspections, which is time-consuming and inefficient, and even problems cannot be found. With the popularization and application of digital twin modeling technology, on-site photos can be quickly obtained through drones and imported into the management platform to quickly generate on-site real-world models, and then use more realistic and standardized models to lock abnormal faults and truly achieve The purpose of remote inspection and problem identification.
(2) Visual monitoring application of power grid status environment. Based on the digital twin technology, the fine three-dimensional panoramic simulation of the main equipment, stations and environment of the power grid can realize real-time interaction with the collected data, and can dynamically integrate and display the equipment and key sensor data in the simulation scene. Through the video network and sensor network deployed in the plant, real-time feedback of environmental changes and real-time analysis. Based on the generated digital model, the data system of the 3D structure can be comprehensively analyzed. During the post-maintenance period of the platform, the power transmission and transformation project can be monitored in an all-round way through the digital twin model, so as to grasp the data of the working status of each device and view its overall change trend. Through the virtual space, the actual location of the substation, the basic parameters of the device and related design materials are displayed. This can not only improve the actual control effect and degree, but also effectively avoid the occurrence of abnormal situations, and buy more time for starting the accident emergency plan [32].
(3) Application of intelligent early warning and maintenance processing. During routine production, most workers in charge of control will analyze whether there is any difference in the device and the type of problem based on the accumulation of personal history. Obviously, this early warning and identification method is too dependent on personal ability, and there is also serious personal interference, which makes it impossible to accurately identify subtle changes in the device at the moment. Using the intelligent evaluation system, it is possible to continuously monitor the equipment in operation, and at the same time automatically analyze the working trajectory of the equipment, perceive abnormal signs in advance and take countermeasures to avoid serious problems and damage to a certain section or even the entire power grid. In addition, with the help of scientific and effective early warning, a more feasible maintenance plan can be designed.
Driven by the "dual carbon" strategy, the large-scale integration of wind power and photovoltaics has brought huge challenges to the planning, dispatching, and safe and stable operation of the new power system. Due to its refined and high-fidelity simulation of the physical grid, the digital twin grid has unique advantages in supporting grid planning and design, scheduling operation, and promoting the digital development of the power system. With the gradual maturity of emerging technologies such as big data, cloud computing, and blockchain, the security problems of digital twin technology can be gradually solved. Digital twin power grid will greatly improve the operation efficiency of power system and ensure the safety of power system operation. The construction of a new power system with new energy as the main body serves the implementation of the national "double carbon" strategy.
6.6 Transportation based on digital twin
As a basic, leading, and strategic industry in the national economy, transportation has gradually developed into a main supporting part that meets the basic needs of the people and the rapid development of the modern economy, and strongly supports and serves the people's better life. As a representative of the digitalization of physical products, digital twin technology optimizes the working mode of large-scale infrastructure projects from design, construction, management to later operation and maintenance; makes full use of data feedback to grasp changes in the physical world, and fundamentally solves the "information-physics" interaction The problem. Digital twin technology has further promoted the development of digitization, intelligence, and informatization in the field of transportation, which is of great significance to the development of the entire industry. Three application scenarios are listed below.
(1) Railway traffic management. Usually for the purpose of unified planning, unified scheduling and unified management of rail transit power supply, electrical works and housing construction, etc., a rail transit management platform based on digital twins is proposed to realize the integrated display of the whole line in the 3D scene, to achieve standardization, Digital and streamlined working mode. It mainly involves the construction of infrastructure comprehensive operation and maintenance management platform, intelligent passenger station and Li Sheng's scene of construction management work. The virtual environment of the station can not only display the real world, but also automatically generate disposal plans for abnormal events.
(2) Waterway transportation construction. In order to fully tap the potential of waterway transportation, a new generation of technical means such as digital twins and artificial intelligence is introduced to improve quality and efficiency from the perspective of top-level design and data fusion development. At the same time, faced with practical problems such as the shortage of waterway transportation personnel and the backwardness of waterway transportation tools, according to the characteristics of shipping and intelligent needs, with the overall goal of smooth information, accurate information, simple process, and adapting to future development, make full use of physical models, sensing technologies and Historical data, mapping and reflecting the operating status of waterway transportation facilities in the virtual world, can provide managers with a high-quality information management platform to assist the safe operation of waterway transportation vehicles.
(3) Air traffic applications. There are many main application scenarios of digital twin technology in aviation traffic, such as "test flight", under the superimposition of various mission parameters and abnormal environments, to study and verify the processing strategy designed in advance by the aircraft; to realize flight reproduction in the virtual environment, real-time Collect changes in load, temperature and structure, and use the data to reflect the real flight status; in the evaluation work after the failure or damage, accurately analyze the change of the sensor finger, diagnose the real cause of the abnormality, and generate a support plan under the failure situation; take charge of design correction analysis platform to verify the working conditions of vulnerable parts under abnormal conditions and improve the design scheme. Relevant data show that the application of digital Lisheng technology can reduce the maintenance cost of aircraft and increase its service life.
Adopt the concept of digitalization, map the virtual digital environment, improve the service quality of transportation, and promote the digital twin technology to form a Chinese solution in the field of comprehensive transportation.
7. Summary and Outlook
As an enabling technology and method to practice advanced concepts such as intelligent manufacturing, industry 4.0, industrial Internet, CPS, and smart city, digital twin technology can not only use human existing theories and knowledge to establish virtual models, but also use the Simulation technology explores and predicts the unknown world, discovers and seeks better methods and approaches, constantly stimulates human innovative thinking, and constantly pursues optimization and progress. It provides new ideas and tools for the innovation and development of the current industry, and has been recognized by the industry. and the growing attention of academia. This paper expounds the origin and definition of digital twin technology. At the same time, starting from the application requirements and based on the proposed digital twin five-dimensional structure model, it introduces six basic principles of digital twin driving and the digital twin standard system framework. Digital twin technology has been widely used in all walks of life. Six popular fields are listed, and the application of digital twin technology is briefly explained.
In the future, how to integrate with the new generation of information technology (NewIT) to make digital twin technology from theory to comprehensive application is the focus of the next stage of development and research of digital twin technology. The integration of digital twin technology with Internet of Things, 5G communication network, cloud computing, artificial intelligence, 3R, blockchain big data, etc. can be considered. The deep integration of digital twin with NewIT can realize the real and comprehensive perception of physical entities, multi-dimensional and multi-scale models Accurate construction, deep integration of all elements/full process/full business data, on-demand use of intelligent/humanized/personalized services and comprehensive/dynamic/real-time interaction. Although we have explained the framework of the digital twin standard system in the previous article, it is only a general theory, and no specific digital twin standard has been released yet. The development and application of digital twins require the guidance and reference of standards, and the designation of international standards for digital twins is also the top priority of current digital twin technology.
8. References
