CN112084550B - Digital twin modeling method for intelligent hoisting process of prefabricated building components - Google Patents
Digital twin modeling method for intelligent hoisting process of prefabricated building components Download PDFInfo
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Abstract
The invention discloses a digital twin modeling method for an intelligent hoisting process of prefabricated components of an assembled building, which mainly comprises the steps of solid modeling, digital twin virtual body modeling and virtual-real interaction associated modeling of an assembled building construction site. The construction site entity modeling consists of intelligent hoisting component modeling, intelligent hoisting equipment modeling and intelligent gateway modeling, and construction site data acquisition is realized; the digital twin virtual body modeling carries out analog simulation on the construction site from four layers of geometry, physics, behavior and rules; the virtual-real interactive association modeling is to realize synchronous simulation of construction site solid modeling and digital twin virtual modeling through a data transmission protocol, and realize model-driven prediction and optimization. The invention can solve the problems of difficult mapping of data, redundant information, inadequacy, difficult searching and the like in the traditional assembly type building prefabricated part hoisting process, strengthens the control of the assembly type construction process, improves the construction efficiency and improves the informatization level of the assembly type hoisting process.
Description
Technical Field
The invention relates to the field of digital twin and building construction, in particular to a digital twin modeling method for an intelligent hoisting process of prefabricated building components.
Background
In recent years, china has become a great building country which is spotlighted, and the future China building industry is bound to take green, industrialized and informationized roads. The fabricated building is one of important paths for realizing the conversion from the traditional building mode to the modern industrialized building mode, and the technical level directly reflects the building capacity and technological strength of the country, so that the fabricated building is comprehensively promoted to be a great weight in the building industry. Along with the improvement of the industrialization degree, the technical level of the fabricated building is also continuously improved, such as the improvement of the prefabrication rate, the increase of the component body, the wider propulsion area, the increase of the hoisting height and the like, and the accompanying safety hazards in the aspects of hoisting operation, high-altitude falling objects and the like are brought into high importance to the industry. The hoisting management level of the fabricated building construction is improved, and the method has important significance for promoting the development of the fabricated building towards the healthy and sustainable directions and for economic construction and social stability of China.
Digital twin is a key enabling technology for solving the difficult problem of intelligent manufacturing information physical fusion and the aim of trampling intelligent manufacturing concepts, is widely focused and researched in academia, and is introduced into the building industry for landing application by the industry. Digital twin is a key enabling technology for solving the physical fusion problem of intelligent manufacturing information and trampling intelligent manufacturing concepts and targets, is widely focused and researched in academia, and is introduced into more and more fields for landing application by the industry. The primary task of digital twinning applications is to create a digital twinning model of the application object.
Therefore, the establishment of the digital twin model is a precondition of applying the digital twin concept in the building construction stage, and the standardized establishment method of the digital twin model is one of key problems to be solved urgently.
Along with the continuous improvement of informatization requirements of the assembly type hoisting process, the digital twin is used as an informatization solution with universality, so that the informatization level of the assembly type hoisting process can be greatly improved. On the basis of the method, the invention provides a digital twin modeling method for an intelligent hoisting process of prefabricated components of an assembled building, and compared with the traditional hoisting process of prefabricated components of the assembled building, the method has the following three advantages:
(1) Clearly and comprehensively showing the logic relation of the data in the hoisting process of the fabricated building.
(2) All information of the assembly type hoisting process is collected, stored and processed, so that the control of the assembly type construction process is enhanced, and the construction efficiency is improved.
(3) The defects that the traditional assembly type hoisting process is difficult to map, has redundant information, is not intuitive enough and is difficult to find are overcome, and the informatization level of the assembly type hoisting process is improved.
Disclosure of Invention
The invention aims to solve the problems that data are difficult to map, information is redundant, visual and difficult to find in the hoisting process of the traditional prefabricated building components, and logic is disordered in the information collecting, storing and processing processes.
The digital twin modeling method for the intelligent hoisting process of the prefabricated building components clearly and comprehensively displays the logical relationship of data in the hoisting process of the prefabricated building. All information of the assembly type hoisting process is collected, stored and processed, so that the control of the assembly type construction process is enhanced, and the construction efficiency is improved.
The defects that the traditional assembly type hoisting process is difficult to map, has redundant information, is not intuitive enough and is difficult to find are overcome, and the informatization level of the assembly type hoisting process is improved.
In order to solve the technical problems, the technical scheme adopted is as follows:
the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the construction site entity modeling consists of intelligent hoisting component modeling, intelligent hoisting equipment modeling and intelligent gateway modeling, and construction site data acquisition is realized;
the digital twin virtual body modeling carries out analog simulation on the construction site from four layers of geometry, physics, behavior and rules;
the virtual-real interactive association modeling is to realize synchronous simulation of construction site solid modeling and digital twin virtual modeling through a data transmission protocol, and realize model-driven prediction and optimization.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the intelligent hoisting component consists of a component, an active RFID tag and an embedded terminal X.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the types of the components mainly comprise laminated slabs, stairs, walls, balconies and the like.
The RFID tag is closely attached to the member, and the unique number of the member and the entire characteristic information of the member can be identified by scanning the RFID tag.
The embedded terminal X adopts STEM32, integrates real-time data acquisition and preprocessing APP, and is used for real-time sensing of environment and component states, data storage, calculation and transmission.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the intelligent hoisting equipment consists of equipment, heterogeneous sensors, an actuator, a controller and an embedded terminal Y.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the equipment itself mainly comprises a crane, a transverse hanging beam and the like
The heterogeneous sensor mainly collects position data S, speed data V, stress data F, energy consumption data E, visual data I, voice data L and the like.
The executor and the controller receive the execution instruction and the control instruction, and realize the execution and control of the assembly type prefabricated part hoisting automation.
The embedded terminal Y requests data from the sensor in a request form by calling the real-time data acquisition preprocessing APP, so that non-redundant storage, edge calculation and transmission communication, autonomous analysis and decision-making of real-time data related to the hoisting equipment are realized.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the intelligent gateway adopts embedded equipment such as RPI and the like, and establishes connection with the bottom intelligent manufacturing equipment through communication protocols such as MTConnect, automationML, OPC UA and the like.
The intelligent gateway integrates the intelligent hoisting component and the data on the embedded terminal X and the embedded terminal Y on the intelligent hoisting equipment, and the data is transmitted in a JSON format and stored in a cloud NoSQL public database according to the authority and the hierarchy. The intelligent gateway is connected with the intelligent hoisting component and the intelligent hoisting equipment in a wireless mode such as Zigbee, WIFI, bluetooth and the like.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the digital twin virtual body modeling carries out analog simulation on the construction site from four layers of geometry, physics, behavior and rules.
The geometric layer is mainly modeled aiming at basic information such as appearance, size, model and the like of the hoisting member and the hoisting equipment, and a geometric model is built by mainly applying BIM modeling software such as Revit, 3Dsmax and the like.
The physical layer is mainly modeled aiming at the aspects of material parameters, mechanical properties and the like of the hoisting member and the hoisting equipment, and a physical model is established by mainly applying finite element analysis software such as midas, ansys and the like.
The behavior layer carries out the time-space evolution simulation on the whole hoisting process to obtain the change of material parameters and mechanical properties in the time-space evolution process, and the material parameters and the mechanical properties are integrated into a physical model in a parameterized mode.
The rule model limits the mechanical performance parameters of the components and the running state of the equipment in the hoisting process quantitatively according to the national standard specification, and is integrated into the physical model in a parameterized mode.
Further, the digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the virtual-real interactive correlation model is implemented through a high-speed, high-stability and low-delay data transmission protocol (such as DDS, MQTT, HTTP and the like). The virtual-real interaction correlation model synchronizes real-time data such as component parameters, equipment running states, environmental changes and the like in the entity model of the assembly type building hoisting construction site to the digital twin virtual body model and stores the digital twin virtual body model in a public database according to security rights, so that the digital twin virtual body model realizes synchronous simulation.
The virtual-real interaction correlation model applies algorithms such as BP neural network, SVM, deep learning and the like to form real-time judgment, analysis and prediction of the hoisting process, and realizes self-perception, self-decision and self-control of the entity of the hoisting construction site of the fabricated building.
Compared with the prior art, the invention clearly and comprehensively displays the logic relationship of the data in the hoisting process of the assembled building. All information of the assembly type hoisting process is collected, stored and processed, so that the control of the assembly type construction process is enhanced, and the construction efficiency is improved. The defects that the traditional assembly type hoisting process is difficult to map, has redundant information, is not intuitive enough and is difficult to find are overcome, and the informatization level of the assembly type hoisting process is improved.
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FIG. 1 is a flow chart of a digital twin modeling method for an intelligent hoisting process of prefabricated building components.
Detailed Description
The present invention will be described in further detail with reference to examples for the purpose of making the objects, technical solutions and advantages of the present invention more clear. 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.
Implementation example:
taking the hoisting process of a typical component-superimposed sheet of an assembly type construction site as an example.
Firstly, intelligent hoisting superimposed sheet modeling.
The intelligence guarantees that the superimposed sheet accords with the quality requirement in superimposed sheet manufacturing process. And an active RFID tag and an embedded terminal X are closely attached to the laminated slab to form the intelligent hoisting laminated slab. The unique number of the superimposed sheet and all characteristic information of the manufacturer, the production place, the material, the size and the like of the superimposed sheet can be identified by scanning the RFID tag. The embedded terminal X adopts STEM32, integrates real-time data acquisition and preprocessing APP, senses information such as position, stress strain and wind speed of the laminated slab in real time, and stores, calculates and transmits the data.
Second, intelligent crane modeling.
And arranging a heterogeneous sensor, an actuator, a controller and an embedded terminal Y on the crane to form intelligent hoisting equipment. The heterogeneous sensor mainly collects position data S of a lifting hook, lifting speed data V, lifting rope stress data F, crane energy consumption data E, other visual data I, voice data L and the like. The executor and the controller receive the execution instruction and the control instruction, and realize the execution and control of the superimposed sheet hoisting automation. The embedded terminal Y requests data from the sensor in a request form by calling the real-time data acquisition preprocessing APP, so that non-redundant storage, edge calculation and transmission communication, autonomous analysis and decision-making of crane-related real-time data are realized.
Then, intelligent gateway modeling is performed.
The intelligent gateway adopts embedded equipment such as RPI and the like, and establishes connection with the bottom intelligent manufacturing equipment through communication protocols such as MTConnect, automationML, OPC UA and the like. And the intelligent gateway integrates the intelligent superimposed sheet and the data on the embedded terminal X and the embedded terminal Y on the intelligent crane, and the data is transmitted in a JSON format and stored in a cloud NoSQL public database according to the authority and the hierarchy. The intelligent gateway is connected with the intelligent hoisting component and the intelligent hoisting equipment in a WIFI mode.
Next, digital twin virtual body modeling is performed.
And overlapping the slab and the crane geometric model by using Revit modeling software. The superimposed sheet geometric model comprises all characteristic information such as manufacturers, production places, materials, sizes and the like, and corresponds to the information of the active RFID labels on the superimposed sheet; the crane geometric model comprises all information of tonnage, model, span, lifting height and the like. And building a physical model of the laminated slab and the crane by using midas finite element analysis software. The superimposed sheet physical model mainly comprises information such as materials, stress strain and the like; the crane physical model mainly comprises the information. The behavior layer carries out the time-space evolution simulation on the whole hoisting process to obtain the change of material parameters and mechanical properties of the superimposed sheet in the time-space evolution process, the change of the position of a crane hook, the hoisting speed, the stress of a hoisting rope and the energy consumption, and the changes are integrated into a physical model in a parameterized mode. The rule model limits the mechanical property parameters of the superimposed sheet and the crane running state in the hoisting process in a quantitative manner according to the national standard specification, and is integrated into the physical model in a parameterized manner.
After hoisting is started, real-time data such as superimposed sheet parameters, crane running states, environmental changes and the like in the entity model of the assembled building hoisting construction site are synchronized to a digital twin virtual body model by the virtual-real interaction correlation model through a high-speed, high-stability and low-delay data transmission protocol (such as DDS, MQTT, HTTP and the like), and the digital twin virtual body model is stored in a public database according to security rights, so that synchronous simulation is realized by the digital twin virtual body model. And (3) performing real-time judgment, analysis and prediction on the hoisting process of the superimposed sheet by using algorithms such as BP neural network, SVM, deep learning and the like, and realizing self-sensing, self-decision and self-control on the entity of the hoisting construction site of the fabricated building.
While the foregoing describes the illustrative embodiments of the present invention so that those skilled in the art may understand the present invention, the present invention is not limited to the specific embodiments, and all inventive innovations utilizing the inventive concepts are herein within the scope of the present invention as defined and defined by the appended claims, as long as the various changes are within the spirit and scope of the present invention.
Claims (1)
1. The digital twin modeling method for the intelligent hoisting process of the prefabricated building components is characterized by comprising the following steps of:
the construction site entity modeling of the intelligent hoisting of the prefabricated building components consists of intelligent hoisting components, intelligent hoisting equipment and an intelligent gateway, so that the intelligent hoisting construction site data acquisition of the prefabricated building components is realized;
the digital twin virtual modeling is used for carrying out analog simulation on the intelligent hoisting construction site of the prefabricated building components from four layers of geometry, physics, behavior and rules;
the virtual-real interaction associated modeling is to realize synchronous simulation of the intelligent hoisting construction site entity modeling and the digital twin virtual modeling of prefabricated parts of the fabricated building through a data transmission protocol, so as to realize model-driven prediction and optimization;
the intelligent hoisting component of the assembled building consists of a component, an active RFID tag and an embedded terminal X;
the intelligent hoisting components of the assembled building comprise superimposed sheets, stairs, walls and balconies;
the RFID tag is closely attached to the intelligent hoisting component of the assembled building, and the unique number of the intelligent hoisting component of the assembled building and all characteristic information of the intelligent hoisting component of the assembled building are identified by scanning the RFID tag;
the embedded terminal X adopts STEM32, integrates real-time data acquisition and preprocessing APP, and is used for real-time sensing of environment and component states, data storage, calculation and transmission;
the intelligent hoisting equipment consists of equipment, heterogeneous sensors, an actuator, a controller and an embedded terminal Y;
the hoisting equipment comprises a crane and a transverse hanging beam;
the heterogeneous sensor acquires position data S, speed data V, stress data F, energy consumption data E, visual data I and voice data L;
the executor and the controller receive the execution instruction and the control instruction, so that the execution and the control of the assembly type prefabricated part hoisting automation are realized;
the embedded terminal Y requests data from the sensor in a request form by calling the real-time data acquisition preprocessing APP, so that non-redundant storage, edge calculation and transmission communication of real-time data related to the hoisting equipment are realized, and autonomous analysis and decision are performed;
the intelligent gateway adopts RPI embedded equipment and establishes connection with the bottom intelligent manufacturing equipment through MTConnect, automationML or OPC UA communication protocol;
the intelligent gateway integrates the intelligent hoisting component and the data on the embedded terminal X and the embedded terminal Y on the intelligent hoisting equipment, and the data is transmitted in a JSON format and stored in a cloud NoSQL public database according to the authority and the hierarchy;
the intelligent gateway is connected with the intelligent hoisting component and the intelligent hoisting equipment in a Zigbee, WIFI or Bluetooth wireless mode;
the digital twin virtual body modeling carries out analog simulation on the construction site from four layers of geometry, physics, behavior and rules;
modeling is carried out on basic information of appearance, size and model of the hoisting member and hoisting equipment by a geometric layer, and a geometric model is established by applying Revit and 3DsmaxBIM modeling software;
modeling is carried out on the aspect of material parameters and mechanical properties of the hoisting member and the hoisting equipment on a physical layer, and a physical model is established by applying midas and ansys finite element analysis software;
performing time-space evolution simulation on the whole hoisting process by a behavior layer to obtain the change of material parameters and mechanical properties in the time-space evolution process, and integrating the material parameters and the mechanical properties into a physical model in a parameterized mode;
the rule model carries out quantitative limitation on mechanical performance parameters and equipment running states of components in the hoisting process according to national standard specifications, and is integrated into a physical model in a parameterized mode;
the virtual-real interaction association model passes through a data transmission protocol; the virtual-real interaction correlation model synchronizes real-time data of component parameters, equipment running states and environmental changes in the entity model of the assembly type building hoisting construction site to the digital twin virtual model and stores the digital twin virtual model in a public database according to security rights, so that the digital twin virtual model realizes synchronous simulation;
and the virtual-real interaction correlation model applies BP neural network, SVM and deep learning algorithm to form real-time judgment, analysis and prediction of the hoisting process, and realizes self-perception, self-decision and self-control of the entity of the hoisting construction site of the fabricated building.
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| CN112419799B (en) * | 2020-12-25 | 2023-05-23 | 山东盈先信息科技有限公司 | Intelligent perception virtual-real interaction practical training system and method for assembled building |
| CN113047548B (en) * | 2021-03-10 | 2022-04-29 | 陕西华山建设集团有限公司 | Hoisting construction method for steel stairs in irregular plate column shear wall structure |
| CN113110313A (en) * | 2021-03-26 | 2021-07-13 | 广东建设职业技术学院 | Construction process control method based on digital twinning |
| CN115271269B (en) * | 2022-09-28 | 2022-12-16 | 中化学起重运输有限公司 | BIM-based large prefabricated part hoisting safety control method |
| CN115329446B (en) * | 2022-10-13 | 2023-01-31 | 江苏航运职业技术学院 | Digital twinning modeling method for intelligent hoisting process of prefabricated parts of fabricated building |
| CN117236054B (en) * | 2023-10-08 | 2024-11-01 | 苏州诺克智能装备股份有限公司 | Automobile welding fixture assembly method, system and medium based on digital twin |
| CN118427907B (en) * | 2024-07-05 | 2024-09-10 | 深圳市烨兴智能空间技术有限公司 | Digital twinning-based multi-curved-surface special-shaped film structure installation method and device |
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