CN-122019665-A - Intelligent sharing method and system for building data based on functional collaborative feedback

CN122019665ACN 122019665 ACN122019665 ACN 122019665ACN-122019665-A

Abstract

The invention provides a method and a system for intelligently sharing construction data based on functional collaborative feedback, which comprise the steps of collecting management data, constructing and updating a digital twin body in a ship and ocean engineering construction process based on the management data, identifying cross-department and/or cross-stage collaborative tasks based on the digital twin body, constructing a corresponding data demand model for each collaborative task, encoding the data demand model of the collaborative tasks and predefined triggering conditions into intelligent contracts, deploying the intelligent contracts into a permission blockchain network formed by construction participant nodes, and automatically executing the intelligent contracts when the digital twin body judges that the triggering conditions are met so as to directionally share the data specified by the data demand model among authorized nodes. The invention combines the business system data with the high-precision physical perception data, realizes the on-demand, automatic and tamper-proof directional sharing by utilizing the blockchain intelligent contract, thoroughly breaks the information island and establishes a trusted data flow channel.

Inventors

JI YONGJUN
WANG ZEXIN
Zhou Yunzhou
Liu Aosheng
LIN SHIGUANG

Assignees

上海外高桥造船海洋工程设计有限公司

Dates

Publication Date: 20260512
Application Date: 20260120

Claims (10)

1. An intelligent sharing method for building data based on functional collaborative feedback is characterized by comprising the following steps: collecting management data of design, production, logistics and quality in the whole process of ship and ocean engineering construction; constructing and updating a digital twin body of the ship and ocean engineering construction process based on the management data, wherein the digital twin body comprises geometric, physical, rule and real-time state information; Based on the digital twin body, identifying cross-department and/or cross-stage collaborative tasks, and constructing a corresponding data demand model for each collaborative task; Encoding the data demand model of the collaborative task and a predefined trigger condition into an intelligent contract and deploying the intelligent contract into a licensed blockchain network formed by building participant nodes, wherein when the digital twin body judges that the trigger condition is met, the intelligent contract is automatically executed so as to directionally share the data specified by the data demand model among authorized nodes; After the data sharing and the driving cooperative operation are completed, collecting effect data reflecting the operation result and the resource consumption; analyzing the effect data by using an artificial intelligent model to generate a quantitative evaluation result of the collaborative task; And dynamically optimizing parameters of the data demand model, triggering conditions of the intelligent contract and execution logic according to the quantitative evaluation result and real-time feedback data acquired from the digital twin and physical field.
2. The method of claim 1, wherein the collecting management data of design, production, logistics and quality throughout the ship and marine engineering construction comprises: acquiring electronic data of designs, plans, orders and documents from a business information system; monitoring welding deformation and residual stress distribution data in real time through a distributed optical fiber sensing network embedded or attached on the large-scale section and the structural member; Three-dimensional space coordinates and gesture data of high-value equipment and key components are continuously tracked in indoor and outdoor environments through a multi-mode positioning system integrating ultra-wideband, radio frequency identification and visual identification.
3. The method of claim 1, wherein the digital twin performs prospective simulation deductions in virtual space based on currently shared data prior to collaborative task triggering, the simulation deductions including process feasibility verification, physical space interferometry, and critical path construction period simulation; The digital twin body converts potential conflict found in simulation deduction into a structured early warning instruction and an optimization suggestion, and the structural early warning instruction and the optimization suggestion are directionally pushed to relevant responsible party nodes through the intelligent contract so as to drive the prepositive adjustment of the collaborative process.
4. The method of claim 1, wherein in the licensed blockchain network, each participant node's data access, write, and contract execution rights are bound to organizational roles and functions in the build project; Each time the data sharing transaction driven by the intelligent contract, the all-link records of the request, the authorization, the execution and the confirmation are encrypted and generate a non-tamperable block, so as to form a data operation certification and tracing chain.
5. The method of claim 1, wherein analyzing the effect data using an artificial intelligence model to generate a quantitative assessment of the collaborative task comprises: calculating a cooperative efficiency improvement coefficient and a resource waste reduction coefficient; determining the quantitative evaluation result according to the cooperative efficiency improvement coefficient and the resource waste reduction coefficient; The collaborative efficiency promotion coefficient is used for quantifying time-consuming optimization effects, and the resource waste reduction coefficient is used for quantifying cost control effects.
6. The method of claim 5, wherein the co-efficiency boost coefficient is calculated by: Wherein, the In order to cooperate with the efficiency-enhancing factor, Refers to the average time taken to complete the collaborative task in a historical same type or class of scenario, Refers to the actual time consumption of completing the collaborative task during the current execution; the calculation formula of the resource waste reduction coefficient is as follows: Wherein, the The coefficient is reduced for the waste of resources, Refers to the standard quota budget cost determined according to the standard process library, the man-hour quota and the bill of materials, Refers to the actual consumption cost acquired in real time through the internet of things system, Refers to dynamic adjustment factors related to task complexity, environmental risk factors.
7. The method according to claim 1, wherein the collaboration scenario in which the method is implemented includes: In a design release stage, the digital twin body performs manufacturability analysis based on the manufacturing capability data updated in real time, and synchronizes analysis results and modification suggestions to design department nodes through the intelligent contract; in the material supply stage, the digital twin body generates a distribution demand according to the real-time construction progress and the inventory prediction model, and automatically triggers the intelligent contract to issue a distribution instruction comprising a time window and a geofence to a provider node; In the quality closed loop, when the quality deviation is detected, a cross-department root analysis task is automatically initiated based on the blockchain storage certificate, and analysis conclusion and correction measures are fed back to a source link of design, process or purchase through the optimized data demand model.
8. An intelligent sharing system for building data based on functional collaborative feedback, comprising: the management data acquisition module is used for acquiring management data of design, production, logistics and quality in the whole process of ship and ocean engineering construction; The digital twin body construction module is used for constructing and updating a digital twin body of the ship and ocean engineering construction process based on the management data, and the digital twin body comprises geometric, physical, regular and real-time state information; the data demand model construction module is used for identifying cross-department and/or cross-stage collaborative tasks based on the digital twin body and constructing a corresponding data demand model for each collaborative task; The data sharing module is used for encoding the data demand model of the cooperative task and a predefined triggering condition into an intelligent contract and deploying the intelligent contract into a licensed blockchain network formed by building participant nodes, and when the digital twin judges that the triggering condition is met, the intelligent contract is automatically executed so as to directionally share the data specified by the data demand model among authorized nodes; The effect data acquisition module is used for acquiring effect data reflecting an operation result and resource consumption after the data sharing and the driving collaborative operation are completed; the quantitative evaluation result generation module is used for analyzing the effect data by utilizing an artificial intelligent model to generate a quantitative evaluation result of the cooperative task; And the dynamic optimization module is used for dynamically optimizing parameters of the data demand model, triggering conditions of the intelligent contract and execution logic according to the quantitative evaluation result and real-time feedback data acquired from the digital twin and physical field.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program when run performs the method of any one of claims 1 to 7.
10. An electronic device, the electronic device comprising: A processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any one of the preceding claims 1 to 7.

Description

Intelligent sharing method and system for building data based on functional collaborative feedback Technical Field The application relates to the technical field of ship and ocean engineering construction, in particular to an intelligent construction data sharing method and system based on functional collaborative feedback. Background The construction of ships and ocean engineering equipment (such as large container ships, liquefied natural gas ships, floating production, storage and unloading devices and the like) is typical complex product system engineering, and has the characteristics of long project period, numerous participants, complex process, intensive resources and the like. The current field faces various systematic technical problems in terms of data management and collaboration. Under the current multi-organization collaborative construction mode, each of the design institutes, the general assembly shipyard, the segmentation factory, the matched suppliers, the ship inspection institutions and the like runs an independent business information system. These systems have significant differences in data structure, standards, and interfaces, forming an information barrier that is difficult to open. More critical, the construction process involves huge capital and significant security responsibilities, and parties have extremely high requirements on the authenticity, integrity and non-tamperability of the data. In the current centralized data management mode, the storage and circulation of key engineering data (such as material authentication reports, nondestructive testing records and process parameters) depend on the internal systems of specific participants, and risks of being tampered or damaged by single parties exist. When quality accidents or contract disputes occur, the sources, circulation paths and related operational responsibilities of the problem data are difficult to objectively and efficiently trace, the responsibilities are difficult to define, and the disputes are high in cost. At the same time, the state of the physical construction site lacks real-time, accurate digital perception. The manager has difficulty in grasping key information such as actual welding deformation of the ship body section, accurate three-dimensional pose of large equipment, real-time capacity load of workshops, material inventory dynamic and the like. The prior art scheme is multifunctional and single, focuses on post-hoc recording and reporting, and belongs to a passive response type tool. The capability of carrying out virtual simulation and risk early warning on key operations such as hoisting, folding and the like to be carried out based on real-time data is lacking, and the adaptive optimization of the driving flow rule is not achieved through the deep analysis of the historical collaborative efficiency and the resource consumption mode. The improvement of the operation of the whole system highly depends on personal experience of management personnel, and an intelligent mechanism which is continuously self-perfected is not established. Although technologies such as the internet of things and big data have been applied in local links, the technologies are limited to single-function promotion, for example, only using a sensor to monitor the state of equipment, or only using a cloud platform to store documents in a centralized manner. The schemes fail to deeply fuse the new generation information technology with the core business flow of ship construction from the perspective of system engineering, and construct a full value chain of coverage design, production, logistics and quality management, and the integrated data collaboration system has intelligent perception, trusted sharing, prospective decision making and closed loop optimization capability. Therefore, developing an intelligent data sharing method and system capable of systematically solving the multi-dimensional problem becomes an urgent need for promoting the transformation and upgrading of the ship and ocean engineering construction industry to digital, networked and intelligent. Disclosure of Invention The invention aims to overcome the defects of the prior art, and provides an intelligent sharing method and system for building data based on functional collaborative feedback, so as to solve the problems of isolated data, unsmooth circulation and low reliability of each link of ship building in the prior art. In a first aspect, the present invention provides a method for intelligently sharing construction data based on functional collaborative feedback, which is characterized in that the method includes: collecting management data of design, production, logistics and quality in the whole process of ship and ocean engineering construction; constructing and updating a digital twin body of the ship and ocean engineering construction process based on the management data, wherein the digital twin body comprises geometric, physical, rule and real-tim