Digital model construction and management system and method for full life cycle of infrastructure

Abstract

The invention relates to the technical field of facility safety, in particular to a digital model construction and management system and method for the whole life cycle of infrastructure. Comprising a data collection and preprocessing module, a digital model construction module, a model management and updating module, an analysis and simulation module, an operation and maintenance management module, a decision support module and a system integration and interface module. By integrating a plurality of modules, construction and management of the digital model of the whole life cycle of the infrastructure are realized, the accuracy and consistency of data are remarkably improved, accurate construction and efficient management of the three-dimensional digital model are ensured, and meanwhile, through real-time monitoring and analysis, the real-time monitoring and management of the three-dimensional digital model are realized. Potential problems can be found in time, early warning and maintenance can be carried out, powerful decision support is provided for planning, design, construction and operation and maintenance of infrastructures, data sharing with other systems is achieved through the system integration and interface module, and the overall management efficiency and cooperative work capacity are further improved.

Description

Technical Field

[0001] The present invention relates to the field of facility safety technology, and in particular to a digital model building and management system and method for the entire life cycle of infrastructure. Background Art

[0002] Infrastructure is the cornerstone of urban and social development, and its planning, design, construction, operation and maintenance are all crucial. Traditional management methods often have problems such as inaccurate data, imprecise model construction, and low management efficiency, which cannot meet the needs of modern infrastructure management. Therefore, a more efficient and accurate management method is needed to improve the management level of infrastructure.

[0003] Secondly, with the continuous development of digital technology, especially the widespread application of BIM (Building Information Modeling), Internet of Things, cloud computing and other technologies, new technical means are provided for the full life cycle management of infrastructure. These technologies can realize real-time data collection, processing and analysis, build accurate three-dimensional digital models, and realize efficient management and updating of models. At the same time, through system integration and interface modules, data sharing and interaction with other systems can also be realized, further improving the overall management efficiency and collaborative work ability.

[0004] However, despite the huge potential of digital technology in infrastructure management, there are still many challenges in practical application. For example, how to ensure the accuracy and consistency of data, how to build accurate three-dimensional digital models, how to achieve efficient management and update of models, and how to timely discover potential problems and conduct early warning and maintenance through real-time monitoring and analysis. These problems need to be solved through technological innovation and method improvement.

[0005] Therefore, this invention patent proposes a digital model construction and management system for the entire life cycle of infrastructure, which aims to achieve digital management of the entire life cycle of infrastructure by integrating multiple modules and functions, improve data accuracy and consistency, ensure the precise construction and efficient management of three-dimensional digital models, and provide strong decision support through real-time monitoring and analysis. This technical solution not only meets the needs of modern infrastructure management, but also promotes the in-depth application and development of digital technology in the field of infrastructure management. Summary of the invention

[0006] The purpose of the present invention is to provide a system and method for building and managing a digital model of an infrastructure throughout its entire life cycle, so as to solve the problems raised in the above-mentioned background technology.

[0007] The technical solution of the present invention is:

[0008] In one aspect, a digital model construction and management system for the entire life cycle of infrastructure includes:

[0009] The data collection and preprocessing module is used to collect various data of the infrastructure throughout its life cycle and perform preprocessing to ensure the accuracy and consistency of the data. The various data of the infrastructure throughout its life cycle include geometric information, material information, construction information, and operation and maintenance information.

[0010] A digital model building module, which is used to build a three-dimensional digital model of the infrastructure based on the pre-processed data using advanced modeling techniques and tools, wherein the constructed three-dimensional digital model contains the geometric shape, structural characteristics and material property information of the infrastructure;

[0011] The model management and update module is used to store, manage and update digital models using an efficient database management system. It also supports model version control and can record historical versions of the model for easy tracking and backtracking.

[0012] Analysis and simulation module, which is used to perform various analyses and simulations using digital models, including structural analysis, energy consumption analysis and traffic flow simulation;

[0013] The operation and maintenance management module is used to discover potential problems of infrastructure through real-time monitoring and analysis of data in the digital model, and to carry out early warning and maintenance, thereby managing the operation and maintenance of infrastructure, including daily maintenance, fault warning and maintenance plan formulation;

[0014] Decision support module, which is used to provide decision support for the planning, design, construction and operation and maintenance of infrastructure throughout its life cycle based on digital models and analysis results;

[0015] The system integration and interface module is responsible for integrating the above modules, ensuring data exchange and collaborative work between them, and providing interfaces with other systems to achieve data sharing and interaction.

[0016] Preferably, the data collection and preprocessing module collects various types of data of the infrastructure throughout its life cycle and performs preprocessing to ensure the accuracy and consistency of the data, including the following steps:

[0017] S11: Determine the data source. First, you need to identify the source of the required data, which includes sensors, IoT devices, historical documents, and field surveys.

[0018] S12: Data collection, using appropriate methods and techniques to collect data based on the identified sources;

[0019] S13: Data preprocessing: According to the type and category of data, select appropriate data preprocessing methods to preprocess the collected data to ensure the quality and availability of the data.

[0020] Preferably, the data collection and preprocessing module selects a suitable data preprocessing method according to the type and category of the data, preprocesses the collected data, and ensures the quality and availability of the data. The data preprocessing methods used include:

[0021] A11: Data cleaning includes removing duplicate data, processing missing values ​​and correcting erroneous data. Missing data is processed by deletion, filling and interpolation methods.

[0022] A12: Data format conversion includes data type conversion, data standardization, data normalization and data encoding. The principle formula for data standardization is:

[0023] z=(x-μ) / σ;

[0024] Among them, z is the data after standardization, x is the original data, μ is the mean, and σ is the standard deviation;

[0025] The principle formula for normalizing data is:

[0026] x' = (x-min) / (max-min);

[0027] Among them, x' is the data after normalization, x is the original data, min and max are the minimum and maximum values ​​in the data set respectively;

[0028] A13: Data verification includes data consistency check, logic check and statistical check, which verifies the accuracy and consistency of data.

[0029] Preferably, the digital model building module comprises the following steps when building a three-dimensional digital model of the infrastructure based on the pre-processed data using advanced modeling techniques and tools:

[0030] S21: Select modeling techniques and tools. Select appropriate modeling techniques and tools based on the characteristics and needs of the infrastructure.

[0031] S22: Data import and integration: import the pre-processed data into the modeling tool and perform data integration to ensure data integrity and consistency;

[0032] S23: Model construction, using modeling tools to construct a three-dimensional digital model of the infrastructure based on the imported data;

[0033] S24: Model verification and optimization: verify the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure, and optimize the model to improve its accuracy and reliability.

[0034] Preferably, the digital model building module imports the pre-processed data into the modeling tool and integrates the data to ensure the integrity and consistency of the data, and performs data integration through the following steps:

[0035] S31: Data extraction, selecting and extracting required data from various data sources;

[0036] S32: Data transmission, sending the extracted data subset to the target location;

[0037] S33: Data reorganization: associate the cleaned data according to the new data organization logic to strengthen the internal connection of the data;

[0038] S34: Data publishing: publishing the integrated data to the corresponding database and data warehouse as required for subsequent use.

[0039] Preferably, when the digital model building module associates the cleaned data according to the new data organization logic and strengthens the internal connection of the data, the data fusion method used includes:

[0040] A21: Weighted average method, by assigning different weights to different data sources, and then performing weighted summation to obtain the final fusion result. Its principle formula is:

[0041]

[0042] Among them, is the result after fusion, ω i is the weight of the ith data source, x i is the value of the i-th data source;

[0043] A22: The Bayesian method is based on probability theory and updates the understanding and prediction of data by calculating the posterior probability. Its principle formula is:

[0044]

[0045] Among them, P(A|B) represents the probability of A given B, and P(B|A) represents the probability of B given A. and P(B) represent the prior probabilities of A and B respectively.

[0046] Preferably, the digital model building module uses an optimization algorithm to minimize the loss function when verifying the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure and optimizing the model to improve the accuracy and reliability of the model. The principle formula of the optimization algorithm used is:

[0047]

[0048] Among them, θ j are the parameters of the model, α is the learning rate, J(θ) is the loss function, is the loss function for the parameter θ j The partial derivative of θ j The new value of is assigned to the original θ j .

[0049] Preferably, the model management and update module includes the following steps when using an efficient database management system to store, manage and update the digital model:

[0050] S41: Model storage. First, select a suitable database system for storage according to the model type, size, complexity and usage requirements, and regularly back up model data to prevent data loss or damage. At the same time, establish a data recovery mechanism so that the model data can be quickly restored when necessary. Finally, control the access to the model data to ensure that only authorized users can access and modify the model data. The selectable database systems include relational databases and non-relational databases.

[0051] S42: Model management, including version control, classification management and tag management. Version control is to record the historical versions of the model, including the modification time, modification content and modification personnel of each version. Classification management is to classify the model according to the model type, purpose and business field factors. Tag management is to add tags to the model for subsequent query and screening.

[0052] S43: Version updates, including partial modifications, reconstruction and regular updates. Regular updates are to determine the frequency and timing of model updates based on infrastructure reconstruction, expansion, maintenance plans and changes in business needs to ensure that the model can reflect changes in actual conditions in a timely manner.

[0053] Preferably, when the analysis and simulation module uses the digital model to perform various analyses and simulations, the principle steps are as follows:

[0054] S51: Determine the analysis objectives and the types of analysis and simulations that need to be performed based on the characteristics and needs of the infrastructure;

[0055] S52: Model setting and parameter adjustment, setting model parameters in analysis and simulation tools to ensure that the model can accurately reflect the actual situation;

[0056] S53: Run analysis and simulation, use analysis and simulation tools to run the model and perform the required analysis and simulation;

[0057] S54: Result analysis and interpretation: interpret and analyze the analysis and simulation results to extract useful information and conclusions. The analysis of the analysis and simulation results includes data visualization, trend analysis and sensitivity analysis.

[0058] Preferably, the operation and maintenance management module includes the following steps when performing operation and maintenance management of the infrastructure by real-time monitoring and analyzing the data in the digital model, discovering potential problems of the infrastructure, and performing early warning and maintenance in advance:

[0059] S61: Real-time monitoring, using sensors and IoT technologies to monitor the status and performance of infrastructure in real time;

[0060] S62: Fault warning: Based on real-time monitoring data and analysis results, fault warning is carried out, and when potential problems are found, warning signals are issued in time so that corresponding countermeasures can be taken;

[0061] S63: Maintenance plan formulation: According to the fault warning and actual situation, a maintenance plan is formulated, which includes determining the maintenance time, maintenance content and required resources;

[0062] S64: Maintenance execution and tracking, execute the maintenance plan, and track and record the maintenance process.

[0063] On the other hand, a method for building and managing a digital model of the entire life cycle of infrastructure includes the following steps:

[0064] S71: Project initiation and requirements analysis, determine project goals, scope and stakeholders, and conduct requirements analysis;

[0065] S72: Conceptual design and preliminary planning: Based on the results of the demand analysis, conduct conceptual design and develop preliminary planning, including schedule, budget and resource allocation;

[0066] S73: Detailed design and modeling, using BIM and other digital tools for detailed design and building three-dimensional models;

[0067] S74: Collaborative design and optimization, through the cloud platform to achieve multi-party collaboration among designers, engineers and construction personnel, and to optimize the design, resolve conflicts and improve the design quality;

[0068] S75: Digital model update and verification: Update the digital model in a timely manner and use simulation and verification tools to verify the updated model to ensure the consistency between the model and the actual situation.

[0069] Beneficial effects of the present invention:

[0070] 1. By integrating multiple modules such as data collection and preprocessing, digital model construction, model management and update, analysis and simulation, operation and maintenance management, decision support, and system integration and interface, the digital model construction and management of the entire life cycle of infrastructure is realized. This technical solution significantly improves the accuracy and consistency of data, ensures the precise construction and efficient management of three-dimensional digital models, and through real-time monitoring and analysis, it can timely discover potential problems and conduct early warning and maintenance, providing strong decision support for infrastructure planning, design, construction and operation and maintenance. In addition, the solution also realizes data sharing and interaction with other systems through system integration and interface modules, further improving the overall management efficiency and collaborative work ability;

[0071] 2. By using the optimization algorithm, combining the learning rate and loss function to iteratively update the model parameters, the loss function is effectively minimized, thereby achieving accurate verification and optimization of the constructed model, significantly improving the accuracy and reliability of the model, ensuring that the model can be highly consistent with the actual conditions of the infrastructure, and providing strong digital support for the full life cycle management of the infrastructure;

[0072] 3. By clarifying the analysis objectives, accurately setting model parameters, efficiently running analysis and simulation tools, and conducting in-depth analysis and visualization of the results, a comprehensive and accurate analysis and simulation of infrastructure is achieved. This solution not only improves the accuracy and efficiency of analysis and simulation, but also deeply explores the useful information in the results through data visualization, trend analysis and sensitivity analysis, providing strong decision-making support for infrastructure planning, design, construction and operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 What is shown is a schematic diagram of the construction of a digital model and management system for the entire life cycle of infrastructure of the present invention;

[0074] Figure 2 What is presented is a flow chart of the method for building and managing a digital model of the entire life cycle of infrastructure according to the present invention. DETAILED DESCRIPTION

[0075] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0076] See also Figure 1The present invention provides an embodiment: a digital model construction and management system for the entire life cycle of infrastructure, including:

[0077] The data collection and preprocessing module is used to collect various data of the infrastructure throughout its life cycle and perform preprocessing to ensure the accuracy and consistency of the data. The various data of the infrastructure throughout its life cycle include geometric information, material information, construction information, and operation and maintenance information.

[0078] A digital model building module, which is used to build a three-dimensional digital model of the infrastructure based on the pre-processed data using advanced modeling techniques and tools, wherein the constructed three-dimensional digital model contains the geometric shape, structural characteristics and material property information of the infrastructure;

[0079] The model management and update module is used to store, manage and update digital models using an efficient database management system. It also supports model version control and can record historical versions of the model for easy tracking and backtracking.

[0080] Analysis and simulation module, which is used to perform various analyses and simulations using digital models, including structural analysis, energy consumption analysis and traffic flow simulation;

[0081] The operation and maintenance management module is used to discover potential problems of infrastructure through real-time monitoring and analysis of data in the digital model, and to carry out early warning and maintenance, thereby managing the operation and maintenance of infrastructure, including daily maintenance, fault warning and maintenance plan formulation;

[0082] Decision support module, which is used to provide decision support for the planning, design, construction and operation and maintenance of infrastructure throughout its life cycle based on digital models and analysis results;

[0083] The system integration and interface module is responsible for integrating the above modules, ensuring data exchange and collaborative work between them, and providing interfaces with other systems to achieve data sharing and interaction.

[0084] Through the above steps, the present invention realizes the digital model construction and management of the entire life cycle of infrastructure by integrating multiple modules such as data collection and preprocessing, digital model construction, model management and updating, analysis and simulation, operation and maintenance management, decision support, and system integration and interface. This technical solution significantly improves the accuracy and consistency of data, ensures the precise construction and efficient management of three-dimensional digital models, and through real-time monitoring and analysis, it can timely discover potential problems and carry out early warning and maintenance, providing strong decision-making support for infrastructure planning, design, construction and operation and maintenance. In addition, the solution also realizes data sharing and interaction with other systems through system integration and interface modules, further improving the overall management efficiency and collaborative work ability.

[0085] Preferably, the data collection and preprocessing module collects various types of data of the infrastructure throughout its life cycle and performs preprocessing to ensure the accuracy and consistency of the data, including the following steps:

[0086] S11: Determine the data source. First, you need to identify the source of the required data, which includes sensors, IoT devices, historical documents, and field surveys.

[0087] S12: Data collection, using appropriate methods and techniques to collect data based on the identified sources;

[0088] S13: Data preprocessing: According to the type and category of data, select appropriate data preprocessing methods to preprocess the collected data to ensure the quality and availability of the data.

[0089] Through the above steps, the present invention ensures the accuracy and consistency of various types of data throughout the life cycle of the infrastructure by clarifying the data sources (including sensors, IoT devices, historical documents and field surveys), using appropriate methods and technologies to collect data, and selecting appropriate data preprocessing methods based on the data type. This technical solution effectively improves the quality and availability of data, and lays a solid foundation for the construction and management of subsequent digital models.

[0090] Preferably, the data collection and preprocessing module selects a suitable data preprocessing method according to the type and category of the data, preprocesses the collected data, and ensures the quality and availability of the data. The data preprocessing methods used include:

[0091] A11: Data cleaning includes removing duplicate data, processing missing values ​​and correcting erroneous data. Missing data is processed by deletion, filling and interpolation methods.

[0092] A12: Data format conversion includes data type conversion, data standardization, data normalization and data encoding. The principle formula for data standardization is:

[0093] z=(x-μ) / σ;

[0094] Among them, z is the data after standardization, x is the original data, μ is the mean, and σ is the standard deviation;

[0095] The principle formula for normalizing data is:

[0096] x' = (x-min) / (max-min);

[0097] Among them, x' is the data after normalization, x is the original data, min and max are the minimum and maximum values ​​in the data set respectively;

[0098] A13: Data verification includes data consistency check, logic check and statistical check, which verifies the accuracy and consistency of data.

[0099] Through the above steps, the present invention significantly improves the quality and availability of collected data by implementing preprocessing steps such as data cleaning (removing duplications, filling in missing data, and correcting errors), data format conversion (including type conversion, standardization, normalization, and encoding, wherein standardization uses the z-score formula and normalization uses the minimum-maximum scaling method), and data verification (consistency, logic, and statistical verification), ensures the accuracy and consistency of the data, and provides a reliable foundation for subsequent data analysis and model building.

[0100] Preferably, the digital model building module comprises the following steps when building a three-dimensional digital model of the infrastructure based on the pre-processed data using advanced modeling techniques and tools:

[0101] S21: Select modeling techniques and tools. Select appropriate modeling techniques and tools based on the characteristics and needs of the infrastructure.

[0102] S22: Data import and integration: import the pre-processed data into the modeling tool and perform data integration to ensure data integrity and consistency;

[0103] S23: Model construction, using modeling tools to construct a three-dimensional digital model of the infrastructure based on the imported data;

[0104] S24: Model verification and optimization: verify the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure, and optimize the model to improve its accuracy and reliability.

[0105] Through the above steps, the present invention carefully selects modeling techniques and tools, effectively imports and integrates pre-processed data, uses advanced tools to build a three-dimensional digital model of the infrastructure, and undergoes a rigorous verification and optimization process to ensure that the model can accurately reflect the actual conditions of the infrastructure, significantly improve the accuracy and reliability of the model, and provide strong digital support for the full life cycle management of the infrastructure.

[0106] Preferably, the digital model building module imports the pre-processed data into the modeling tool and integrates the data to ensure the integrity and consistency of the data, and performs data integration through the following steps:

[0107] S31: Data extraction, selecting and extracting required data from various data sources;

[0108] S32: Data transmission, sending the extracted data subset to the target location;

[0109] S33: Data reorganization: associate the cleaned data according to the new data organization logic to strengthen the internal connection of the data;

[0110] S34: Data publishing: publishing the integrated data to the corresponding database and data warehouse as required for subsequent use.

[0111] Through the above steps, the present invention realizes the effective integration of pre-processed data through the steps of data extraction, transmission, reorganization and publication, ensures the integrity and consistency of the data, enhances the intrinsic connection between the data, and efficiently publishes the integrated data to the designated location, providing a high-quality data foundation for the subsequent construction of digital models, and significantly improving the efficiency and accuracy of model construction.

[0112] Preferably, when the digital model building module associates the cleaned data according to the new data organization logic and strengthens the internal connection of the data, the data fusion method used includes:

[0113] A21: Weighted average method, by assigning different weights to different data sources, and then performing weighted summation to obtain the final fusion result. Its principle formula is:

[0114]

[0115] Among them, is the result after fusion, ω i is the weight of the ith data source, x i is the value of the i-th data source;

[0116] A22: The Bayesian method is based on probability theory and updates the understanding and prediction of data by calculating the posterior probability. Its principle formula is:

[0117]

[0118] Among them, P(A|B) represents the probability of A given B, and P(B|A) represents the probability of B given A. and P(B) represent the prior probabilities of A and B respectively.

[0119] Through the above steps, the present invention uses advanced data fusion technologies such as weighted averaging and Bayesian method to perform in-depth correlation processing on the cleaned data, effectively strengthen the internal connection between the data, improve the comprehensive utilization rate and accuracy of the data, provide more accurate and comprehensive data support for the construction of the digital model, and significantly enhance the reliability and practicability of the model.

[0120] Preferably, the digital model building module uses an optimization algorithm to minimize the loss function when verifying the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure and optimizing the model to improve the accuracy and reliability of the model. The principle formula of the optimization algorithm used is:

[0121]

[0122] Among them, θ j are the parameters of the model, α is the learning rate, J(θ) is the loss function, is the loss function for the parameter θ j The partial derivative of θ j The new value of is assigned to the original θ j .

[0123] Through the above steps, the present invention uses an optimization algorithm, combines the learning rate and the loss function to iteratively update the model parameters, and effectively minimizes the loss function, thereby achieving accurate verification and optimization of the constructed model, significantly improving the accuracy and reliability of the model, and ensuring that the model can be highly consistent with the actual conditions of the infrastructure, providing strong digital support for the full life cycle management of the infrastructure.

[0124] Preferably, the model management and update module includes the following steps when using an efficient database management system to store, manage and update the digital model:

[0125] S41: Model storage. First, select a suitable database system for storage according to the model type, size, complexity and usage requirements, and regularly back up model data to prevent data loss or damage. At the same time, establish a data recovery mechanism so that the model data can be quickly restored when necessary. Finally, control the access to the model data to ensure that only authorized users can access and modify the model data. The selectable database systems include relational databases and non-relational databases.

[0126] S42: Model management, including version control, classification management and tag management. Version control is to record the historical versions of the model, including the modification time, modification content and modification personnel of each version. Classification management is to classify the model according to the model type, purpose and business field factors. Tag management is to add tags to the model for subsequent query and screening.

[0127] S43: Version updates, including partial modifications, reconstruction and regular updates. Regular updates are to determine the frequency and timing of model updates based on infrastructure reconstruction, expansion, maintenance plans and changes in business needs to ensure that the model can reflect changes in actual conditions in a timely manner.

[0128] Through the above steps, the present invention realizes the storage, management and updating of digital models through an efficient database management system. By selecting a suitable database system, regular backup and recovery mechanism, and permission control, the security and accessibility of model data are ensured. At the same time, through version control, classification management and label management, the efficiency and convenience of model management are improved. In addition, according to changes in infrastructure and business needs, the model is updated regularly to ensure the timeliness and accuracy of the model, providing strong support for the full life cycle management of infrastructure.

[0129] Preferably, when the analysis and simulation module uses the digital model to perform various analyses and simulations, the principle steps are as follows:

[0130] S51: Determine the analysis objectives and the types of analysis and simulations that need to be performed based on the characteristics and needs of the infrastructure;

[0131] S52: Model setting and parameter adjustment, setting model parameters in analysis and simulation tools to ensure that the model can accurately reflect the actual situation;

[0132] S53: Run analysis and simulation, use analysis and simulation tools to run the model and perform the required analysis and simulation;

[0133] S54: Result analysis and interpretation: interpret and analyze the analysis and simulation results to extract useful information and conclusions. The analysis of the analysis and simulation results includes data visualization, trend analysis and sensitivity analysis.

[0134] Through the above steps, the present invention realizes comprehensive and accurate analysis and simulation of infrastructure by clarifying the analysis objectives, accurately setting the model parameters, efficiently running the analysis and simulation tools, and deeply analyzing and visualizing the results. This solution not only improves the accuracy and efficiency of the analysis and simulation, but also deeply mines the useful information in the results through data visualization, trend analysis and sensitivity analysis, providing powerful decision-making support for the planning, design, construction and operation and maintenance of infrastructure.

[0135] Preferably, the operation and maintenance management module includes the following steps when performing operation and maintenance management of the infrastructure by real-time monitoring and analyzing the data in the digital model, discovering potential problems of the infrastructure, and performing early warning and maintenance in advance:

[0136] S61: Real-time monitoring, using sensors and IoT technologies to monitor the status and performance of infrastructure in real time;

[0137] S62: Fault warning: Based on real-time monitoring data and analysis results, fault warning is carried out, and when potential problems are found, warning signals are issued in time so that corresponding countermeasures can be taken;

[0138] S63: Maintenance plan formulation: According to the fault warning and actual situation, a maintenance plan is formulated, which includes determining the maintenance time, maintenance content and required resources;

[0139] S64: Maintenance execution and tracking, execute the maintenance plan, and track and record the maintenance process.

[0140] Through the above steps, the present invention monitors the status and performance of the infrastructure in real time, combines data analysis to achieve fault warning, formulates and executes maintenance plans in a timely manner, and tracks and records the maintenance process throughout, thereby effectively improving the efficiency and accuracy of infrastructure operation and maintenance management, ensuring the safe and stable operation of the infrastructure, and reducing the risk and impact of failures.

[0141] See also Figure 2 The present invention provides an embodiment: a method for building and managing a digital model of an infrastructure throughout its life cycle, comprising the following steps:

[0142] S71: Project initiation and requirements analysis, determine project goals, scope and stakeholders, and conduct requirements analysis;

[0143] S72: Conceptual design and preliminary planning: Based on the results of the demand analysis, conduct conceptual design and develop preliminary planning, including schedule, budget and resource allocation;

[0144] S73: Detailed design and modeling, using BIM and other digital tools for detailed design and building three-dimensional models;

[0145] S74: Collaborative design and optimization, through the cloud platform, designers, engineers and construction personnel can collaborate to optimize the design, resolve conflicts and improve the design quality;

[0146] S75: Digital model update and verification: Update the digital model in a timely manner and use simulation and verification tools to verify the updated model to ensure the consistency between the model and the actual situation.

[0147] Through the above steps, the present invention comprehensively improves the digital management level of the entire life cycle of infrastructure through systematic project initiation, demand analysis, conceptual design, detailed design and modeling, collaborative design and optimization, and digital model update and verification. This method not only ensures the accurate realization of project goals, but also significantly improves the design quality and efficiency through multi-party collaborative design and optimization. At the same time, the continuous update and verification of the digital model ensures a high degree of consistency between the model and the actual situation, providing strong support for the planning, design, construction and operation and maintenance of infrastructure.

[0148] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of those skilled in the art without departing from the spirit of the present invention.

Claims

1. A digital model construction and management system for the entire life cycle of infrastructure; characterized by: Included are: The data collection and preprocessing module is used to collect various data of the infrastructure throughout its life cycle and perform preprocessing to ensure the accuracy and consistency of the data. The various data of the infrastructure throughout its life cycle include geometric information, material information, construction information, and operation and maintenance information. A digital model building module, which is used to build a three-dimensional digital model of the infrastructure based on the pre-processed data using advanced modeling techniques and tools, wherein the constructed three-dimensional digital model contains the geometric shape, structural characteristics and material property information of the infrastructure; The model management and update module is used to store, manage and update digital models using an efficient database management system. It also supports model version control and can record historical versions of the model for easy tracking and backtracking. Analysis and simulation module, which is used to perform various analyses and simulations using digital models, including structural analysis, energy consumption analysis and traffic flow simulation; The operation and maintenance management module is used to discover potential problems of infrastructure through real-time monitoring and analysis of data in the digital model, and to carry out early warning and maintenance, thereby managing the operation and maintenance of infrastructure, including daily maintenance, fault warning and maintenance plan formulation; Decision support module, which is used to provide decision support for the planning, design, construction and operation and maintenance of infrastructure throughout its life cycle based on digital models and analysis results; The system integration and interface module is responsible for integrating the above modules, ensuring data exchange and collaborative work between them, and providing interfaces with other systems to achieve data sharing and interaction.

2. According to claim 1, a digital model construction and management system for the entire life cycle of infrastructure, characterized in that: The data collection and preprocessing module collects various types of data throughout the life cycle of the infrastructure and preprocesses it to ensure the accuracy and consistency of the data, including the following steps: S11: Determine the data source. First, you need to identify the source of the required data, which includes sensors, IoT devices, historical documents, and field surveys. S12: Data collection, using appropriate methods and techniques to collect data based on the identified sources; S13: Data preprocessing: According to the type and category of data, select appropriate data preprocessing methods to preprocess the collected data to ensure the quality and availability of the data.

3. According to claim 2, a digital model construction and management system for the entire life cycle of infrastructure, characterized in that: The data collection and preprocessing module selects appropriate data preprocessing methods according to the type and category of data, preprocesses the collected data, and ensures the quality and availability of the data. The data preprocessing methods used include: A11: Data cleaning includes removing duplicate data, processing missing values ​​and correcting erroneous data. Missing data is processed by deletion, filling and interpolation methods. A12: Data format conversion includes data type conversion, data standardization, data normalization and data encoding. The principle formula for data standardization is: z=(x-μ) / σ; Among them, z is the data after standardization, x is the original data, μ is the mean, and σ is the standard deviation; The principle formula for normalizing data is: x' = (x-min) / (max-min); Among them, x' is the data after normalization, x is the original data, min and max are the minimum and maximum values ​​in the data set respectively; A13: Data verification includes data consistency check, logic check and statistical check, which verifies the accuracy and consistency of data.

4. According to claim 3, a digital model construction and management system for the entire life cycle of infrastructure, characterized in that: The digital model building module uses advanced modeling techniques and tools to build a 3D digital model of the infrastructure based on pre-processed data, including the following steps: S21: Select modeling techniques and tools. Select appropriate modeling techniques and tools based on the characteristics and needs of the infrastructure. S22: Data import and integration: import the pre-processed data into the modeling tool and perform data integration to ensure data integrity and consistency; S23: Model construction, using modeling tools to construct a three-dimensional digital model of the infrastructure based on the imported data; S24: Model verification and optimization: verify the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure, and optimize the model to improve its accuracy and reliability.

5. According to claim 4, a digital model construction and management system for the entire life cycle of infrastructure, characterized in that: The digital model building module imports the pre-processed data into the modeling tool and integrates the data to ensure the integrity and consistency of the data. The following steps are performed to integrate the data: S31: Data extraction, selecting and extracting required data from various data sources; S32: Data transmission, sending the extracted data subset to the target location; S33: Data reorganization: associate the cleaned data according to the new data organization logic to strengthen the internal connection of the data; S34: Data publishing: publishing the integrated data to the corresponding database and data warehouse as required for subsequent use.

6. According to claim 5, a digital model construction and management system for the entire life cycle of infrastructure, characterized in that: The digital model building module associates the cleaned data according to the new data organization logic to strengthen the internal connection of the data. The data fusion methods used include: A21: Weighted average method, by assigning different weights to different data sources, and then performing weighted summation to obtain the final fusion result. Its principle formula is: Among them, is the result after fusion, ω i is the weight of the ith data source, x i is the value of the i-th data source; A22: The Bayesian method is based on probability theory and updates the understanding and prediction of data by calculating the posterior probability. Its principle formula is: Among them, P(A|B) represents the probability of A given B, and P(B|A) represents the probability of B given A. and P(B) represent the prior probabilities of A and B respectively.

7. A digital model construction and management system for the entire life cycle of infrastructure according to claim 6, characterized in that: The digital model building module verifies the constructed model to ensure that it can accurately reflect the actual situation of the infrastructure, and optimizes the model to improve the accuracy and reliability of the model. The optimization algorithm is used to minimize the loss function. The principle formula of the optimization algorithm is: Among them, θ j are the parameters of the model, α is the learning rate, J(θ) is the loss function, is the loss function for the parameter θ j The partial derivative of θ j The new value of is assigned to the original θ j .

8. A digital model construction and management system for the entire life cycle of infrastructure according to claim 7, characterized in that: The model management and update module uses an efficient database management system to store, manage and update digital models, including the following steps: S41: Model storage. First, select a suitable database system for storage according to the model type, size, complexity and usage requirements, and regularly back up model data to prevent data loss or damage. At the same time, establish a data recovery mechanism so that the model data can be quickly restored when necessary. Finally, control the access to the model data to ensure that only authorized users can access and modify the model data. The selectable database systems include relational databases and non-relational databases. S42: Model management, including version control, classification management and tag management. Version control is to record the historical versions of the model, including the modification time, modification content and modification personnel of each version. Classification management is to classify the model according to the model type, purpose and business field factors. Tag management is to add tags to the model for subsequent query and screening. S43: Version updates, including partial modifications, reconstruction and regular updates. Regular updates are to determine the frequency and timing of model updates based on infrastructure reconstruction, expansion, maintenance plans and changes in business needs to ensure that the model can reflect changes in actual conditions in a timely manner.

9. A digital model construction and management system for the entire life cycle of infrastructure according to claim 8, characterized in that: When the analysis and simulation module uses digital models to perform various analyses and simulations, the principle steps are as follows: S51: Determine the analysis objectives and the types of analysis and simulations that need to be performed based on the characteristics and needs of the infrastructure; S52: Model setting and parameter adjustment, setting model parameters in analysis and simulation tools to ensure that the model can accurately reflect the actual situation; S53: Run analysis and simulation, use analysis and simulation tools to run the model and perform the required analysis and simulation; S54: Result analysis and interpretation: interpret and analyze the analysis and simulation results to extract useful information and conclusions. The analysis of the analysis and simulation results includes data visualization, trend analysis and sensitivity analysis.

10. A method for building and managing a digital model of the entire life cycle of infrastructure, characterized by: The following steps are included: S71: Project initiation and requirements analysis, determine project goals, scope and stakeholders, and conduct requirements analysis; S72: Conceptual design and preliminary planning: Based on the results of the demand analysis, conduct conceptual design and develop preliminary planning, including schedule, budget and resource allocation; S73: Detailed design and modeling, using BIM and other digital tools for detailed design and building three-dimensional models; S74: Collaborative design and optimization, through the cloud platform to achieve multi-party collaboration among designers, engineers and construction personnel, and to optimize the design, resolve conflicts and improve the design quality; S75: Digital model update and verification: Update the digital model in a timely manner and use simulation and verification tools to verify the updated model to ensure the consistency between the model and the actual situation.

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