Geotechnical engineering three-dimensional intelligent design system and construction method of resource library of geotechnical engineering three-dimensional intelligent design system

Abstract

The invention relates to a geotechnical engineering three-dimensional intelligent design system and a construction method of a resource library of the geotechnical engineering three-dimensional intelligent design system. The method comprises the following steps of: classifying input data according to professional attributes and data types (structured and unstructured) according to requirements of geotechnical engineering three-dimensional design and artificial intelligence AI model training and application on the input data; and constructing relational databases such as a standard library, a rock and soil parameter library, a physical property index library, an industrial profile library, a reinforcing member library, a reinforcing scheme library, a monitoring instrument library and the like for the structured professional data according to professions. The unstructured data is processed in two modes, one mode is classified and managed according to documents, images, two-dimensional diagrams and three-dimensional models, and the other mode is to construct indexes of sections, standard components or parts and the incidence relation between the three-dimensional models and the indexes. The constructed resource library is coded by a computer to form a resource layer in a B / S or C / S architecture software system, structured data is stored and managed by adopting a relational database, and unstructured data is managed by adopting a file database or a file server.

Description

Technical Field

[0001] The present invention relates to the technical field of geotechnical engineering, and in particular to a three-dimensional intelligent design system for geotechnical engineering and a method for constructing a resource library thereof. Background Art

[0002] In recent years, the rapid development of artificial intelligence and digital technologies in various fields has spawned numerous industry hotspots. The integration of DeepSeek language large models into geotechnical engineering and their intelligent application has garnered significant attention. The training and application of all AI models are inseparable from data, the vast majority of which is the result of digital technology applications. Digital technology applications also rely on high-quality input data, some of which is universal and independent of specific projects. In geotechnical engineering, engineering design must adhere to the technical standards of the industry and region to which the specific project belongs. These standards are independent of specific project standards and are universal, forming a crucial component of the geotechnical engineering resource layer. Therefore, the construction of a three-dimensional intelligent design resource library for geotechnical engineering has the important goal of providing high-quality input data for geotechnical digital design and the application of artificial intelligence technologies. One of the key criteria for high quality is compatibility with standards across different industries and regions. CN114564555A discloses a method and system for storing survey data compatible with multi-industry and multi-regional standards. This method aims to address the compatibility issues of cross-industry and cross-regional standards in the application of digital technologies. However, this method is targeted at geological survey professionals and does not involve geotechnical engineering design and artificial intelligence technology applications. CN117171846A discloses a three-dimensional design method and system for roadbed transition sections, which generate a three-dimensional model for slope protection; CN114892688A discloses a three-dimensional design method and system for slope anchor frame beams, which generate a three-dimensional model for anchor layout based on the actual terrain fluctuations of the slope; these methods focus on the digital design process and the application of data, and do not involve basic data, that is, the construction method of the resource layer.

[0003] CN118350110A discloses a generative geotechnical engineering design system and equipment based on artificial intelligence. By introducing artificial intelligence, it solves the unreasonable problems existing in traditional geotechnical engineering design methods. Although this method introduces AI technology, it still focuses on the application of basic data (including resource libraries) and does not involve the construction of resource libraries.

[0004] The approaches described in this section are not necessarily approaches that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any approach described in this section is prior art simply by virtue of its inclusion in this section. Similarly, unless otherwise indicated, the issues raised in this section should not be considered as having been recognized in any prior art. Summary of the Invention

[0005] In response to the technical problems existing in the prior art, the present invention provides a method for constructing a resource library for a three-dimensional intelligent design system for geotechnical engineering, which serves the three-dimensional digitalization and intelligent design of geotechnical engineering by introducing AI technology to construct a resource library.

[0006] The technical solution of the present invention to solve the above technical problems is as follows: In one aspect, the present invention provides a method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system, comprising: Classify the original resource data according to the input data requirements of geotechnical engineering 3D design and artificial intelligence (AI) model training and application, and the original resource data includes structured data and unstructured data; For structured data, a corresponding relational database is constructed according to professional attributes. The relational database includes a standard library, a geotechnical parameter library, a physical property index library, an industrial profile library, a soil and stone material library, a reinforcement library, a reinforcement scheme library, and a monitoring instrument library. For unstructured data, an unstructured relational database is constructed. First, according to the different AI technologies relied on, the unstructured data is classified and managed into four types: documents, images, two-dimensional drawings and three-dimensional models; second, a section and standard parts model library is constructed according to the three-dimensional design requirements, and an index of sections, standard parts or their components is established. A relational database is used to manage the index and construct the relationship between sections and standard parts.

[0007] Furthermore, for structured data, corresponding relational databases are constructed according to professional attributes, including: Determine the terminology for entering the resource library for the structured data based on whether it is applicable to all specific projects; Use the provisions of different technical specifications and standards as term dictionary values; Establish the relationship between different terms in accordance with the rules and requirements that should be followed between terms.

[0008] The values of structured professional data often adhere to standards across different industries and regions, and distinct terms often have clear relationships between them. To this end, we approach professional data construction similarly to a relational database, first determining which terms are included in the resource library based on their applicability to all specific projects. We then incorporate the provisions of different technical standards as terminology dictionary values to meet cross-industry compatibility requirements. We then establish relationships between terms based on the rules and requirements they adhere to, and consider the extensibility and configurability of terminology dictionary values to accommodate changes caused by revisions to technical standards.

[0009] Expandability refers to supporting technical standards of different industries and regions, and configurability means that data can be added during use to adapt to changes in technical specifications and standards after revision. The configuration results can meet the requirements of design work in the early survey and design, construction and operation and maintenance stages of the project.

[0010] Furthermore, the standard library “libraries” the geotechnical design standards of different industries / regions, and uses a relational database to store and manage the terminology dictionary values in the technical standards to describe the corresponding conventions, including: When building a standard library, first determine the terms corresponding to the common data that geotechnical engineering relies on as key fields and indexes, and then convert the values specified by different technical standards into a set of term dictionary values for the corresponding term fields, so that the actual values in actual application change with the implemented technical standards, thereby achieving cross-industry compatibility.

[0011] The term dictionary values in the standard library mainly include the division and name of project stages, requirements for slope and foundation pit design parameters (step height, bridle width, slope ratio), safety factor requirements for slopes of different scales and grades, relevant requirements for cavern layout design (the outline shape of the main powerhouse, main transformer room, and tailwater surge chamber of the underground powerhouse, minimum spacing, minimum turning radius of the tunnel, and slope requirements, etc.), reinforcement design requirements for slopes, foundation pits, and caverns, and foundation treatment requirements for projects of different scales and grades.

[0012] Furthermore, the geotechnical parameter library is used to store and manage geotechnical parameters required for geotechnical engineering mechanics calculations; the method for constructing the geotechnical parameter library includes: Geotechnical parameters are classified according to the two situations of geotechnical engineering objects and the contact surface between geotechnical and structural structures. The geotechnical physical and mechanical parameter indicators and recommended values are determined in accordance with the technical requirements in the specified regulations and specifications. A geotechnical parameter library is constructed to serve the parameter assignment of mechanical calculations in the geotechnical engineering design process.

[0013] Geotechnical engineering objects are divided into slopes, foundation pits, caverns and foundation engineering; the structure in the contact surface between geotechnical and structural can be concrete or metal. The strength indicators of various geotechnical and concrete, geotechnical and metal contact surfaces in the regulations and specifications are recorded in the parameter library for centralized management. Once the geotechnical type and contact surface type are determined, the geotechnical engineering mechanics calculation parameters can be determined.

[0014] In the water conservancy and hydropower industry, the geotechnical parameter library is coordinated with the thematic models in the technical regulations for 3D geological modeling of water conservancy and hydropower projects, connecting geological survey results with calculation input conditions. The geological zoning model corresponds to the material zoning in the mechanical calculation model, and geotechnical physical and mechanical parameter values are managed according to geological zoning classification. Geotechnical physical and mechanical parameter values for slope and foundation pit projects are valued and classified according to rock mass structure or rock soil type; and geotechnical physical and mechanical parameters for foundation and cavern projects are valued and classified according to rock mass quality. The geotechnical parameter library for cavern design supports surrounding rock quality classifications commonly used in other regions and industries, such as RMR, BQ, and Q. Rock mass mechanical parameters include the Hoek-Brown strength parameter.

[0015] Furthermore, the physical property index library contains various methods used in geophysical exploration and detection in the field of geotechnical engineering and the corresponding physical property indexes and dimensions; the physical property index library customizes the entry of multiple geophysical methods and geophysical indexes according to industry specifications and local standards, establishes a standard format for geophysical data entry, and generates geophysical dictionary indexes for various industries.

[0016] The test indicators and input formats of each geophysical method customized in the physical property index library can be dynamically updated, and a unified data interaction standard is formed by using the conventions of the library files. It can customize and expand various geophysical methods and physical property indicators according to different engineering stages and uncertain geological conditions, and solve the problem of data interaction difficulties during cross-disciplinary collaboration in the engineering exploration process, so that specific projects can choose different geophysical and detection methods and naturally realize data interaction.

[0017] The physical property index library customizes the entry of multiple geophysical methods and geophysical indicators according to industry specifications and local standards, and establishes a standard format for geophysical data entry. The standard format for data entry includes the dictionary value, code, geophysical method, dimension, recording method (single point or interval depth), counting method, etc. of the geophysical indicator, and generates geophysical dictionary indexes for various industries. When a specific project references a specified geophysical dictionary value, the physical property index library automatically generates a geophysical data entry table in a standard format.

[0018] Furthermore, the industrial profile library, earth and stone material library, reinforcement parts library, reinforcement scheme library, and model library together constitute a reinforcement design resource library; wherein, The industrial profile library data is derived from industrial materials (rebars, steel strands, steel plates, steel sections, etc.) produced by manufacturers, and records the specifications, material grades, geometric shapes, unit prices, and mechanical properties of each industrial material.

[0019] The industrial profile library and the earth and stone material library together constitute the material library.

[0020] The reinforcement library is used to define the design parameters of reinforcements and record their safety parameters. It serves as the basic data source for reinforcement verification. The reinforcements in the reinforcement library are made of one or more materials and include specific design parameters, thereby playing a specific reinforcement role.

[0021] The reinforcement scheme library is composed of one or more combinations of reinforcements. The reinforcement scheme library is generally classified and managed according to geotechnical engineering types (slope, foundation pit, foundation, cavern). Based on the combination of various reinforcements in the reinforcement library and the recording of the layout design parameters of each reinforcement, a set of layout design schemes for multiple reinforcement combinations is formed to meet the application requirements under different geological conditions, project grades and scales, and site conditions.

[0022] The material library, reinforcement components, and reinforcement schemes follow the hierarchical relationship required by the IFC standard: the reinforcement scheme is composed of reinforcement components combined according to certain design parameters, and the reinforcement components are made by processing and assembling the corresponding materials.

[0023] The material library, reinforcement components, and reinforcement plans support dynamic updates, and design parameters and market unit prices can be adjusted at any time. The resource library can calculate the unit price of each reinforcement component in the design plan and output a total cost list, facilitating dynamic evaluation and optimization of the entire design and construction process of a single project.

[0024] Furthermore, the monitoring instrument resource library includes various instruments commonly used in geotechnical engineering safety monitoring and corresponding parameter indicators; the monitoring instrument resource library is constructed by customizing the input of monitoring instrument names and configuring the parameter indicators, dimensions and data recording methods of the monitoring instruments.

[0025] The monitoring instrument resource library can customize the entry of commonly used monitoring sensors in various industries, define the indicator names and dimensions of monitoring instruments, and provide the counting method required by the industry. When a specified monitoring project selects the monitoring instrument dictionary value configured in the monitoring instrument resource library, the monitoring instrument resource library uniquely determines the monitoring data recording form format of the instrument according to the name and recording value format of each instrument, meeting the requirements of monitoring layout design, recording and displaying monitoring data.

[0026] Furthermore, the documents and images in the unstructured relational database are managed according to the requirements of the referenced language AI model and image recognition AI model respectively; the language AI model automatically generates the text content required for documents and reports by retrieving input data.

[0027] For two-dimensional images and three-dimensional models that lack the ability to be processed by AI technology, they are managed with reference to image data.

[0028] The language AI models include proficient dedicated models or reference general language large models such as DeepSeek, ChatGPT, OpenAI, etc.; the text content in the document is generated by accessing resource libraries and specific engineering project data (field data and three-dimensional digital results data), dedicated language models or general large language models.

[0029] Furthermore, the sections and standard parts in the section and standard parts model library are components used in the design of composite geotechnical engineering objects (tunnels, retaining walls, etc.). A parametric graphic library is constructed for each section and standard part, and an index is established for each graphic therein. The sections or standard parts are indexed using a relational database and assembled into a three-dimensional contour model.

[0030] On the other hand, the present invention also provides a three-dimensional intelligent design system for geotechnical engineering, which adopts a B / S or C / S architecture and consists of a resource layer, a data layer, a logic layer and an application layer; wherein, The resource layer is used to store the resource library constructed by the above-mentioned method for constructing a resource library of the geotechnical engineering three-dimensional intelligent design system, wherein structured data is stored and managed using a relational database, and unstructured databases are managed using a file database or file server; the resource layer data is accessed through an API interface to achieve data access between various layers within the system and between the system and third-party systems; The data layer is used to store and manage all engineering data within the system and realize the interaction between various professional data; The logic layer consists of data processing and presentation technologies including AI models; The application layer is composed of application functions, which are used to read user input data and operation commands, and realize networked applications and services based on various professional data of the data layer.

[0031] The beneficial effects of the present invention are as follows: (1) The present invention provides a sufficient basis for geotechnical engineering three-dimensional design based on knowledge-driven artificial intelligence design by constructing a configurable and expandable geotechnical engineering resource library, and transforms the design schemes and requirements based on industry regulations and specifications, and even professional methods integrated with expert experience, to realize intelligent recommendation of geotechnical three-dimensional design parameters, and utilizes these input parameters to construct the required three-dimensional design model results, naturally improving the standardization and normalization of the design process, and continuously promoting the development and application of geotechnical engineering three-dimensional design technology.

[0032] (2) The geotechnical engineering resource library of the present invention forms a unified data interaction standard, which is the key to integrating multi-disciplinary data and realizing cross-disciplinary data interaction. It is also the foundation of the three-dimensional digital and intelligent design of geotechnical engineering, and plays the dual role of standardizing digital operation processes and realizing cross-disciplinary data interaction. The three-dimensional collaborative design process of geotechnical engineering references the basic data in the resource library, thereby improving the standardization and process level of the design process, thereby improving the ability to ensure work quality and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A technical roadmap for the method and system for constructing a geotechnical engineering resource library provided by an embodiment of the present invention; Figure 2 A schematic diagram of the definition of term values within a geotechnical engineering resource library in a method and system for constructing a geotechnical engineering resource library provided by an embodiment of the present invention; Figure 3 A schematic diagram of slope design parameters built into the standard library of the geotechnical engineering resource library and the system provided in an embodiment of the present invention; Figure 4An example diagram of guiding excavation slope ratio according to slope design parameters in a standard library provided by an embodiment of the present invention; Figure 5 A schematic diagram of a geotechnical parameter library of a method and system for constructing a geotechnical engineering resource library provided by an embodiment of the present invention; Figure 6 A schematic diagram of a physical property index library of a geotechnical engineering resource library construction method and system provided in an embodiment of the present invention; Figure 7 Schematic diagram of the industrial profile library, soil and rock library, reinforcement library, and reinforcement solution library that follow the IFC standard hierarchical relationship provided by an embodiment of the present invention; Figure 8 A schematic diagram of a parametric cross-section graphic library of a method and system for constructing a geotechnical engineering resource library provided by an embodiment of the present invention; Figure 9 A schematic diagram of a monitoring instrument library for a method and system for constructing a geotechnical engineering resource library provided by an embodiment of the present invention; Figure 10 A schematic diagram of the architecture of a method and system for constructing a geotechnical engineering resource library provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0035] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the described features. In the description of this application, "plurality" means two or more, unless otherwise specifically specified.

[0036] In the description of this application, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art will recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0037] Figure 1 A flowchart of a method for constructing a resource library for a three-dimensional intelligent design system for geotechnical engineering is provided in accordance with an embodiment of the present invention. The constructed resource library is computer-coded to form a resource layer within a B / S or C / S architecture software system. Input data is categorized by professional attributes and data types (structured and unstructured) based on the requirements for three-dimensional geotechnical engineering design and artificial intelligence (AI) model training and application. Structured data is stored and managed using a relational database, while unstructured data is managed using a file database or file server. Data access and application are implemented using software engineering techniques. Corresponding relational databases are constructed for structured data by discipline, including a standard library, a geotechnical parameter library, a physical property index library, a library of industrial profiles, a library of soil and rock, a library of reinforcement materials, a library of reinforcement solutions, and a library of monitoring instruments. Unstructured data is processed in two ways: first, data is categorized and managed according to the AI technology used, into four types: documents, images, two-dimensional drawings, and three-dimensional models. Second, unstructured data, such as sections and standard parts, is processed and constructed, and indexes of sections, standard parts, or their components are established. A relational database is used to manage the indexes and establish relationships between sections and standard parts. Based on specific cases, the implementation method of the construction method of the geotechnical engineering 3D intelligent design resource library is as follows: In this embodiment, the structured professional data values often follow different industry and regional standards, and there is a clear relationship between different terms. For professional data, according to the idea of building a relational database, the fields entering the resource library are first determined based on whether they are applicable to all specific projects, and then the provisions of different technical standards are used as field values to meet cross-industry compatibility requirements. Figure 2As shown, using the generic term "control hole ratio" for all specific projects as an example, Geotechnical Engineering extracts the minimum and maximum agreed-upon drill hole ratios for different project levels, phases, and drill hole types according to the "Geotechnical Engineering Investigation Code." This automatically checks the compliance of drill hole ratios during exploration and layout. The resource library also supports the extensibility and configurability of the "control hole ratio" term value to accommodate changes caused by revisions to technical standards.

[0038] In this embodiment, the standard library in the structured data resource library "libraries" the geotechnical design standards of different industries / regions: a relational database is used to store and manage the terminology values in the technical standards to describe the corresponding conventions. When building the standard library, the terms corresponding to the common data relied on by geotechnical engineering design are first determined as key fields and indexes. The values specified in different technical standards are then converted into a set of terminology values for the term, so that the actual values in actual application vary with the implemented technical standards, thereby achieving cross-industry compatibility. Preferably, Figure 3 As shown in the figure, the technical requirements for slope excavation in the Code for Slope Design of Hydropower Projects (NB / T10512-2021) are built into the standard library. Figure 4 Taking the slope profile design shown in the figure as an example, the standard library provides recommended values for the height of artificial excavation steps and the width of the bridle path for rock slopes based on hydropower engineering experience. The height of the artificial rock slope steps is 15-20m, and the bridle path width is not less than 2m. The geological terms of different geological zones in the 3D geological model are used as input conditions to index the design parameters agreed upon in the specifications and standards in the standard library. The standard library intelligently recommends slope ratio parameters for slope excavation in different geological zones: 1:0.5-1:1 for strongly weathered slopes, 1:0.3-1:0.5 for weakly weathered slopes, and 1:0.3-vertical for slightly weathered slopes, and automatically corrects the initial slope profile.

[0039] In this embodiment, the geotechnical parameter library is configured according to the requirements of the engineering geological survey specifications for geotechnical engineering objects (slopes, foundation pits, caverns, and foundation engineering, etc.), and the project type is determined according to the engineering dictionary value in the standard library. Taking into account the variability of the local location of the project (geological division according to the lithology and weathering degree of the stratum), different geological divisions are defined in the standard library through "geological terms", such as Figure 5 As shown in the figure, the geotechnical physical and mechanical parameter values of slope and foundation pit engineering are taken according to the rock structure or rock type, and are associated with the specific term values such as "interlayered, thin layered..." defined in the "rock structure" in the standard library. The rock mechanical parameters agreed in the specifications in the geotechnical parameter library, such as elastic modulus, Poisson's ratio, cohesion, friction angle, etc., are automatically matched.

[0040] In this embodiment, the physical property index library is established as follows: Figure 6As shown in the figure, the physical property index library is configured with geophysical indicators and their entry formats that are suitable for multiple industries according to technical requirements and data recording formats. The standard format of data entry can be freely expanded: dictionary value, code, geophysical method, dimension, and recording method (single point or interval) of geophysical indicators. Taking the dictionary value "longitudinal wave velocity" as an example, when a specific project references this dictionary value for geophysical data entry, the system automatically generates a geophysical data entry table established by the acoustic wave method and seismic wave method, and the data is recorded in the form of "single point" (one depth point corresponds to one geophysical value).

[0041] In this embodiment, the industrial profile library, soil and stone library, reinforcement library and reinforcement scheme library together constitute a reinforcement design resource library that complies with the IFC standard. The hierarchical relationship between the three complies with the requirements of the IFC standard, such as Figure 7 As shown in the figure, the industrial profile library contains industrial materials produced by manufacturers such as steel bars, steel strands, steel plates, and steel sections. The steel bars include steel bars of different models (rebars, round steels, etc.), grades (HPB, HRB, HRBF, etc.) and performance indicators on the market, which can be customized and expanded. The reinforcement library is composed of various industrial materials, such as Figure 7 For example, the "anchor rod" in the reinforcement scheme library is composed of "rebar" and "anchor pad" of specified models in the industrial profile library and "mortar" in the soil and rock library. The material form and mechanical parameters of the reinforcement are comprehensively defined according to industry standards and technical requirements. The reinforcement scheme library automatically recommends a set of layout design schemes with multiple combinations of reinforcements based on the engineering geological conditions, project grade and site conditions of the specified slope range, such as Figure 7 As shown in the slope reinforcement scheme, the combination of reinforcement parts can be readjusted according to the recommended reinforcement scheme to effectively control the construction cost while meeting the safety requirements of the support design.

[0042] In this embodiment, the documents and images in the unstructured data resource library are managed in accordance with the requirements of the reference language AI model and the image recognition AI model, and necessary preprocessing is performed; among them, the language AI model automatically generates the text content required for documents and reports by retrieving input data. For two-dimensional graphics and three-dimensional models that lack available AI technology to process, they are managed in the form of a file server with reference to the image data.

[0043] Preferably, the language AI model includes a skilled dedicated model or references a general language large model such as DeepSeek, ChatGPT, OpenAI, etc.; the text content in the document is generated by accessing resource libraries and specific engineering project data (field data and three-dimensional digital results data), dedicated language models or general large language models.

[0044] In this embodiment, the sections and standard parts in the unstructured data resource library are components used in the design of composite geotechnical engineering objects (tunnels, retaining walls, etc.). Parameterized section graphic libraries are constructed separately and stored in the form of file servers. A relational database is used to manage indexes and build associations between sections and standard parts. Taking the section of a retaining wall as an example, the retaining wall type is indexed as a dictionary value. When the resource library indexes a cantilever retaining wall, the resource library intelligently recommends: Figure 8 The cantilever retaining wall cross-section and design parameters are shown, and custom modifications to the cantilever retaining wall design parameters are allowed. The system updates and displays the three-dimensional contour model of the composite geotechnical engineering object through graphic technology.

[0045] In this embodiment, the monitoring instrument resource library includes various instruments for geotechnical engineering safety monitoring and corresponding parameter indicators, and is scalable, such as Figure 9 As shown, you can customize the entry of commonly used monitoring sensors in various industries, define the indicator names and dimensions of the monitoring instruments, and provide the counting method required by the industry. When the specified monitoring project selects the monitoring instrument dictionary value configured in the monitoring instrument resource library, the resource library uniquely determines the monitoring data record form format of the instrument according to the field name and record value format of each instrument, meeting the requirements of monitoring layout design, recording and displaying monitoring data.

[0046] In this embodiment, the system adopts B / S or C / S architecture, and consists of four layers: resource layer, data layer, logic layer and application layer. Figure 10 As shown. The resource layer refers to the information in various professional systems that is often unrelated to specific engineering projects. That is, it is constructed into various resource libraries through computer coding technology. The resource layer data is accessed through the API interface, realizing data access between various layers within the system and between the system and third-party systems. The data layer stores and manages the data of specific projects during application, which is the data integrated from all professional aspects of the system. The logic layer refers to the data processing technology after the integration of multi-professional data, which is composed of data processing and graphic display technologies including AI models. The application layer is composed of application functions, which are used to read user input data and operation commands, and realize networked applications and services based on various professional data in the data layer, so that users can operate and obtain the required results.

[0047] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0048] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but is only limited by the claims after authorization and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by their equivalents. In addition, the steps may be performed in an order different from that described in this disclosure. Further, the various elements in the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced by equivalent elements that appear after this disclosure.

Claims

1. A method for constructing a resource library for a three-dimensional intelligent design system for geotechnical engineering, characterized in that: include: Classify the original resource data according to the input data requirements of geotechnical engineering 3D design and artificial intelligence (AI) model training and application, and the original resource data includes structured data and unstructured data; For structured data, a corresponding relational database is constructed according to professional attributes. The relational database includes a standard library, a geotechnical parameter library, a physical property index library, an industrial profile library, a soil and stone material library, a reinforcement library, a reinforcement scheme library, and a monitoring instrument library. For unstructured data, an unstructured relational database is constructed. First, according to the different AI technologies relied on, the unstructured data is classified and managed into four types: documents, images, two-dimensional drawings and three-dimensional models; second, a cross-section and standard parts model library is constructed according to the three-dimensional design requirements, and an index of the cross-section, standard parts or the components therein is established. A relational database is used to manage the index and build an association between the index and the three-dimensional model.

2. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 1, characterized in that: For structured data, corresponding relational databases are built according to professional attributes, including: Determine the terminology for entering the resource library for the structured data based on whether it is applicable to all specific projects; Use the provisions of different technical specifications and standards as term dictionary values; Establish the relationship between different terms in accordance with the rules and requirements that should be followed between terms.

3. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 2, characterized in that: The standard library "libraries" the geotechnical design standards of different industries / regions, and uses a relational database to store and manage the terminology dictionary values in the technical standards to describe the corresponding conventions, including: When building a standard library, first determine the terms corresponding to the common data that geotechnical engineering relies on as key fields and indexes, and then convert the values specified by different technical standards into a set of term dictionary values for the corresponding term fields.

4. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 2, characterized in that: The geotechnical parameter library is used to store and manage geotechnical parameters required for geotechnical engineering mechanics calculations; the method for constructing the geotechnical parameter library includes: Classify geotechnical parameters according to the geotechnical engineering objects and the contact surface between geotechnical and structural conditions, determine the geotechnical physical and mechanical parameter indicators and recommended values according to the technical requirements of the specified regulations and specifications, and build a geotechnical parameter library; The geotechnical engineering objects include slopes, foundation pits, caverns and foundation engineering; the structures in the contact surface between the geotechnical and structural elements include concrete or metal. The strength indicators of various types of geotechnical and concrete, and geotechnical and metal contact surfaces in the regulations and specifications are recorded in the parameter library for centralized management. Once the geotechnical type and contact surface type are determined, the geotechnical engineering mechanics calculation parameters can be determined.

5. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 2, characterized in that: The physical property index library contains various methods used in geophysical exploration and detection in the field of geotechnical engineering and the corresponding physical property indexes and dimensions; the physical property index library customizes the entry of multiple geophysical methods and geophysical indexes according to industry specifications and local standards, establishes a standard format for geophysical data entry, and generates geophysical dictionary indexes for various industries.

6. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 2, characterized in that: The industrial profile library, earth and stone material library, reinforcement material library, reinforcement scheme library, and model library together constitute the reinforcement design resource library; wherein: The industrial profile database data is derived from industrial materials produced by manufacturers, and records the specifications, material grades, geometric shapes, unit prices and mechanical properties of each industrial material; The industrial profile library and the earth and stone material library together constitute the material library; The reinforcements in the reinforcement library are made of one or more materials, and the reinforcement solution library is composed of one or more combinations of reinforcements. The material library, reinforcement components, and reinforcement schemes follow the hierarchical relationship required by the IFC standard: the reinforcement scheme is composed of reinforcement components combined according to certain design parameters, and the reinforcement components are made by processing and assembling the corresponding materials.

7. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 2, characterized in that: The monitoring instrument resource library includes various instruments commonly used in geotechnical engineering safety monitoring and corresponding parameter indicators; the monitoring instrument resource library is constructed by customizing the input of monitoring instrument names and configuring the parameter indicators, dimensions and data recording methods of the monitoring instruments.

8. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 1, characterized in that: The documents and images in the unstructured relational database are managed according to the requirements of the referenced language AI model and image recognition AI model respectively; for two-dimensional graphs and three-dimensional models that lack available AI technology for processing, they are managed with reference to image data.

9. The method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to claim 1, characterized in that: The sections and standard parts in the model library are components used in the design of composite geotechnical engineering objects. A parametric graphic library is constructed for the sections and standard parts respectively, and an index is established for each graphic therein. The sections or standard parts are indexed using a relational database and assembled into a three-dimensional contour model.

10. A three-dimensional intelligent design system for geotechnical engineering, characterized in that: The system adopts B / S or C / S architecture and consists of resource layer, data layer, logic layer and application layer; among which: The resource layer is used to store a resource library constructed by the method for constructing a resource library of a geotechnical engineering three-dimensional intelligent design system according to any one of claims 1 to 9, wherein structured data is stored and managed using a relational database, and unstructured databases are managed using a file database or a file server; the resource layer data is accessed through an API interface to achieve data access between layers within the system and between the system and third-party systems; The data layer is used to store and manage all engineering data within the system and realize the interaction between various professional data; The logic layer consists of data processing and presentation technologies including AI models; The application layer is composed of application functions, which are used to read user input data and operation commands, and realize networked applications and services based on various professional data of the data layer.

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