Building engineering information digital management system and method based on data analysis

Abstract

The invention relates to the technical field of digital management, in particular to a building engineering information digital management system and method based on data analysis. The method comprises the following steps: obtaining and preprocessing constructional engineering information to obtain standard constructional engineering information; determining an engineering stage according to the standard constructional engineering information so as to generate constructional engineering stage data; stage nodes of the building engineering stage data are identified, and engineering stage flow information is extracted; and performing building type division on the standard building engineering information according to the engineering stage flow information to generate building engineering type data. Through a data analysis technology, a pattern recognition technology and a deep learning technology, subdivision of constructional engineering types is realized, and corresponding engineering information quality evaluation of subdivided constructional engineering type features is realized, so that constructional engineering information digital management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of digital management, and particularly to a digital management system and method for construction project information based on data analysis. Background Art

[0002] In traditional construction project management, there are often information barriers among different stages such as design, construction, and operation and maintenance, as well as among different departments. Data is difficult to share and circulate, resulting in untimely and inaccurate information transmission, which affects the project progress and quality. Relying on manual information collection, collation, and analysis, the workload is large and prone to errors. It is difficult to quickly and effectively process a large amount of complex data and provide accurate basis for decision-making in a timely manner, making the refinement degree of project management insufficient. With the application of big data analysis technology in the construction project field, higher requirements are put forward for the whole life cycle management from design to operation and maintenance. The digital management system needs to integrate and correlate the information of each stage to achieve the whole process and all-round management of construction projects. However, the existing digital management technology for construction project information fails to be subdivided according to the types of construction projects, and it is difficult to conduct corresponding engineering information quality assessment for the characteristics of subdivided construction project types, resulting in low efficiency of digital management of construction project information. Summary of the Invention

[0003] Based on this, it is necessary to provide a digital management system and method for construction project information based on data analysis to solve at least one of the above technical problems.

[0004] To achieve the above object, a digital management method for construction project information based on data analysis, the method includes the following steps:

[0005] Step S1: Obtain construction project information and perform preprocessing to obtain standard construction project information; determine the project stage according to the standard construction project information, so as to generate construction project stage data;

[0006] Step S2: Identify the stage nodes of the construction project stage data and extract the project stage process information; classify the standard construction project information according to the project stage process information to generate construction project type data;

[0007] Step S3: Determine the engineering quality indicators of the construction project type data, and perform engineering information quality assessment on the standard construction project information based on the engineering quality indicators to obtain an engineering information quality assessment report; perform engineering compliance information heterogeneous integration on the standard construction project information according to the engineering information quality assessment report to obtain engineering heterogeneous integration data;

[0008] Step S4: Count the occurrences of engineering terms in the engineering heterogeneous integrated data, and establish a construction engineering information index based on the occurrences of engineering terms; perform information digital management of the construction engineering information according to the construction engineering information index.

[0009] The present invention obtains construction engineering information and preprocesses it, can standardize the construction engineering information, ensures the consistency and accuracy of the data, and makes the data easier to be recognized and utilized. Determine the engineering stage information of the standard construction engineering information, clarify the key information of the construction project at different stages, facilitate the effective monitoring and management of the project progress, and improve the refinement level of project management. Identify the stage nodes of the construction project stage data and extract the engineering stage process information, which can clearly show each stage of the construction project and their interrelationships. Classify the standard construction engineering information according to the engineering stage process information, so that the information of different types of construction projects can be classified and managed, further improving the pertinence and effectiveness of the construction engineering information management. Determine the engineering quality indicators for the construction project type data, and evaluate the engineering information quality of the standard construction engineering information based on the engineering quality indicators, comprehensively understand the quality status of the construction engineering information, timely discover the problems existing in the information, and provide a reliable basis for subsequent information processing and engineering decision-making; perform engineering compliance information heterogeneous integration on the standard construction engineering information according to the engineering information quality assessment report, realize the effective integration of engineering compliance information from different sources and in different formats, break the information silos, and improve the sharing and availability of data. Count the occurrences of engineering terms in the engineering heterogeneous integrated data, and establish a construction engineering information index based on the occurrences of engineering terms, which is convenient for quickly retrieving and locating construction engineering information, improves the efficiency of information query, and provides convenience for engineering personnel to obtain the required information in the design, construction, operation and maintenance and other links. Perform information digital management of the construction engineering information according to the construction engineering information index to complete the construction engineering information digital management operation, realize the systematic and standardized management of the construction engineering information, improve the efficiency and quality of project management, and promote the digital transformation of the construction engineering industry. Therefore, the present invention realizes the subdivision of the construction project types through data analysis technology, pattern recognition technology and deep learning technology, and realizes the corresponding engineering information quality assessment for the characteristics of the subdivided construction project types, thereby improving the efficiency of the construction engineering information digital management.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: Obtain construction engineering information;

[0012] Step S12: Perform preprocessing operations on the construction project information. The preprocessing operations on the project information include removing the missing values in the project text information and enhancing the contrast of the project image information to obtain the standard construction project information;

[0013] Step S13: Determine the project timestamp for the standard construction project information; divide the project timestamp into time phases to obtain time phase data;

[0014] Step S14: Perform project phase matching on the standard construction project information according to the time phase data to obtain the project matching phase; perform construction project information mapping on the project matching phase to generate construction project phase data.

[0015] The present invention obtains the construction project information, ensuring the integrity of the data. By removing the missing values in the project text information and enhancing the contrast of the project image information, the accuracy and reliability of the data are improved, ensuring the accuracy of subsequent analysis. The preprocessing operations make the construction project information from different sources and formats consistent in quality and format, facilitating subsequent unified processing and analysis. Determining the project timestamp and dividing it into time phases realizes the precise management of the construction project time information. Performing project phase matching on the standard construction project information according to the time phase data ensures the accurate correspondence between the project information and the corresponding time phases. Performing construction project information mapping on the project matching phase realizes the dynamic mapping of the project information in different phases.

[0016] Preferably, step S2 includes the following steps:

[0017] Step S21: Identify project keywords for the construction project phase data, identify the project keywords of start, completion, entry, and acceptance, and record the phase information where the project keywords are located to obtain project keyword phase data;

[0018] Step S22: Sort the project keyword phase data in chronological order to form a phase node sequence; extract phase process information from the construction project phase data according to the phase node sequence to obtain project phase process information;

[0019] Step S23: Extract construction procedures, the required quantity of building materials, and construction building parameters from the project phase process information to obtain the construction project design objectives;

[0020] Step S24: Determine the construction building functions for the construction project design objectives, and based on the construction building functions, classify the standard construction project information by building type to generate construction project type data.

[0021] The present invention identifies engineering keywords for the data in the construction engineering stage, identifies key engineering keywords such as "start", "complete", "enter", and "acceptance", and records the stage information where they are located, which can accurately identify the key nodes of the project and provide clear reference points for subsequent process analysis and management. Sort the engineering keyword stage data in chronological order to form a stage node sequence, so that each stage and key node of the project are clearly presented in chronological order, facilitating project managers to intuitively understand the project progress and process. Extract the stage process information from the construction engineering stage data according to the stage node sequence, which can describe in detail each stage of the project and their interrelationships. Extract the construction processes, the required quantities of building materials, and the construction building parameters from the engineering stage process information, which can clarify the construction requirements and design objectives of the project. Determine the construction building functions for the construction engineering design objectives, which can clarify the usage functions and performance requirements of the project. Classify the standard construction engineering information based on the construction building functions to achieve the classified management of different types of construction projects.

[0022] Preferably, step S24 includes the following steps:

[0023] Step S241: Traverse the text of the construction engineering design objectives, extract the building function keywords for residential, office, and shopping mall, and record the frequency and context description of each building function keyword to obtain the building function content information;

[0024] Step S242: Judge the functional areas of the building function content information. By statistically analyzing the area ratio of the functional areas of the building function information, if the area ratio of the office area exceeds 50%, then determine that the construction building function is an office building;

[0025] Step S243: Respectively perform the functional area judgment described in step S242 on each building function keyword to determine the construction building function type;

[0026] Step S244: Classify the standard construction engineering information according to the construction building function type. If the construction building function is an office building, then classify the construction project as an office building type;

[0027] Step S245: Respectively perform the building type classification described in step S244 on each type of the construction building function type to obtain the construction project type data.

[0028] The text traversal of the architectural engineering design objectives in the present invention can accurately extract architectural function keywords such as residential, office, and shopping mall, record their frequencies and context descriptions, so as to obtain complete architectural function content information, providing an accurate basis for subsequent functional area judgment; based on the architectural function content information, by statistically analyzing the area ratios of each functional area, the functional type of the construction building can be quickly and accurately determined. For example, when the area ratio of the office area exceeds 50%, it can be clearly determined that the functional type of the construction building is an office building, effectively avoiding the ambiguity of functional type judgment; according to the functional type of the construction building, the standard architectural engineering information is classified, and the architectural engineering can be accurately classified into the corresponding architectural type (such as the office building type), and complete architectural engineering type data is formed, providing a clear classification basis for the subsequent management and decision-making of the architectural engineering, and improving the systematicness and accuracy of architectural engineering information management.

[0029] Preferably, step S3 includes the following steps:

[0030] Step S31: Determine the type quality standard for the architectural engineering type data, and set engineering quality indicators for the type quality standard to generate engineering quality indicators;

[0031] Step S32: Compare the standard architectural engineering information with the quality indicators according to the engineering quality indicators to obtain quality indicator comparison data; evaluate the quality status of the engineering information based on the quality indicator comparison data to obtain an engineering information quality evaluation report;

[0032] Step S33: Perform heterogeneous integration of engineering compliance information on the standard architectural engineering information according to the engineering information quality evaluation report to obtain engineering heterogeneous integration data.

[0033] The present invention determines the type quality standard for the architectural engineering type data, ensuring that there is a clear reference basis for the quality standards of different types of architectural engineering. Setting engineering quality indicators based on the type quality standard makes the quality evaluation more scientific and quantitative, facilitating the accurate evaluation of the quality of all aspects of the architectural engineering. Comparing the standard architectural engineering information with the quality indicators according to the engineering quality indicators can accurately identify the differences between the architectural engineering information and the quality standards. Evaluating the quality status of the engineering information based on the quality indicator comparison data can comprehensively evaluate the quality status of the architectural engineering information, timely discover problems in the information, and ensure the accuracy and integrity of the information. Performing heterogeneous integration of engineering compliance information on the standard architectural engineering information according to the engineering information quality evaluation report realizes the effective integration of engineering compliance information from different sources and in different formats, ensuring the integrity and consistency of the engineering information. The generation of engineering heterogeneous integration data breaks the information silos, improves the sharing and availability of data, and provides comprehensive data support for the compliance management of the project.

[0034] Preferably, step S31 includes the following steps:

[0035] Step S311: Perform a building type industry matching on the building engineering type data to obtain building type industry data; obtain the building quality standards for the type industry from the building type industry data to generate type quality standards;

[0036] Step S312: Set the compliance range for the deviation of the indoor net height of the building for the type quality standards, specifically set as not exceeding ±20 mm, to form indoor net height deviation range data;

[0037] Step S313: Set the compliance range for the deviation of the building wall verticality for the type quality standards, specifically set as not exceeding 3 mm, to form wall verticality deviation range data;

[0038] Step S314: Set the compliance range for the deviation of the building floor flatness for the type quality standards, specifically set as not exceeding 5 mm, to form floor flatness deviation range data;

[0039] Step S315: Combine the indoor net height deviation range data, wall verticality deviation range data, and floor flatness deviation range data to obtain engineering quality indicators.

[0040] The present invention performs a building type industry matching on the building engineering type data, ensuring that the quality standards of different types of building projects are consistent with industry norms. Obtaining the building quality standards for the type industry based on the building type industry data ensures the scientificity and authority of the quality standards, providing a reliable basis for subsequent quality assessment. Setting the compliance range for the deviation of the building wall verticality for the type quality standards, specifically set as not exceeding 3 mm, clarifies the allowable deviation range of the wall verticality, providing a specific standard for the measurement and evaluation of the wall verticality, ensuring that the wall verticality meets the building quality requirements. Setting the compliance range for the deviation of the building floor flatness for the type quality standards, specifically set as not exceeding 5 mm, clarifies the allowable deviation range of the floor flatness, providing a specific standard for the measurement and evaluation of the floor flatness, ensuring that the floor flatness meets the building quality requirements. Comprehensive index generation: Combine the indoor net height deviation range data, wall verticality deviation range data, and floor flatness deviation range data to obtain engineering quality indicators. This step integrates multiple key quality indicators into a comprehensive engineering quality indicator system, providing a unified measurement standard for comprehensively evaluating the quality of building projects, ensuring the comprehensiveness and systematicness of quality assessment.

[0041] Preferably, step S32 includes the following steps:

[0042] Step S321: Extract the interior net height of the standard construction project information, record the height difference between the interior net height of the building and the preset interior net height of the building. If the height difference meets the engineering quality index, it is judged that the interior net height is qualified; otherwise, it is judged that the interior net height is unqualified, so as to obtain the comparison data of the interior net height;

[0043] Step S322: Extract the wall verticality of the standard construction project information, record the verticality difference between the wall verticality of the building and the preset wall verticality of the building. If the verticality difference meets the engineering quality index, it is judged that the wall verticality is qualified; otherwise, it is judged that the wall verticality is unqualified, so as to obtain the comparison data of the wall verticality;

[0044] Step S323: Extract the floor flatness of the standard construction project information, record the flatness difference between the floor flatness of the building and the preset floor flatness of the building. If the flatness difference meets the engineering quality index, it is judged that the flatness difference is qualified; otherwise, it is judged that the flatness difference is unqualified, so as to obtain the comparison data of the floor flatness;

[0045] Step S324: Calculate the compliance frequency of the interior net height comparison data, and count the proportion of qualified and unqualified interior net height comparison data to obtain the pass rate of the interior net height;

[0046] Step S325: Identify the distribution of the verticality deviation values of the wall verticality comparison data, detect the discrete distribution characteristics of the deviation values, and obtain the discrete degree of the wall verticality;

[0047] Step S326: Measure the flatness coverage value of the floor flatness comparison data, count the proportion of the total building floor area and the flatness occupied area to obtain the flatness coverage value of the floor;

[0048] Step S327: Assign a weight of 0.3 to the pass rate of the interior net height, assign a weight of 0.4 to the discrete degree of the wall verticality, and assign a weight of 0.3 to the flatness coverage value of the floor to form the engineering quality weight assignment data;

[0049] Step S328: Perform weighted calculation and evaluation according to the engineering quality weight assignment data to obtain the engineering information quality evaluation report.

[0050] The present invention extracts the indoor net height in the standard construction project information, records the height difference with the preset indoor net height, and can accurately measure the actual deviation of the indoor net height. According to whether the height difference conforms to the preset indoor net height deviation range data (not exceeding ±20 mm), it judges whether the indoor net height is qualified and generates the indoor net height comparison data. This step ensures that the measurement result of the indoor net height can directly reflect whether it meets the quality standard. It extracts the verticality of the building wall surface in the standard construction project information and records the verticality difference with the preset verticality of the building wall surface. This step can accurately measure the actual deviation of the wall surface verticality and provide specific data for subsequent qualification judgment. According to whether the verticality difference conforms to the preset wall surface verticality deviation range data (not exceeding 3 mm), it judges whether the wall surface verticality is qualified, ensuring that the measurement result of the wall surface verticality can directly reflect whether it meets the quality standard and improving the accuracy and reliability of quality assessment. It extracts the flatness of the building ground surface in the standard construction project information and records the flatness difference with the preset flatness of the building ground surface. This step can accurately measure the actual deviation of the ground surface flatness and provide specific data for subsequent qualification judgment. According to whether the flatness difference conforms to the preset ground surface flatness deviation range data (not exceeding 5 mm), it judges whether the ground surface flatness is qualified, ensuring that the measurement result of the ground surface flatness can directly reflect whether it meets the quality standard and improving the accuracy and reliability of quality assessment. By comprehensively evaluating the indoor net height comparison data, the wall surface verticality comparison data, and the ground surface flatness comparison data, it can comprehensively evaluate multiple key quality indicators of the construction project, provide a comprehensive quality assessment result, and ensure the comprehensiveness and systematicness of the project information. The project information quality assessment report can detail whether each quality indicator is qualified, provide clear quality feedback to project managers, facilitate the timely discovery and solution of quality problems, and ensure that the overall quality of the project meets the standard requirements. By calculating the compliance frequency of the indoor net height comparison data and statistically analyzing the proportion of qualified and unqualified indoor net height comparison data, it can quantify the qualification situation of the indoor net height, provide specific statistical indicators for quality assessment, and facilitate an intuitive understanding of the overall quality level of the indoor net height. By identifying the distribution of the verticality deviation values in the wall surface verticality comparison data and detecting the discrete distribution characteristics of the deviation values, it can detail the deviation distribution of the wall surface verticality, provide specific distribution characteristics for quality assessment, and facilitate the identification of the stability and consistency of the wall surface verticality. By measuring the flatness coverage value of the ground surface flatness comparison data and statistically analyzing the proportion of the total building area and the flatness occupied area, it can quantify the coverage of the ground surface flatness, provide a specific coverage ratio for quality assessment, and facilitate an intuitive understanding of the overall quality level of the ground surface flatness.The qualification rate of the indoor net height is assigned a weight of 0.3, the degree of dispersion of the wall verticality is assigned a weight of 0.4, and the coverage value of the floor flatness is assigned a weight of 0.3. Through the weight assignment, the importance of different quality indicators in the comprehensive evaluation is reasonably reflected, and the scientificity and rationality of the evaluation results are improved. According to the weighted calculation and evaluation of the engineering quality weight assignment data, an engineering information quality evaluation report is generated. This step comprehensively considers the weights of various quality indicators through weighted calculation, generates a comprehensive and scientific engineering information quality evaluation report, provides detailed quality evaluation results for project managers, facilitates the timely discovery and solution of quality problems, and ensures that the overall quality of the project meets the standard requirements.

[0051] Preferably, step S33 includes the following steps:

[0052] Step S331: Mark the indoor compliant net height information project for the standard construction project information according to the engineering information quality evaluation report, and perform net height label coding to obtain a compliant net height label;

[0053] Step S332: Mark the wall compliant verticality engineering information for the standard construction project information according to the engineering information quality evaluation report, and perform verticality label coding to obtain a compliant verticality label;

[0054] Step S333: Mark the floor compliant flatness engineering information for the standard construction project information according to the engineering information quality evaluation report, and perform flatness label coding to obtain a compliant flatness label;

[0055] Step S334: Map the compliant net height label, compliant verticality label, and compliant flatness label to the standard construction project information for construction project heterogeneous information, and merge the construction project heterogeneous information to obtain engineering heterogeneous integration data.

[0056] According to the engineering information quality assessment report, the standard construction engineering information is marked with indoor compliance net height information engineering and net height label coding is carried out, which can mark and code the qualified information of the indoor net height in the form of labels, facilitating quick identification and retrieval in subsequent data processing and querying, and improving the operability and traceability of the data. According to the engineering information quality assessment report, the standard construction engineering information is marked with ground compliance flatness engineering information and flatness label coding is carried out, which can mark and code the qualified information of the ground flatness in the form of labels. The compliance net height label, compliance verticality label, and compliance flatness label are used to map the heterogeneous construction engineering information of the standard construction engineering information. This step can associate different types of qualified information labels with the standard construction engineering information to ensure the consistency and integrity of the information. The heterogeneous construction engineering information is merged to generate engineering heterogeneous integrated data. This step realizes the integration of different types of construction engineering information, breaks the information silos, improves the sharing and availability of the data, provides unified data support for the overall management and decision-making of the project, and ensures that the overall quality of the project meets the standard requirements.

[0057] Preferably, step S4 includes the following steps:

[0058] Step S41: Obtain the construction engineering terminology thesaurus;

[0059] Step S42: Determine the construction engineering terms for the engineering heterogeneous integrated data based on the construction engineering terminology thesaurus and count the number of occurrences of the construction engineering terms;

[0060] Step S43: Set the construction engineering terms as index keywords and the number of occurrences of the construction engineering terms as index entry values to form a construction engineering information index;

[0061] Step S44: Extract the keywords and their number of occurrences from the construction engineering information index, retrieve the construction engineering documents containing the extracted keywords according to the number of occurrences of the keywords, and sort them according to the keyword occurrence frequency to obtain construction engineering document data;

[0062] Step S45: Classify the construction engineering document data into construction records, quality inspection reports, and rectification progress categories to obtain engineering document category data; assign a unique identification code to each engineering document category data and record the association relationship between the construction engineering documents and the construction projects to obtain engineering association relationship data;

[0063] Step S46: Store the engineering document category data and the engineering association relationship data in a distributed data warehouse, where each engineering document category data is stored in different server nodes;

[0064] Step S47: Perform an indexing operation on the distributed data warehouse for construction project information to obtain an information indexing result; perform a visual display on the information indexing result to obtain an information digital visualization report.

[0065] The present invention obtains a construction project terminology library, which provides basic data for subsequent terminology recognition and statistics, ensures the accuracy and comprehensiveness of terminology recognition, and provides a reliable terminology resource for subsequent data processing and analysis. Determining construction project terms for the heterogeneous integrated data of the project based on the construction project terminology library can accurately identify professional terms in the data and ensure the accuracy and consistency of the terms. Counting the number of occurrences of construction project terms can quantify the usage of the terms, provide specific data support for subsequent index construction, and facilitate quick retrieval and analysis. Setting the construction project terms as index keywords and the number of occurrences of the construction project terms as index entry values to form a construction project information index. This step constructs an efficient index system, facilitating quick retrieval and positioning of construction project information, and improving the efficiency and accuracy of information query. Performing an information indexing operation on the construction project information according to the construction project information index to obtain an information indexing result. This step realizes the quick retrieval and positioning of construction project information, and improves the efficiency and convenience of information management. Performing digital management visualization on the information indexing result to generate an information digital visualization report. This step intuitively displays the distribution and usage of construction project information through visualization means, facilitating project managers to quickly understand and analyze the data, providing a scientific basis for decision-making, and completing the digital management operation of construction project information.

[0066] In this specification, a digital management system for construction project information based on data analysis is provided for implementing the above-mentioned digital management method for construction project information based on data analysis. The digital management system for construction project information based on data analysis includes:

[0067] A construction project information collection module, configured to obtain construction project information and perform preprocessing to obtain standard construction project information; determine the project phase according to the standard construction project information, so as to generate construction project phase data;

[0068] A building type division module, configured to identify the phase nodes of the construction project phase data and extract the engineering phase process information; perform building type division on the standard construction project information according to the engineering phase process information to generate construction project type data;

[0069] An engineering information quality evaluation module, configured to determine the engineering quality indicators of the construction project type data, and perform engineering information quality evaluation on the standard construction project information based on the engineering quality indicators to obtain an engineering information quality evaluation report; perform engineering compliance information heterogeneous integration on the standard construction project information according to the engineering information quality evaluation report to obtain engineering heterogeneous integrated data;

[0070] The engineering information digital management module is used to count the occurrences of engineering terms in the heterogeneous integrated data of the project, and establish a building engineering information index based on the occurrences of engineering terms; perform information digital management of the building engineering information according to the building engineering information index.

[0071] Through the building engineering information acquisition module of the present invention, the building engineering information is obtained and preprocessed, and the building engineering information can be standardized, ensuring the consistency and accuracy of the data, making the data easier to be recognized and utilized. Determine the engineering stage information of the standard building engineering information, clarify the key information of the building project at different stages, facilitate the effective monitoring and management of the project progress, and improve the refinement level of project management. Through the building type classification module, identify the stage nodes of the building engineering stage data and extract the engineering stage process information, which can clearly show each stage of the building project and their mutual relationships. Classify the standard building engineering information according to the engineering stage process information, so that the information of different types of building projects can be classified and managed, further improving the pertinence and effectiveness of building engineering information management. Through the engineering information digital management module, determine the engineering quality indicators for the building engineering type data, and perform engineering information quality assessment on the standard building engineering information based on the engineering quality indicators, comprehensively understand the quality status of the building engineering information, timely discover the problems existing in the information, and provide a reliable basis for subsequent information processing and engineering decision-making; perform engineering compliance information heterogeneous integration on the standard building engineering information according to the engineering information quality assessment report, realizing the effective integration of engineering compliance information from different sources and in different formats, breaking the information silos, and improving the sharing and availability of data. Through the engineering information digital management module, count the occurrences of engineering terms in the engineering heterogeneous integrated data, and establish a building engineering information index based on the occurrences of engineering terms, facilitating the quick retrieval and positioning of building engineering information, improving the efficiency of information query, and providing convenience for project personnel to obtain the required information in the design, construction, operation and maintenance and other links. Perform information digital management of the building engineering information according to the building engineering information index to complete the building engineering information digital management operation, realizing the systematic and standardized management of the building engineering information, improving the efficiency and quality of project management, and promoting the digital transformation of the building engineering industry. Therefore, the present invention realizes the subdivision of the building engineering type through data analysis technology, pattern recognition technology and deep learning technology, and realizes the corresponding engineering information quality assessment for the characteristics of the subdivided building engineering type, thereby improving the efficiency of building engineering information digital management. Brief Description of the Drawings

[0072] Figure 1 It is a schematic diagram of the step flow of a method for digital management of building engineering information based on data analysis;

[0073] Figure 2 is Figure 1 a detailed implementation step flow diagram of step S2 in

[0074] Figure 3 is Figure 2 a detailed implementation step flow diagram of step S24 in

[0075] The realization, functional features and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the drawings. Specific Embodiments

[0076] The technical method of the present invention will be clearly and completely described below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0077] In addition, the drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0078] It should be understood that although the terms "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0079] To achieve the above object, please refer to Figures 1 to 3 , a digital management method for construction project information based on data analysis, the method includes the following steps:

[0080] Step S1: Obtain construction project information and perform preprocessing to obtain standard construction project information; determine the project stage according to the standard construction project information, so as to generate construction project stage data;

[0081] Step S2: Identify the phase nodes of the construction project stage data and extract the engineering phase process information; classify the standard construction project information according to the engineering phase process information to generate construction project type data;

[0082] Step S3: Determine the engineering quality indicators of the construction project type data, and conduct an engineering information quality assessment on the standard construction project information based on the engineering quality indicators to obtain an engineering information quality assessment report; perform heterogeneous integration of engineering compliance information on the standard construction project information according to the engineering information quality assessment report to obtain engineering heterogeneous integration data;

[0083] Step S4: Count the number of occurrences of engineering terms in the engineering heterogeneous integration data, and establish a construction project information index based on the number of occurrences of engineering terms; perform information digital management of the construction project information according to the construction project information index.

[0084] The present invention acquires construction project information and preprocesses it, which can standardize the construction project information, ensuring the consistency and accuracy of the data and making the data easier to be recognized and utilized. Determine the engineering stage information for the standard construction project information, clarify the key information of the construction project at different stages, facilitate the effective monitoring and management of the project progress, and improve the refinement level of project management. Identify the stage nodes of the construction project stage data and extract the engineering stage process information, which can clearly show each stage of the construction project and their mutual relationships. Classify the standard construction project information according to the engineering stage process information, enabling the information of different types of construction projects to be classified and managed, and further enhancing the pertinence and effectiveness of construction project information management. Determine the engineering quality indicators for the construction project type data, and evaluate the engineering information quality of the standard construction project information based on the engineering quality indicators, comprehensively understand the quality status of the construction project information, timely discover the problems existing in the information, and provide a reliable basis for subsequent information processing and engineering decision-making; perform heterogeneous integration of engineering compliance information on the standard construction project information according to the engineering information quality assessment report, realizing the effective integration of engineering compliance information from different sources and in different formats, breaking the information silos, and improving the sharing and availability of data. Count the number of occurrences of engineering terms in the engineering heterogeneous integration data, and establish a construction project information index based on the number of occurrences of engineering terms, facilitating the quick retrieval and positioning of construction project information, improving the efficiency of information query, and providing convenience for project personnel to obtain the required information in the design, construction, operation and maintenance and other links. Perform digital management of the construction project information according to the construction project information index to complete the digital management operation of the construction project information, realizing the systematic and standardized management of the construction project information, improving the efficiency and quality of project management, and promoting the digital transformation of the construction project industry. Therefore, the present invention realizes the subdivision of construction project types through data analysis technology, pattern recognition technology and deep learning technology, and realizes the corresponding engineering information quality assessment for the characteristics of the subdivided construction project types, thereby improving the efficiency of digital management of construction project information.

[0085] In an embodiment of the present invention, with reference to Figure 1 as shown, the digital management method of construction project information based on data analysis includes the following steps:

[0086] Step S1: Acquire construction project information and perform preprocessing to obtain standard construction project information; determine the engineering stage according to the standard construction project information, thereby generating construction project stage data;

[0087] In the embodiments of the present invention, first, construction project information needs to be obtained, which is achieved through various methods. Devices such as total stations, GPS receivers, or laser scanners are used to collect the original data on-site. These devices can provide high-precision and high-stability measurement data. The collected data includes information such as the dimensions, locations, and terrains of buildings. Next, the obtained construction project information is preprocessed to obtain standard construction project information. The preprocessing steps include data cleaning, format conversion, and standardization. Data cleaning refers to removing incorrect and duplicate data records to ensure the accuracy and integrity of the data. Format conversion is to convert data from different sources into a unified format. Standardization is to unify the data according to preset standards. For example, all length units are unified to meters, and area units are unified to square meters, etc., which is completed through professional data processing software. For example, SQL databases are used for data cleaning and format conversion, and Python scripts are used for data standardization processing. After the preprocessing is completed, the engineering phase information of the standard construction project information is determined. This process involves classifying and labeling each stage of the construction project. For example, the construction project is divided into the design stage, construction stage, acceptance stage, etc. This goal can be achieved by using BIM (Building Information Modeling) technology, and corresponding stage identifiers are assigned to each building component or construction task. For example, in the design stage, the components in the BIM model are marked as "design stage", and in the construction stage, the stage identifiers of these components are updated to "construction stage". In addition, GIS (Geographic Information System) technology can be combined to integrate the spatial location information of the construction project with the stage information to generate a more intuitive visual display of the construction project stage data.

[0088] Step S2: Identify the stage nodes of the construction project stage data and extract the engineering stage process information; classify the standard construction project information according to the engineering stage process information to generate construction project type data;

[0089] In the embodiments of the present invention, the stage nodes of the data in the construction engineering stage are identified, and the engineering stage process information is extracted. In specific operations, each stage of the construction project is modeled in detail, including the design stage, the construction stage, the acceptance stage, etc. The nodes of each stage, such as the completion of design, the completion of foundation construction, the topping out of the main structure, etc., are marked and recorded. At the same time, the GIS technology is used to manage the spatial location information of the construction project, and the construction project stage data containing time and space information is generated. The detailed engineering stage process information is extracted, including the start time, end time, duration of each stage, and the logical relationship between them, etc. Next, according to the engineering stage process information, the standard construction project information is classified by building type to generate the construction project type data. The specific operation of building type classification is to divide the construction project into civil construction projects, industrial construction projects, structure projects, and other construction projects. Civil construction projects are further subdivided into residential buildings and public buildings. Among them, residential buildings are further subdivided according to their usage functions and the number of above-ground floors, such as villas, ordinary residences, multi-story and high-rise buildings, etc.; public buildings are divided into various types according to their different service functions, such as administrative offices, cultural and educational research, medical and health care, commercial services, viewing and entertainment, sports buildings, transportation buildings, communication and broadcasting, garden buildings, memorial buildings, etc. Industrial construction projects are classified according to the span and eave height of single-story factories and the area and eave height of multi-story factories. Special buildings such as theaters, stadiums (gymnasiums), libraries, museums, art galleries, exhibition halls, etc., which serve the public, are classified according to Class I, Class II, Class III, and Class IV. Structures are classified according to the height or capacity of chimneys, water towers, silos, storage pools, etc.

[0090] Step S3: Determine the engineering quality indicators of the construction project type data, and based on the engineering quality indicators, conduct an engineering information quality assessment on the standard construction project information to obtain an engineering information quality assessment report; according to the engineering information quality assessment report, conduct an engineering compliance information heterogeneous integration on the standard construction project information to obtain engineering heterogeneous integration data;

[0091] In the embodiments of the present invention, for determining the engineering quality indicators of construction project type data, in specific operations, by collecting the quality inspection data of the construction project at each stage, including material inspection, construction process inspection, completion acceptance inspection and other data, a database is established that includes fields such as construction project type, construction stage, quality inspection items, inspection results, etc. Then, according to the construction project type and construction stage, the corresponding engineering quality indicators are determined, such as qualification rate, functional completeness, performance indicators, safety indicators, reliability indicators, etc. For example, for the main structure stage of civil construction projects, the engineering quality indicators may include the qualification rate of concrete strength, the qualification rate of the thickness of steel bar protection layer, the deviation of structural verticality, etc. Next, based on the engineering quality indicators, the engineering information quality of the standard construction project information is evaluated to obtain an engineering information quality evaluation report. In specific operations, the collected construction project quality inspection data is compared and analyzed with the determined engineering quality indicators, the scores or qualification rates of each indicator are calculated, and according to the preset evaluation criteria, the quality of the construction project information is comprehensively evaluated. The evaluation result obtains an engineering information quality evaluation report, and the report content includes the basic information of the construction project, the quality inspection data of each stage, the evaluation results of the engineering quality indicators, existing quality problems and proposed rectification measures, etc. Finally, according to the engineering information quality evaluation report, the engineering compliance information heterogeneous integration of the standard construction project information is carried out to obtain engineering heterogeneous integration data. This process can be realized by using data integration technology and a distributed data circulation platform. In specific operations, the data in the engineering information quality evaluation report is integrated with other relevant information of the construction project, such as design documents, construction contracts, supervision reports, etc., to construct a heterogeneous database containing the whole life cycle information of the construction project.

[0092] Step S4: Count the number of occurrences of engineering terms in the engineering heterogeneous integration data, and establish a construction project information index according to the number of occurrences of engineering terms; perform information digital management of the construction project information according to the construction project information index.

[0093] In the embodiments of the present invention, the occurrence times of engineering terms in engineering heterogeneous integrated data are counted by using text analysis software. In specific operations, the text information in the engineering heterogeneous integrated data is imported into the text analysis software, and this text information includes descriptive content in documents such as design documents, construction contracts, and supervision reports. The word segmentation function of the software is used to perform word segmentation on this text, decomposing the text into individual words. Then, through the statistical function of the software, the occurrence times of each engineering term in all texts are counted. For example, Excel software can be used to assist in the statistics. The list of words after word segmentation is copied into an Excel table, and the "count" function of Excel is used to count the occurrence times of each engineering term, obtaining a list containing engineering terms and their occurrence times. Next, an index of construction engineering information is established based on the occurrence times of engineering terms, which is achieved by using a database management system. In specific operations, the statistically obtained engineering terms and their occurrence times are imported into the database management system, and a new database table named "Construction Engineering Information Index" is created. This table contains two fields: "Engineering Term" and "Occurrence Times", and the field types are text and integer respectively. Through the import function of the database management system, the data of engineering terms and their occurrence times are imported into this table to complete the establishment of the construction engineering information index. Finally, the construction engineering information is digitally managed according to the construction engineering information index.

[0094] Preferably, step S1 includes the following steps:

[0095] Step S11: Obtain construction engineering information;

[0096] Step S12: Perform preprocessing operations on the construction engineering information. The preprocessing operations on the engineering information include eliminating missing values in the engineering text information and enhancing the contrast of the engineering image information to obtain standard construction engineering information;

[0097] Step S13: Determine the engineering timestamp for the standard construction engineering information; perform time stage division on the engineering timestamp to obtain time stage data;

[0098] Step S14: Perform engineering stage matching on the standard construction engineering information according to the time stage data to obtain an engineering matching stage; perform mapping of the construction engineering information on the engineering matching stage to generate construction engineering stage data.

[0099] In the embodiments of the present invention, various types of information of construction projects are collected by using data acquisition devices and software systems. These information cover design documents, construction drawings, construction logs, quality inspection reports, material lists, etc. Design documents and construction drawings can be exported in DWG or PDF format through CAD software; construction logs and quality inspection reports are usually recorded in Word documents or Excel spreadsheets; material lists can be exported from project management software. All these information are uniformly stored in an enterprise-level document management system or cloud storage service. With the help of data cleaning software, the text data is preprocessed, and the rows or columns where missing values are located are automatically identified and marked. For the marked missing values, the entire rows containing the missing values are deleted and filled, so as to obtain complete text information without missing items. An image processing device is used to perform contrast enhancement processing on engineering images. The engineering image files stored in the image database are imported into the image processing device, and the built-in contrast enhancement function of the device analyzes and adjusts the histogram of the image, making the dark parts of the image darker and the bright parts brighter, thereby improving the overall contrast of the image and making the image details clearer. A timestamp generation tool is used to add accurate time stamps to each event or record in the construction project. According to the system clock or Network Time Protocol (NTP) server, the current accurate time is obtained and converted into a unified time format, such as the ISO8601 format (YYYY-MM-DDTHH:MM:SSZ), and then this timestamp is appended to the corresponding construction project information record. Referring to the progress schedule of the construction project, the entire project cycle is divided into several time phases, such as the design phase, construction preparation phase, main construction phase, decoration phase, acceptance phase, etc. Each phase has a clear start time and end time, and these time points are also recorded in the ISO 8601 format. By comparing the timestamp of each record with the time range of each phase, the records are classified into the corresponding project phases to form time phase data. A database query tool is used to match the standard construction project information with the time phase data. In the database, the construction project information table and the time phase data table store detailed construction project records and the time ranges of each phase respectively. By writing SQL query statements, the records in the construction project information table are associated and queried with the time ranges in the time phase data table, the project phase to which each record belongs is filtered out, and the matching results are updated to the construction project information table, adding a new field of "project phase" to each record, and the field value is the corresponding phase name. The data in the information table is sorted and organized according to the project phases, and a new construction project phase data table is generated. The new table contains detailed information of each phase, such as phase name, start and end times, construction project records within this phase, etc., and finally complete construction project phase data is formed.

[0100] As an example of the present invention, refer to Figure 2As shown, in this example, step S2 includes:

[0101] Step S21: Identify engineering keyword for the construction project stage data, identify the start, completion, entry, and acceptance engineering keywords, and record the stage information where the engineering keywords are located to obtain the engineering keyword stage data;

[0102] Step S22: Sort the engineering keyword stage data in chronological order to form a stage node sequence; extract the stage process information from the construction project stage data according to the stage node sequence to obtain the engineering stage process information;

[0103] Step S23: Extract the construction processes, the required amount of building materials, and the construction building parameters from the engineering stage process information to obtain the construction project design objectives;

[0104] Step S24: Determine the construction building functions for the construction project design objectives, and classify the standard construction project information based on the construction building functions to generate the construction project type data.

[0105] In the embodiments of the present invention, a text analysis software is used to identify keywords in the text content of the construction project stage data. During operation, the construction project stage data is imported into the text analysis software, the keyword identification function of the software is set, and the keywords to be identified are specified as "start", "complete", "enter", and "acceptance". The software will automatically scan the text, identify these keywords, and record the specific positions where each keyword appears, that is, the information of the corresponding stage, so as to obtain the engineering keyword stage data including the keywords and their corresponding stage information. The obtained engineering keyword stage data is imported into the database management system. In the database management system, the corresponding data table is selected, and its sorting function is used to sort the data according to the time field in the stage data in chronological order. After the sorting is completed, a stage node sequence arranged in chronological order is obtained. Then, based on this stage node sequence, the construction project stage data is analyzed, and the start node and end node of each stage, as well as the stage process information such as the time interval between the nodes, are extracted to form the complete engineering stage process information data. For the extraction of construction procedures, the construction log and construction drawings are consulted, and the construction procedures included in each stage are listed in the order of construction, such as foundation construction, main structure construction, decoration construction, etc. For the extraction of the required amount of building materials, referring to the material list and material markings in the construction drawings, the names, specifications, and quantities of various building materials required for each stage are counted. For the extraction of construction building parameters, BIM software is used to extract parameter information such as the size, structural type, and material properties of the building. The extracted construction procedures, required amount of building materials, and construction building parameters are integrated together to form the construction project design target data. According to the construction building parameters and required amount of building materials and other information in the construction project design target, the function of the construction building is determined. For example, if the building parameters show that the building has more living spaces and living supporting facilities, its function is determined as a residential building; if the building is mainly used for commercial activities, its function is determined as a commercial building. After determining the function of the construction building, the database management system is used again to match the standard construction project information with the function of the construction building. In the database, the standard construction project information table is selected, a new field "building type" is added, and then according to the function of the construction building, the construction project information is classified into the corresponding building types, such as residential buildings, public buildings, industrial buildings, etc., and finally the construction project type data including the building type information is generated.

[0106] As an example of the present invention, refer to Figure 3 As shown, in this example, step S24 includes:

[0107] Step S241: Traverse the text of the construction project design target, extract the residential, office, and shopping mall building function keywords, and record the frequency and context description of each building function keyword to obtain the building function content information;

[0108] Step S242: Determine the functional area of the building function content information. By counting the area ratio of the functional areas of the building function information, if the area ratio of the office area exceeds 50%, it is determined that the construction building function is an office building;

[0109] Step S243: Perform the functional area judgment described in Step S242 on each building function keyword respectively to determine the construction building function type;

[0110] Step S244: Classify the standard building project information according to the construction building function type. If the construction building function is an office building, the building project is classified as an office building type;

[0111] Step S245: Perform the building type classification described in Step S244 on each type of the construction building function type respectively to obtain the building project type data.

[0112] In the embodiments of the present invention, the text of the architectural engineering design objective is traversed to extract the keyword of the building functions of residence, office, and shopping mall, and the frequency of occurrence and the context description of each building function keyword are recorded to obtain the building function content information. The text of the architectural engineering design objective document is traversed using natural language processing tools. During the operation, the design objective document is imported into the text analysis software, the keyword extraction function is set, and the keywords to be recognized are specified as "residence", "office", and "shopping mall". The software will automatically scan the text, recognize these keywords, and record the frequency of occurrence of each keyword and its context description to form the building function content information. For example, if the document appears "This building contains multiple office areas, and each area is equipped with an independent meeting room and rest area", the frequency of the keyword "office" increases, and its context description is recorded as "contains multiple office areas, and each area is equipped with an independent meeting room and rest area". The function area of the building function content information is judged. By counting the area ratio of the function area of the building function information, if the area ratio of the office area exceeds 50%, the construction building function is determined to be an office building. The context description in the building function content information is compared and analyzed with the building drawings and area data. Referring to the area of each function area marked in the building drawings, the total area of the office area is counted, and its proportion in the total building area is calculated. If the calculation result shows that the area ratio of the office area exceeds 50%, the function of the construction building is determined to be an office building. The function area judgment described in step S242 is performed on each building function keyword respectively to determine the construction building function type. For each building function keyword extracted in step S241, the operation of step S242 is repeated to perform the function area judgment respectively. For example, for the keyword "residence", the area ratio of the residence area is counted; for the keyword "shopping mall", the area ratio of the shopping mall area is counted. According to the area ratio of each function area, the specific function type of the construction building is determined, such as a residential building, an office building, or a shopping mall building. The standard architectural engineering information is classified according to the construction building function type. If the construction building function is an office building, the architectural engineering is classified as an office building type. According to the construction building function type determined in step S243, the standard architectural engineering information is classified. In the specific operation, the architectural engineering information is stored in the database management system, and according to the construction building function type, the architectural engineering information is classified into the corresponding building type. For example, if the function type of a certain architectural engineering is determined to be an office building, the type field of the architectural engineering in the database is updated to "office building type". The building type classification described in step S244 is performed on each construction building function type respectively to obtain the architectural engineering type data. The operation of step S244 is repeated for all construction building function types to perform the building type classification. Finally, the classified architectural engineering information is summarized to form the complete architectural engineering type data.

[0113] Preferably, step S3 includes the following steps:

[0114] Step S31: Determine the type quality standard for the construction project type data, and set the engineering quality indicators for the type quality standard to generate engineering quality indicators;

[0115] Step S32: Compare the quality indicators of the standard construction project information according to the engineering quality indicators to obtain quality indicator comparison data; evaluate the quality status of the engineering information for the quality indicator comparison data to obtain an engineering information quality evaluation report;

[0116] Step S33: Perform heterogeneous integration of engineering compliance information on the standard construction project information according to the engineering information quality evaluation report to obtain engineering heterogeneous integration data.

[0117] In the embodiment of the present invention, the type quality standard for the construction project type data is determined, and the engineering quality indicators are set for the type quality standard. Use construction project management software to determine the type quality standard for the construction project type data. In specific operations, import the construction project type data into the management software, and the software automatically matches the corresponding quality standards according to the type of construction project (such as civil construction projects, industrial construction projects, etc.). Then, based on these quality standards, set specific engineering quality indicators, such as concrete strength, steel bar protection layer thickness, structural verticality, etc. These indicators will be stored in the database to form an engineering quality indicator data table, which contains fields such as indicator name, indicator standard value, applicable stage, etc. Compare the quality indicators of the standard construction project information according to the engineering quality indicators, and evaluate the quality status of the engineering information for the quality indicator comparison data; compare the actual detection data in the standard construction project information with the engineering quality indicators generated in step S31. In specific operations, import the actual detection data into the quality detection software, and the software will automatically read the engineering quality indicators in the database and perform item-by-item comparison to generate quality indicator comparison data. The comparison data includes information such as actual value, standard value, deviation value, etc. Then, according to the preset evaluation rules, evaluate the quality status of the engineering information for the quality indicator comparison data. The evaluation result will generate a detailed engineering information quality evaluation report, and the report content includes the basic information of the construction project, the quality detection data of each stage, the evaluation result of the quality indicators, existing quality problems, and proposed rectification measures, etc. According to the engineering information quality evaluation report, use data integration tools to perform heterogeneous integration of engineering compliance information on the standard construction project information. In specific operations, integrate the data in the engineering information quality evaluation report with other relevant information of the construction project (such as design documents, construction contracts, supervision reports, etc.). Through the standardization of data identification, data encapsulation organization, and data semantics, ensure that data from different sources can be efficiently interconnected and interoperable. Finally, construct a heterogeneous database containing the whole life cycle information of the construction project to form engineering heterogeneous integration data.

[0118] Preferably, step S31 includes the following steps:

[0119] Step S311: Match the building project type data with the building type industry to obtain the building type industry data; obtain the building quality standards for the building type industry data to generate the type quality standards;

[0120] Step S312: Set the compliance range of the indoor net height deviation of the building for the type quality standards, specifically set to not exceed ±20 mm, to form the indoor net height deviation range data;

[0121] Step S313: Set the compliance range of the wall verticality deviation of the building for the type quality standards, specifically set to not exceed 3 mm, to form the wall verticality deviation range data;

[0122] Step S314: Set the compliance range of the floor flatness deviation of the building for the type quality standards, specifically set to not exceed 5 mm, to form the floor flatness deviation range data;

[0123] Step S315: Combine the indoor net height deviation range data, the wall verticality deviation range data, and the floor flatness deviation range data to obtain the engineering quality indicators.

[0124] In the embodiments of the present invention, a construction project management software is used to match the construction project type data with the construction type industry. In specific operations, the construction project type data is imported into the management software, and the software automatically matches the corresponding industry classification according to the type of the construction project (such as civil construction projects, industrial construction projects, etc.). Then, according to the industry classification, the building quality standards within the industry are obtained. For example, for civil construction projects, the quality standards for residential buildings and public buildings are obtained; for industrial construction projects, the quality standards for single-story factories and multi-story factories are obtained. These quality standards will be stored in the database to form a type quality standard data table, which contains fields such as index name, index standard value, applicable stage, etc. According to the type quality standards, the compliance range of the indoor net height deviation of the building is set. In specific operations, the compliance range of the indoor net height deviation of the building is set to not exceed ±20 mm. This set value will be recorded in the type quality standard data table in the database to form indoor net height deviation range data. For example, in the database, a field "indoor net height deviation range" is created and its value is set to "±20 mm". According to the type quality standards, the compliance range of the wall verticality deviation of the building is set. In specific operations, the compliance range of the wall verticality deviation of the building is set to not exceed 3 mm. This set value will also be recorded in the type quality standard data table in the database to form wall verticality deviation range data. For example, in the database, a field "wall verticality deviation range" is created and its value is set to "3 mm". According to the type quality standards, the compliance range of the floor flatness deviation of the building is set. In specific operations, the compliance range of the floor flatness deviation of the building is set to not exceed 5 mm. This set value will be recorded in the type quality standard data table in the database to form floor flatness deviation range data. For example, in the database, a field "floor flatness deviation range" is created and its value is set to "5 mm". The indoor net height deviation range data, wall verticality deviation range data, and floor flatness deviation range data generated in steps S312 to S314 are merged. In specific operations, a database management tool is used to merge these three data fields into a data table to form a complete engineering quality index data table. This data table will contain all key engineering quality indicators and their compliance ranges, providing data support for subsequent quality assessment and management. For example, a data table named "engineering quality indicators" is created, which contains fields such as "index name" and "compliance range", and the above three indicators and their compliance ranges are respectively recorded in this table.

[0125] Preferably, step S32 includes the following steps:

[0126] Step S321: Extract the interior net height of the standard construction project information, record the height difference between the interior net height of the building and the preset interior net height of the building. If the height difference meets the engineering quality index, it is judged that the interior net height is qualified; otherwise, it is judged that the interior net height is unqualified, so as to obtain the comparison data of the interior net height;

[0127] Step S322: Extract the verticality of the building wall of the standard construction project information, record the verticality difference between the verticality of the building wall and the preset verticality of the building wall. If the verticality difference meets the engineering quality index, it is judged that the wall verticality is qualified; otherwise, it is judged that the wall verticality is unqualified, so as to obtain the comparison data of the wall verticality;

[0128] Step S323: Extract the flatness of the building floor of the standard construction project information, record the flatness difference between the flatness of the building floor and the preset flatness of the building floor. If the flatness difference meets the engineering quality index, it is judged that the flatness difference is qualified; otherwise, it is judged that the flatness difference is unqualified, so as to obtain the comparison data of the floor flatness;

[0129] Step S324: Calculate the compliance frequency of the interior net height comparison data, and count the proportion of the qualified and unqualified interior net height comparison data to obtain the qualification rate of the interior net height;

[0130] Step S325: Identify the distribution of the verticality deviation values of the wall verticality comparison data, detect the discrete distribution characteristics of the deviation values, and obtain the discrete degree of the wall verticality;

[0131] Step S326: Measure the flatness coverage value of the floor flatness comparison data, count the proportion of the total building floor area and the flatness occupied area to obtain the flatness coverage value of the floor;

[0132] Step S327: Assign a weight of 0.3 to the qualification rate of the interior net height, assign a weight of 0.4 to the discrete degree of the wall verticality, and assign a weight of 0.3 to the flatness coverage value of the floor to form the engineering quality weight assignment data;

[0133] Step S328: Perform weighted calculation and evaluation according to the engineering quality weight assignment data to obtain the engineering information quality evaluation report.

[0134] In an embodiment of the present invention, a construction project management software is used to extract the indoor net height data in the standard construction project information. In specific operations, the construction project information is imported into the management software, and the software will automatically read the measured indoor net height values of each room. Then, these measured values are compared with the preset standard (design value) of the indoor net height of the building, and the height difference is recorded. The negative deviation of the indoor net height should not be greater than 20 mm, and the range difference should not exceed 20 mm. If the height difference is within the allowable range, it is determined that the indoor net height is qualified; if it exceeds the range, it is determined that the indoor net height is unqualified, and finally the indoor net height comparison data is formed. Using construction project quality inspection tools, the building wall verticality data in the standard construction project information is extracted. In specific operations, high-precision measuring tools such as a laser plummet are used to measure the verticality of the wall. During the measurement, the vertical distances of the wall are measured from the ground to the top, and the measurement values at each position are recorded. These measured values are compared with the preset standard of the building wall verticality (for example, the allowable deviation of the verticality of a common gypsum wall is 3 mm), and the verticality difference is recorded. If the verticality difference is within the allowable range, it is determined that the wall verticality is qualified; if it exceeds the range, it is determined that the wall verticality is unqualified, and finally the wall verticality comparison data is formed. Using construction project quality inspection tools, the building floor flatness data in the standard construction project information is extracted. In specific operations, a 2m straightedge and a wedge-shaped feeler gauge are used to measure the flatness of the floor. During the measurement, the straightedge is placed diagonally at a 45° angle at the upper left and lower right corners of the floor for measurement, and the straightedge is placed parallel in the middle area of the floor for measurement, a total of three straightedges; an additional straightedge is added in the middle area of the floor of a larger room, a total of four straightedges. These measured values are compared with the preset standard of the building floor flatness (for example, the allowable deviation of the flatness of a common plastered floor is 4 mm), and the flatness difference is recorded. If the flatness difference is within the allowable range, it is determined that the flatness difference is qualified; if it exceeds the range, it is determined that the flatness difference is unqualified, and finally the floor flatness comparison data is formed. The indoor net height comparison data, wall verticality comparison data, and floor flatness comparison data generated in steps S321 to S323 are summarized. Using a database management tool, such as SQL Studio, these data are stored in the database and comprehensively analyzed. In specific operations, an SQL query statement is written to count the qualification rates of each index and generate a detailed engineering information quality assessment report. The report content includes the basic information of the construction project, the comparison results of the measured values and standard values of each index, the qualification rate statistics, existing quality problems, and recommended rectification measures. Finally, through a data visualization tool, such as Tableau, the assessment report is presented in the form of charts and text, providing intuitive data support for the quality management of the construction project. By using data analysis software, such as Excel or the Pandas library of Python, the indoor net height comparison data is processed.In specific operations, import the indoor net height comparison data into the software and count the number of qualified and unqualified indoor net height comparison data. For example, in Excel, the COUNTIF function can be used to count the number of qualified (height difference within the allowable range) and unqualified (height difference exceeding the allowable range) data. Then, calculate the proportion of the number of qualified data to the total number of data to obtain the indoor net height qualification rate. Suppose the total number of data is 1000, and the number of qualified data is 950, then the indoor net height qualification rate is 95%. Use statistical analysis tools such as the R language or the NumPy library of Python to analyze the wall verticality comparison data. In specific operations, import the wall verticality comparison data into the tool and calculate the verticality deviation value of each data point. Then, use a histogram or box plot to identify the discrete distribution characteristics of the deviation values. For example, in Python, the Matplotlib library can be used to draw a histogram, and by observing the shape and distribution of the histogram, determine the degree of dispersion of the deviation values. If the histogram shows that the deviation values are concentrated in a relatively small range, the degree of dispersion is low; if the distribution is wide, the degree of dispersion is high. Use Geographic Information System (GIS) software or professional measurement tools to process the ground flatness comparison data. In specific operations, import the ground flatness comparison data into the GIS software and count the total building ground area and the flatness occupied area. For example, through the area calculation function of the GIS software, the total building ground area and the ground area meeting the flatness requirements can be calculated respectively. Then, calculate the proportion of the flatness occupied area to the total building ground area to obtain the ground flatness coverage value. Suppose the total building ground area is 1000 square meters and the flatness occupied area is 900 square meters, then the ground flatness coverage value is 90%. In the data analysis software, assign weights to the obtained indoor net height qualification rate, wall verticality dispersion degree, and ground flatness coverage value respectively. In specific operations, multiply the indoor net height qualification rate by the weight of 0.3, the wall verticality dispersion degree by the weight of 0.4, and the ground flatness coverage value by the weight of 0.3. For example, in Excel, the formula =A1×0.3 can be used to calculate the weighted value of the indoor net height qualification rate, where the value of the indoor net height qualification rate is contained in cell A1. Store these weighted values in a new data table to form the engineering quality weight assignment data. Use the data analysis software to perform a weighted calculation and evaluation on the engineering quality weight assignment data. In specific operations, sum up the obtained weighted values to get the final engineering information quality evaluation score. For example, in Excel, the SUM function can be used to calculate the sum of the weighted values. Then, according to the preset evaluation criteria, interpret the evaluation score and generate an engineering information quality evaluation report. The report content includes the basic information of the construction project, the evaluation results of each index, existing quality problems, and recommended rectification measures.

[0135] Preferably, step S33 includes the following steps:

[0136] Step S331: Perform threshold screening on the qualified rate data of the indoor net height in the engineering information quality assessment report. Set the qualified rate threshold at 80%, screen out the construction project information with a qualified rate lower than the threshold, mark it as a net height attention project, and obtain the net height compliance attention data.

[0137] Step S332: Divide the interval of the wall verticality dispersion degree data. Divide the dispersion degree into three intervals: low, medium, and high, corresponding to the ranges where the dispersion degree is less than 1 mm, 1 mm to 3 mm, and greater than 3 mm respectively. Count the number of construction project information in each interval to obtain the wall verticality dispersion interval distribution data.

[0138] Step S333: Determine whether the ground flatness coverage value meets the standard. Set the standard coverage value at 90%, judge whether the ground flatness coverage value reaches or exceeds the standard value, mark the construction project information that does not meet the standard as a flatness rectification pending project, and obtain the ground flatness compliance determination data.

[0139] Step S334: Correlate and merge the net height compliance attention data, the wall verticality dispersion interval distribution data, and the ground flatness compliance determination data, and construct an engineering compliance information heterogeneous data framework to obtain a preliminary engineering heterogeneous integration data framework.

[0140] Step S335: Fill and refine the preliminary engineering heterogeneous integration data framework to obtain the engineering heterogeneous integration data.

[0141] In the embodiments of the present invention, a data analysis tool, such as the Pandas library of Excel or Python, is used to process the indoor net height qualification rate data in the engineering information quality assessment report. In specific operations, the indoor net height qualification rate data in the assessment report is imported into the tool, and the qualification rate threshold is set at 80%. By writing query statements or using filtering functions, the construction project information with a qualification rate lower than the threshold is screened out and marked as "net height attention project" to obtain the net height compliance attention data. For example, in Excel, the FILTER function can be used to screen data. A statistical analysis tool, such as the NumPy library of R language or Python, is used to analyze the data on the discrete degree of wall verticality. In specific operations, the data on the discrete degree of wall verticality is imported into the tool, and the discrete degree is divided into three intervals: low, medium, and high, corresponding to the ranges where the discrete degree is less than 1 mm, 1 mm to 3 mm, and greater than 3 mm respectively. By writing conditional statements or using piecewise functions, the number of construction project information in each interval is counted to obtain the data on the discrete interval distribution of wall verticality. A data analysis tool is used to process the data on the ground flatness coverage value. In specific operations, the data on the ground flatness coverage value is imported into the tool, and the qualified coverage value is set at 90%. By writing query statements or using filtering functions, it is judged whether the ground flatness coverage value reaches or exceeds the qualified value, and the construction project information that does not meet the standard is marked as "flatness to be rectified project" to obtain the data on the ground flatness compliance determination. A data integration tool, such as an ETL tool, is used to perform joint merging of the net height compliance attention data, the data on the discrete interval distribution of wall verticality, and the data on the ground flatness compliance determination generated in steps S331 to S333. In specific operations, these data are imported into the ETL tool, and by defining data mapping and conversion rules, the relevant information in different data sets is integrated to construct a heterogeneous data framework for engineering compliance information, obtaining a preliminary heterogeneous integrated data framework for engineering. A data filling tool is used to fill and refine the preliminary heterogeneous integrated data framework for engineering. In specific operations, the preliminary heterogeneous integrated data framework for engineering is imported into the data filling tool, and by writing filling rules or using preset filling templates, the missing values or incomplete information in the data framework are filled and refined. For example, methods such as mean filling, median filling, or interpolation filling can be used to ensure the integrity and accuracy of the data, and finally, the heterogeneous integrated data for engineering is obtained.

[0142] Preferably, step S4 includes the following steps:

[0143] Step S41: Obtain a construction project terminology library;

[0144] Step S42: Determine construction project terms for the heterogeneous integrated data for engineering based on the construction project terminology library, and count the number of occurrences of the construction project terms;

[0145] Step S43: Set the construction engineering terms as index keywords and the number of occurrences of the construction engineering terms as index entry values to form a construction engineering information index;

[0146] Step S44: Extract the keywords and their number of occurrences from the construction engineering information index, retrieve the construction engineering documents containing the extracted keywords according to the number of occurrences of the keywords, and sort them by the keyword occurrence frequency to obtain construction engineering document data;

[0147] Step S45: Classify the construction engineering document data into construction records, quality inspection reports, and rectification progress categories to obtain engineering document category data; assign a unique identification code to each engineering document category data, and record the association relationship between the construction engineering documents and the construction engineering projects to obtain engineering association relationship data;

[0148] Step S46: Store the engineering document category data and the engineering association relationship data in a distributed data warehouse, where each engineering document category data is stored in a different server node;

[0149] Step S47: Perform a construction engineering information index operation on the distributed data warehouse to obtain an information index result; perform a visual display on the information index result to obtain an information digital visualization report.

[0150] In the embodiments of the present invention, by accessing professional construction engineering terminology websites, such as the construction engineering terminology library in the Industrial Standard Library or Baidu Library, downloading and obtaining the construction engineering terminology library. This library contains a large number of construction engineering-related terms and their definitions, ensuring the accuracy and authority of the terms. Save the downloaded terminology library file in Excel or CSV format for subsequent processing. Use text analysis software, such as the Pandas library in Python, to process the engineering heterogeneous integration data. In specific operations, import the engineering heterogeneous integration data into a Pandas DataFrame, and import the list of terms in the construction engineering terminology library into the software. Through the text matching function, search and match the text content in the data to identify the number of times each term appears in the data. For example, the str.contains method in Pandas can be used, combined with the term list, to check each item of the text content in the data, count the number of times each term appears, and save the results to a new DataFrame to form the data of the number of times construction engineering terms appear. Use an index construction tool, such as Elasticsearch, to set the construction engineering terms as index keywords and the number of times construction engineering terms appear as index entry values. In specific operations, import the terms and their number of times data obtained in step S42 into Elasticsearch to create a new index. Through the index management function of Elasticsearch, define the index structure, set the terms as text fields and the number of times as integer fields. Then, insert each term and its number of times as a document into the index to form a construction engineering information index to support subsequent information retrieval. Use Elasticsearch for information indexing operations to query and retrieve construction engineering information according to the construction engineering information index. In specific operations, through the query function of Elasticsearch, write a query statement to retrieve the distribution of specific terms or combinations of terms in the data to obtain the information index result. Then, use a data visualization tool, such as Tableau or PowerBI, import the information index result into the tool, and display the information index result in an intuitive way by creating charts, reports, etc. For example, a bar chart can be created to show the number of times different terms appear, or a map can be created to show the distribution of terms in different regions. Finally, generate an information digital visualization report to provide data support for the management and decision-making of construction engineering and complete the digital management operation of construction engineering information. The operator logs in to a professional construction engineering terminology website, such as the construction engineering terminology library page in the Industrial Standard Library or Baidu Library. Find the download option for the construction engineering terminology library on the website, click the download button, and save the terminology library file to the local computer. This terminology library file is usually in Excel or CSV format. The operator starts the text analysis software, such as the Pandas library in Python.First, import the engineering heterogeneous integrated data file (such as in Excel or CSV format) into a Pandas DataFrame. Then, import the previously downloaded construction engineering terminology library file into the software as well to form a terminology list. Use the text matching function of the software to check the text content in the engineering heterogeneous integrated data item by item, and search for and match each term in the terminology list. Whenever a term is found, record the number of times it appears. Finally, summarize all terms and their occurrence times, save them into a new DataFrame to form the construction engineering term occurrence times data, providing a basis for subsequent steps. The operator opens an index construction tool, such as Elasticsearch. In the management interface of Elasticsearch, create a new index named "Construction Engineering Information Index". Through the index management function of Elasticsearch, define the index structure, set the construction engineering terms as the index keyword field with the type of text; set the construction engineering term occurrence times as the index entry value field with the type of integer. Then, import the term and its occurrence times data obtained in step S42 item by item into this newly created index. Each term and its occurrence times are inserted into the index as a document, thus forming a complete construction engineering information index, providing efficient support for subsequent information retrieval. The operator uses the query function of Elasticsearch to query and retrieve construction engineering information based on the construction engineering information index. In the query interface, enter a specific query statement, such as searching for the distribution of a specific term or term combination in the data. After executing the query, Elasticsearch returns the information index result, including the matching terms and their related information. Next, the operator starts a data visualization tool, such as Kibana. In Kibana, import the information index result returned by Elasticsearch into the tool. Utilize the visualization function of Kibana to create various charts and reports, such as a bar chart showing the occurrence times of different terms, or a map showing the distribution of terms in different regions. Finally, generate an information digital visualization report to intuitively display the analysis results of construction engineering information, providing strong data support for the management and decision-making of construction engineering, thus completing the digital management operation of construction engineering information.

[0151] In this specification, a digital management system for construction engineering information based on data analysis is provided, which is used to execute the above-mentioned digital management method for construction engineering information based on data analysis. The digital management system for construction engineering information based on data analysis includes:

[0152] The construction project information collection module is used to obtain construction project information and perform preprocessing to obtain standard construction project information; determine the project stage based on the standard construction project information, thereby generating construction project stage data;

[0153] The building type classification module is used to identify the stage nodes of the construction project stage data and extract the project stage process information; classify the standard construction project information according to the project stage process information to generate construction project type data;

[0154] The project information quality assessment module is used to determine the project quality indicators of the construction project type data and perform project information quality assessment on the standard construction project information based on the project quality indicators to obtain a project information quality assessment report; perform project compliance information heterogeneous integration on the standard construction project information according to the project information quality assessment report to obtain project heterogeneous integration data;

[0155] The project information digital management module is used to count the number of occurrences of project terms in the project heterogeneous integration data and establish a construction project information index according to the number of occurrences of project terms; perform information digital management of the construction project information according to the construction project information index.

[0156] Through the construction project information collection module, the present invention acquires and preprocesses construction project information, can standardize the construction project information, ensuring the consistency and accuracy of the data, making the data easier to be recognized and utilized. It determines the engineering stage information for the standard construction project information, clarifies the key information of the construction project at different stages, facilitating the effective monitoring and management of the project progress and improving the refinement level of project management. Through the building type classification module, it identifies the stage nodes for the construction project stage data and extracts the engineering stage process information, which can clearly show each stage of the construction project and their mutual relationships. According to the engineering stage process information, it classifies the standard construction project information by building type, enabling the information of different types of construction projects to be classified and managed, further enhancing the pertinence and effectiveness of construction project information management. Through the engineering information digital management module, it determines the engineering quality indicators for the construction project type data and conducts an engineering information quality assessment on the standard construction project information based on the engineering quality indicators, comprehensively understanding the quality status of the construction project information, promptly discovering the problems existing in the information, and providing a reliable basis for subsequent information processing and engineering decision-making; according to the engineering information quality assessment report, it conducts heterogeneous integration of engineering compliance information on the standard construction project information, realizing the effective integration of engineering compliance information from different sources and in different formats, breaking the information silos, and improving the sharing and availability of data. Through the engineering information digital management module, it counts the occurrence times of engineering terms for the engineering heterogeneous integration data and establishes a construction project information index based on the occurrence times of the engineering terms, facilitating the quick retrieval and positioning of construction project information, improving the efficiency of information query, and providing convenience for engineering personnel to obtain the required information in the design, construction, operation and maintenance and other links. According to the construction project information index, it conducts digital management of the construction project information to complete the digital management operation of the construction project information, realizing the systematic and standardized management of the construction project information, improving the efficiency and quality of project management, and promoting the digital transformation of the construction project industry. Therefore, through data analysis technology, pattern recognition technology and deep learning technology, the present invention realizes the subdivision of construction project types and conducts corresponding engineering information quality assessments on the characteristics of the subdivided construction project types, thereby improving the efficiency of digital management of construction project information.

[0157] Therefore, in any aspect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to cover all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0158] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A digital management method for construction engineering information based on data analysis, characterized in that: The following steps are involved: Step S1: Acquire construction project information and perform preprocessing to obtain standard construction project information; Determine the project phase according to standard construction project information, thereby generating construction project phase data; Step S2: Identify the phase nodes of the construction project phase data and extract the project phase process information; Classify standard construction project information into building types according to the project phase process information to generate construction project type data; Step S3: Determine the engineering quality index of the construction engineering type data, and perform engineering information quality assessment on the standard construction engineering information based on the engineering quality index to obtain an engineering information quality assessment report; perform engineering compliance information heterogeneous integration on the standard construction engineering information according to the engineering information quality assessment report to obtain engineering heterogeneous integrated data; Step S4: Count the number of times the engineering terms appear in the engineering heterogeneous integrated data, and establish a construction engineering information index based on the number of times the engineering terms appear; perform digital information management of the construction engineering information based on the construction engineering information index.

2. The digital management method for construction engineering information based on data analysis according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Obtain construction project information; Step S12: performing a preprocessing operation on the construction project information, the preprocessing operation including removing missing values ​​of the construction text information and enhancing the contrast of the construction image information to obtain standard construction project information; Step S13: determining the engineering timestamp of the standard construction engineering information; dividing the engineering timestamp into time stages to obtain time stage data; Step S14: matching the standard construction project information with the project phase according to the time phase data to obtain the project matching phase; mapping the construction project information with the project matching phase to generate the construction project phase data.

3. The digital management method for construction engineering information based on data analysis according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: Performing engineering keyword recognition on the construction engineering phase data, identifying the engineering keywords of start, completion, entry and acceptance, and recording the phase information of the engineering keywords to obtain engineering keyword phase data; Step S22: sorting the engineering keyword phase data in chronological order to form a phase node sequence; extracting phase process information from the construction engineering phase data according to the phase node sequence to obtain engineering phase process information; Step S23: extracting construction procedures, required quantities of building materials and construction parameters from the engineering phase process information to obtain the design objectives of the building project; Step S24: Determine the construction function of the building design target, and classify the standard building information into building types based on the construction function to generate building type data.

4. The digital management method for construction engineering information based on data analysis according to claim 3 is characterized in that: Step S24 includes the following steps: Step S241: traverse the text of the building engineering design target, extract the residential, office and shopping mall building function keywords, and record the frequency and context description of each building function keyword to obtain the building function content information; Step S242: determining the functional area of ​​the building functional content information, and by counting the area ratio of the functional areas of the building functional information, if the office area ratio exceeds 50%, determining that the function of the construction building is an office building; Step S243: performing the function area judgment described in step S242 on each building function keyword to determine the construction building function type; Step S244: classifying the standard construction project information into building types according to the construction building function type. If the construction building function is an office building, the construction project is classified into an office building type. Step S245: Classify each type of construction building function type according to the building type classification described in step S244 to obtain construction project type data.

5. The digital management method of construction engineering information based on data analysis according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: determining the type quality standard of the construction project type data, and setting the project quality index for the type quality standard to generate the project quality index; Step S32: comparing the quality index of the standard construction project information with the project quality index to obtain quality index comparison data; evaluating the quality status of the project information using the quality index comparison data to obtain a project information quality evaluation report; Step S33: Perform heterogeneous integration of engineering compliance information on standard construction engineering information according to the engineering information quality assessment report to obtain heterogeneous engineering integration data.

6. The digital management method for construction engineering information based on data analysis according to claim 5 is characterized in that: Step S31 The following steps are involved: Step S311: matching the construction engineering type data with the construction type industry to obtain the construction type industry data; Obtaining the type industry building quality standards from the building type industry data to generate type quality standards; Step S312: setting the compliance range of the indoor net height deviation of the building for the type quality standard, specifically setting it to not more than ±20 mm, to form the indoor net height deviation range data; Step S313: setting the compliance range of verticality deviation of building wall for the type quality standard, specifically setting it to not more than 3 mm, to form the verticality deviation range data of the wall; Step S314: setting the compliance range of the building ground flatness deviation for the type quality standard, specifically setting it to not more than 5 mm, to form ground flatness deviation range data; Step S315: Combine the indoor net height deviation range data, the wall verticality deviation range data and the ground flatness deviation range data to obtain a project quality index.

7. The digital management method of construction engineering information based on data analysis according to claim 5 is characterized in that: Step S32 includes the following steps: Step S321: extracting the indoor net height of the building from the standard construction project information, recording the height difference between the indoor net height of the building and the preset indoor net height of the building, and if the height difference meets the engineering quality index, the indoor net height is judged to be qualified, otherwise, the indoor net height is judged to be unqualified, so as to obtain indoor net height comparison data; Step S322: extracting the verticality of the building wall of the standard construction project information, recording the verticality difference between the building wall verticality and the preset building wall verticality, and if the verticality difference meets the engineering quality index, it is judged that the wall verticality is qualified, otherwise, it is judged that the wall verticality is unqualified, so as to obtain the wall verticality comparison data; Step S323: extracting the flatness of the building ground of the standard construction project information, recording the flatness difference between the building ground flatness and the preset building ground flatness, and if the flatness difference meets the engineering quality index, it is judged that the flatness difference is qualified, otherwise, it is judged that the flatness difference is unqualified, so as to obtain ground flatness comparison data; Step S324: performing net height compliance frequency measurement on the indoor net height comparison data, and calculating the ratio of qualified to unqualified indoor net height comparison data to obtain the indoor net height qualified rate; Step S325: performing verticality deviation value distribution identification on the wall verticality comparison data, detecting the discrete distribution characteristics of the deviation value, and obtaining the discrete degree of the wall verticality; Step S326: measuring the flatness coverage value of the ground flatness comparison data, calculating the ratio of the total building area to the flatness area, and obtaining the ground flatness coverage value; Step S327: assign a weight of 0.3 to the indoor net height qualification rate, a weight of 0.4 to the wall verticality dispersion degree, and a weight of 0.3 to the ground flatness coverage value, to form engineering quality weight assignment data; Step S328: Perform weighted calculation and evaluation based on the engineering quality weight assignment data to obtain an engineering information quality evaluation report.

8. The digital management method for construction engineering information based on data analysis according to claim 7 is characterized in that: Step S33 includes the following steps: Step S331: Perform threshold screening on the indoor net height qualification rate data in the project information quality assessment report, set the qualification rate threshold to 80%, screen out the construction project information with a qualification rate below the threshold, mark it as a net height concern project, and obtain the net height compliance concern data; Step S332: dividing the wall verticality discrete degree data into three intervals: low, medium and high, corresponding to the discrete degree ranges of less than 1 mm, 1 mm to 3 mm, and greater than 3 mm, respectively, counting the number of building project information in each interval, and obtaining the wall verticality discrete interval distribution data; Step S333: Perform compliance determination on the ground flatness coverage value data, set the compliance coverage value to 90%, determine whether the ground flatness coverage value reaches or exceeds the compliance value, mark the unqualified construction project information as a flatness rectification project, and obtain ground flatness compliance determination data; Step S334: associating and merging the net height compliance concern data, the wall verticality discrete interval distribution data, and the ground flatness compliance determination data, and constructing a heterogeneous data framework of engineering compliance information to obtain a preliminary engineering heterogeneous integrated data framework; Step S335: Fill and refine the preliminary engineering heterogeneous integration data framework to obtain engineering heterogeneous integration data.

9. The digital management method for construction engineering information based on data analysis according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: Acquire a vocabulary of architectural engineering terms; Step S42: determining the construction engineering terms for the heterogeneous engineering integrated data based on the construction engineering terminology lexicon, and counting the number of occurrences of the construction engineering terms; Step S43: setting the construction engineering term as an index keyword and the number of occurrences of the construction engineering term as an index entry value to form a construction engineering information index; Step S44: extracting keywords and their occurrence times from the construction project information index, searching for construction project documents containing the extracted keywords according to the keyword occurrence times, and sorting them by keyword occurrence frequency to obtain construction project document data; Step S45: Classify the construction project document data into construction records, quality inspection reports, and rectification progress categories to obtain project document category data; assign a unique identification code to each project document category data, and record the association between the construction project document and the construction project to obtain project association relationship data; Step S46: storing the engineering document category data and the engineering association relationship data in a distributed data warehouse, wherein each engineering document category data is stored in a different server node; Step S47: Perform construction project information indexing operation on the distributed data warehouse to obtain information indexing results; visualize the information indexing results to obtain an information digital visualization report.

10. A digital management system for construction engineering information based on data analysis, characterized in that: Used to execute the digital management method of construction engineering information based on data analysis as claimed in claim 1, the digital management system of construction engineering information based on data analysis comprises: The construction project information acquisition module is used to obtain construction project information and pre-process it to obtain standard construction project information; determine the project stage according to the standard construction project information, thereby generating construction project stage data; The building type classification module is used to identify the phase nodes of the construction project phase data and extract the project phase process information; the standard construction project information is classified into building types according to the project phase process information to generate construction project type data; The engineering information quality assessment module is used to determine the engineering quality indicators of the construction engineering type data, and to perform engineering information quality assessment on the standard construction engineering information based on the engineering quality indicators to obtain an engineering information quality assessment report; and to perform heterogeneous integration of engineering compliance information on the standard construction engineering information according to the engineering information quality assessment report to obtain heterogeneous engineering integration data; The engineering information digital management module is used to count the number of times engineering terms appear in engineering heterogeneous integrated data, and to establish a construction engineering information index based on the number of times engineering terms appear; and to perform digital management of construction engineering information based on the construction engineering information index.

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