Engineering archive inspection method and system

Abstract

The invention relates to the technical field of computer software, in particular to an engineering archive checking method and system.The method comprises the steps that an engineering archive is divided into five core stages including engineering preparation, construction files, supervision files, as-built drawings and as-built files, data sub-items are subdivided, and the item missing rate is calculated by dynamically configuring the stage weight lambda of 0.5-1.5; a comprehensive lacking index is generated in combination with the proportion of multiple full files, differential rectification is executed according to the characteristics of all stages, and year-on-year and link-on-year analysis and abnormal fluctuation recognition of historical data are supported. The system is correspondingly provided with a stage hierarchical construction module, a lacking data calculation module, a differential rectification module and other core modules, and data hierarchical visual display and full-process digital management are achieved. According to the method, the problems of fuzzy lacking item positioning, rectification disjunction and insufficient quantitative evaluation in the prior art are solved, and standardization and precision of engineering file management are realized.

Description

Technical Field

[0001] This invention belongs to the field of computer software technology, and specifically relates to a method and system for inspecting engineering files. Background Technology

[0002] In the entire lifecycle management of engineering construction, engineering archives serve as the core basis for project compliance verification, completion filing, and subsequent operation and maintenance. Their completeness and standardization directly impact project progress efficiency and long-term management quality. Current engineering archive management systems primarily focus on archive storage and basic query functions. However, significant technical deficiencies remain in key areas such as detailed archive inspection display, closed-loop management of missing item rectification, and quantitative assessment of completeness. These deficiencies fail to meet the actual needs of complex engineering scenarios, as detailed below: (1) Vague location of missing items and low diagnostic efficiency: Existing systems mostly adopt a flat file management model and have not established a phased and hierarchical inspection system based on the business logic of the project. This makes it impossible to realize the hierarchical display of missing items in the project files. It can only count the total number of missing items for the entire project, and it is difficult to accurately locate the project stage (such as project preparation, construction, completion, etc.) and specific data items (such as construction test records, supervision and acceptance data, etc.) to which the missing items belong. This results in managers having to spend a lot of time to investigate the root cause of missing items, and the problem diagnosis efficiency is low, making it impossible to quickly identify high-risk missing item areas.

[0003] (2) Disconnection between rectification operations and lack of practicality: The existing technology lacks a linkage mechanism for recording the reasons for missing items and binding them with targeted archives, resulting in a disconnect between inspection results and rectification actions. On the one hand, there is no mandatory requirement to record the reasons for missing items (such as incomplete approvals or unsubmitted documents), leading to an unclear direction for rectification. On the other hand, there is no design of exclusive binding rules and verification logic for different types of archives. For example, the binding of preliminary approval documents, construction process data, and as-built drawings is not adapted to their business characteristics, and there is a lack of cross-unit collaborative confirmation processes, making it difficult to transform the problems found in the inspection into standardized and practical rectification operations, and making it difficult to form a closed-loop rectification system.

[0004] (3) Insufficient data visualization and quantitative assessment: The existing system lacks the ability to dynamically calculate and summarize missing data in multiple dimensions, and cannot intuitively reflect the severity of the problem of archival integrity. First, it has not achieved real-time statistics of core indicators such as the number of missing items and the missing item rate, nor has it established a comprehensive missing item assessment system for multiple participating units (collections), making it difficult for managers to quickly grasp the overall archival status and core problem areas of the project; second, it lacks phased risk identification and progress visualization functions, and cannot use intuitive forms (such as color labels and progress bars) to indicate high missing item rate stages; third, it does not support year-on-year and month-on-month analysis of historical missing item data, making it impossible to trace the trend of missing item changes, and there is no abnormal fluctuation early warning mechanism, making it difficult to avoid archival management risks in advance.

[0005] In view of this, the present invention is hereby proposed. Summary of the Invention

[0006] In order to solve the above-mentioned technical problems in the prior art, the present invention provides an engineering file inspection method and system, which solves the problems of vague positioning of missing items, disconnection of rectification, and insufficient quantitative evaluation in the prior art, and realizes the standardization, precision and intelligence of engineering file inspection and rectification.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows: Firstly, a method for inspecting engineering documents includes: S1. Divide the project archives into multiple core stages according to the preset business logic, and subdivide each core stage into at least one data item to build a hierarchical inspection system. S2. Obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing data of each core stage and corresponding data item. S3. Based on the business characteristics of each core stage, perform differentiated rectification operations, including recording the reasons for missing items, binding files, and verifying compliance. S4. Use dynamically configured weighting coefficients to perform weighted calculations on the missing item-related data of each core stage to obtain the stage missing item rate data; S5. Calculate the project's comprehensive missing item index based on the missing item rate of each core stage and the proportion of multiple archival documents; S6. Visualize the missing data, missing rate, and comprehensive missing index of the core stage and data items.

[0008] Furthermore, the multiple core stages include the project preparation stage, the construction document stage, the supervision document stage, the as-built drawing stage, and the as-built document stage; The data items for the project preparation phase include decision-making and project approval, surveying and design, construction land and commencement documents; The data items in the construction document stage include engineering management technical data, construction survey records, construction materials, construction test records and inspection reports, and construction quality acceptance records; The documents in the supervision document stage include supervision control documents, supervision management documents, and supervision acceptance documents; The data items in the as-built drawing stage include as-built drawings covering architecture, structure, and mechanical and electrical engineering. The documents for the completion document stage include handover documents, maintenance information, and special acceptance documents.

[0009] Furthermore, the missing data includes the number of missing files and the total number of files that should be archived; The formula for calculating the stage missing item rate data is as follows:

[0010] in, These are dynamically configured weighting coefficients.

[0011] Furthermore, the weight coefficient ranges from 0.5 to 1.5. By storing configuration data in JSON format in a preset field added to the task configuration table, it is possible to customize the weight coefficient value of each core stage according to the project type.

[0012] Furthermore, the differentiated rectification operations described in step 3 specifically include: Project preparation phase: Record the reasons for missing items and their associated approval process status; bind and verify the document type to be either project approval or land use planning permit. Construction document stage: Supports uploading files in batches by document item and automatically matches classification rules; As-built drawing stage: The file is bound to the drawing version number and design change order, and the file extension is verified to be .dwg; Supervision document stage: The record of reasons for missing items is forcibly associated with the supervision unit, and the rectification process triggers collaborative confirmation from the supervision party; As-built documentation stage: Verify that the archives contain valid signatures and seals from government departments.

[0013] Furthermore, the rectification operations in the supervision document stage and the completion document stage are also linked to the system process configuration module, triggering a multi-level approval process. The supervision document stage requires dual confirmation from the supervising engineer and the project manager.

[0014] Furthermore, the formula for calculating the comprehensive shortage index of the project is as follows:

[0015] in, For the entire collection's serial number, This represents the total number of records.

[0016] Furthermore, the visualization described in step 6 includes: Color-coded labels are used to mark the risk level of each core stage, with stages where the missing item rate exceeds a preset threshold highlighted in red. A progress bar is set at the bottom of the page, which can be clicked to expand the completion status of each core stage; When you hover the mouse over the core stage name, it displays the total number of files that should be archived and the number of missing files for that stage.

[0017] Furthermore, it also includes historical data comparison and analysis steps: A time-series database is used to store historical missing item rate data for each core stage; Implement year-on-year analysis of the missing item rate in the current stage compared with the same period of the previous year using SQL window functions; By combining the moving average algorithm to reduce noise in the quarterly missing item rate data, abnormal fluctuation points with an increase of more than 15% in two consecutive periods can be identified.

[0018] Secondly, an engineering document inspection system includes: The stage hierarchy construction module is used to divide the project archives into multiple core stages according to the preset business logic. Each core stage is further subdivided into at least one data item to build a hierarchical inspection system. The missing data calculation module is used to obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing data related to each core stage and corresponding data items. The differentiated rectification module is used to perform differentiated rectification operations based on the business characteristics of each core stage. The rectification operations include recording the reasons for missing items, binding files, and verifying compliance. The stage missing item rate calculation module is used to perform weighted calculation on the missing item related data of each core stage using dynamically configured weight coefficients to obtain the stage missing item rate data. The comprehensive index calculation module is used to calculate the comprehensive missing item index of the project based on the missing item rate of each core stage and the proportion of multiple archival documents; The visualization module is used to visualize the missing item-related data, the stage missing item rate data, and the comprehensive missing item index.

[0019] Compared with existing technologies, the engineering archive inspection method and system provided by this invention includes: dividing engineering archives into five core stages—engineering preparation, construction documents, supervision documents, as-built drawings, and as-built documents—and further subdividing them into data items; calculating the missing item rate by dynamically configuring a stage weight λ of 0.5-1.5; generating a comprehensive missing item index by combining the proportion of multiple archival documents; implementing differentiated rectification according to the characteristics of each stage; and supporting year-on-year and month-on-month analysis of historical data and identification of abnormal fluctuations. The system includes core modules such as stage hierarchy construction, missing item data calculation, and differentiated rectification, achieving hierarchical and visual data display and full-process digital management. This invention solves the problems of vague missing item location, disjointed rectification, and insufficient quantitative assessment in existing technologies, achieving standardization and precision in engineering archive management. Attached Figure Description

[0020] Figure 1 A flowchart of an engineering file inspection method provided in an embodiment of the present invention; Figure 2 This is an architecture diagram of an engineering file inspection system provided in an embodiment of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0022] It should be noted that, unless otherwise specifically stated, the relative arrangement and numerical expressions of the components and steps described in these embodiments should not be construed as limiting the scope of the invention.

[0023] The following description of exemplary embodiments is merely illustrative and is not intended to limit the invention or its application or use in any way. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but where applicable, such techniques, methods, and apparatus should be considered part of this specification.

[0024] Example 1 See Figure 1 , Figure 1 This is a flowchart of an engineering file inspection method proposed in this invention. Specific steps may include: S1. Divide the project archives into multiple core stages according to the preset business logic. Each core stage is further subdivided into at least one data item to build a hierarchical inspection system. The multiple core stages include the project preparation stage, construction document stage, supervision document stage, as-built drawing stage, and as-built document stage. The data items in the project preparation phase include decision-making and project approval, surveying and design, construction land and commencement documents; The documents in the construction documentation stage include engineering management technical documents, construction survey records, construction materials, construction test records and inspection reports, and construction quality acceptance records. The documents in the supervision document stage include supervision control documents, supervision management documents, and supervision acceptance documents; The data items in the as-built drawing stage include as-built drawings covering architecture, structure, and mechanical and electrical engineering. The documents required for the completion documentation stage include handover documents, maintenance information, and special acceptance documents.

[0025] Referring to Table 1, each core stage is defined by checking the stage field (fixed enumeration value) of the detailed data table (archive_detail). The stage_order field controls the display order, ensuring that the front end presents the business process according to the project preparation stage, construction document stage, supervision document stage, as-built drawing stage, and as-built document stage.

[0026] Table 1

[0027] S2. Obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing data of each core stage and corresponding data item. Specifically, the archive data corresponding to the engineering archive inspection task is obtained, and the data is filtered by querying the inspection details data table through SQL statements. The query statement is constructed according to "task_id filtering, stage_order and data item display order sorting". Based on the hierarchical inspection system constructed in step S1, the core stages are grouped, and the number of missing documents and the total number of documents to be archived in each core stage and corresponding data item are calculated respectively. At the same time, the number of documents in each collection and the total number of documents in the project are counted.

[0028] S3. Based on the business characteristics of each core stage, implement differentiated rectification operations, including recording the reasons for missing items, binding files, and verifying compliance; specifically including: Project preparation phase: Record the reasons for missing items and link them to the status of the approval process. During the file binding process, verify that the document type is a preliminary document such as the project approval document and land use planning permit, and force the association of the whole land parcel information. Construction document stage: Supports uploading files in batches by document item. The system automatically matches the classification rules of the item and can bind files according to the dimension of "construction stage - sub-project". As-built drawing stage: The file binding operation associates the drawing version number and design change order, verifies that the file extension is ".dwg" and contains the keyword "as-built drawing", and automatically marks the old version missing files as "updated" when binding new version drawings; Supervision document stage: The record of missing items is forcibly associated with the supervision unit, the rectification process triggers the supervision party's collaborative confirmation, the document creator must be the supervision unit's account, and it is linked to the system process configuration module. Rectification must be completed after double confirmation by the supervision engineer and the project manager. During the completion document stage: when binding the submitted documents, verify whether the documents contain a valid signature issued by the government department, and link the rectification operation with the system process configuration module to trigger a multi-level approval process.

[0029] The rectification operations in the supervision document stage and the completion document stage are also linked to the system process configuration module, triggering a multi-level approval process. Among them, the supervision document stage requires double confirmation from the supervising engineer and the project manager.

[0030] S4. Use dynamically configured weighting coefficients to perform weighted calculations on the missing item-related data for each core stage to obtain the stage missing item rate data; the missing item-related data includes the number of missing files and the total number of files that should be archived. The formula for calculating the stage missing item rate data is:

[0031] in, The weighting coefficients are dynamically configured.

[0032] The weight coefficient ranges from 0.5 to 1.5. The configuration data in JSON format is stored in a preset field added to the task configuration table, and the weight coefficient value of each core stage can be customized according to the project type.

[0033] In this step, the system supports customizing the weighting coefficients for each stage through a backend configuration table. (Value range: 0.5-1.5). In practice, a new field called `stage_weight_config` is added to the task configuration table (`task_config`) to store JSON format data.

[0034] Example application scenario: For subway construction projects, due to the high risks during the construction phase, the administrator sets the configuration to {"Project Preparation": 0.8, "Construction Documents": 1.3, "As-built Drawings": 1.2}; During calculation, the system parses the JSON and extracts the corresponding coefficients for calculation; if 50 construction documents are missing at a certain stage and 200 documents should be archived, then the missing item rate for that stage is... Instead of the traditional 25%, this strengthens the early warning weight for high-risk phases.

[0035] S5. Based on the missing item rate of each core stage and the proportion of multiple archival documents, calculate the project's comprehensive missing item index; the formula for calculating the project's comprehensive missing item index is:

[0036] in, For the entire collection's serial number, This represents the total number of archival records. Before calculation, the file numbering rules and document item mapping relationships of different archival records are standardized through the metadata standardization module. A combined index is established by archival record and stage, and a distributed computing framework is used to achieve real-time data aggregation.

[0037] In this step, for large projects involving multiple participating units (collection sites), the system performs data standardization preprocessing (unified file numbering rules) and then uses a weighted aggregation method to calculate the comprehensive index.

[0038] Specific calculation example: Assume the project includes "civil engineering" (accounting for 60%) and "mechanical and electrical engineering" (accounting for 40%).

[0039] Civil engineering portfolio: The missing item rate during the acceptance phase is calculated as 18%; Mechanical and electrical complete sets: The missing item rate is calculated as 10% during the acceptance phase; Substituting the formula described in the claims: .

[0040] This algorithm avoids the errors caused by simple averaging and truly reflects the impact of the large-scale civil engineering data collection, which has a significant weighting, on overall compliance.

[0041] S6. Visualize the missing data, missing rate, and comprehensive missing index for the core stages and data items. The visualization includes: S61. Use color labels to mark the risk level of each core stage. Stages with a missing item rate exceeding a preset threshold are highlighted in red. Specifically, the number of missing documents, the total number of documents to be archived, and the missing rate of each data item are displayed in groups according to the core stage. Stages with a missing rate exceeding a preset threshold are highlighted in red. S62. A progress bar is set at the bottom of the page, which can be clicked to expand the completion status of each core stage; Specifically, a total row is set at the bottom of the page to summarize the total number of missing documents, the total number of documents to be archived, and the overall missing document index for the entire project. It supports detailed totals by core stage. A progress bar is set at the bottom of the page. Clicking the progress bar can expand the completion status of each core stage. Together with the status indicator lights, it forms a three-level visualization system of global progress, stage details, and item details. S63. When the mouse hovers over the name of a core stage, the total number of files that should be archived and the number of missing files for that stage are displayed.

[0042] S7. Historical data comparison and analysis, the specific steps of which include: S71. Use a time-series database to store historical missing item rate data for each core stage; Specifically, a time-series database is used to store historical missing data for each core stage and data item, supporting multi-year data storage. Data compression algorithms are used for long-term historical data, and storage is optimized by combining a hot and cold data separation strategy. S72. Use SQL window functions to perform year-on-year analysis of the missing item rate in the current stage compared with the same period of the previous year; Specifically, year-on-year analysis is performed using SQL window functions to compare the missing item rate of the current stage with that of the same period of the previous year. When there are differences in the division of project stages in different years, cross-year data alignment is achieved through a stage mapping algorithm. S73. Combine the moving average algorithm to reduce noise in the quarterly missing item rate data and identify abnormal fluctuation points where the increase exceeds 15% for two consecutive periods.

[0043] Specifically, a quarterly missing item rate fluctuation curve is generated, and the data is denoised using a moving average algorithm to identify abnormal fluctuation points where the increase exceeds the preset standard for two consecutive periods.

[0044] The specific historical data processing flow in this step is as follows: Data storage: A time-series database (such as InfluxDB) is used to store the historical missing item rate for each stage, and cold data older than 3 years is stored using compression.

[0045] Year-on-year analysis: The backend interface directly retrieves the data from the same period of the previous year using SQL window functions (such as LAG(rate,12)OVER(ORDERBYtime)) and calculates the difference. For example, if the missing item rate in the 2025 acceptance phase decreased by 5% compared to 2024, the frontend will display a green downward arrow.

[0046] Anomaly Detection: The system applies a moving average (MA) algorithm to filter noise from quarterly data. If the system detects that the increase in data exceeds a preset threshold (e.g., 15%) for two consecutive periods, and after excluding external factors such as project changes (related change orders), the system automatically triggers an 'abnormal fluctuation' warning and marks it as a high-risk trend.

[0047] Example 2 See Figure 2 , Figure 2 The present invention provides an architecture diagram of an engineering document inspection method and system, comprising: M1, the stage hierarchy construction module, is used to divide the project archives into multiple core stages according to the preset business logic. Each core stage is further subdivided into at least one data item to build a hierarchical inspection system. M2, Missing Item Data Calculation Module, is used to obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing item related data for each core stage and corresponding data item; M3, the differentiated rectification module, is used to perform differentiated rectification operations based on the business characteristics of each core stage. The rectification operations include recording the reasons for missing items, binding files, and verifying compliance. M4, the stage missing item rate calculation module, is used to perform weighted calculation on the missing item related data of each core stage using dynamically configured weight coefficients to obtain the stage missing item rate data. M5, the comprehensive index calculation module, is used to calculate the comprehensive missing item index of the project based on the missing item rate of each core stage and the proportion of multiple archival documents; M6, Visualization module, is used to visualize the missing item related data, stage missing item rate data, and comprehensive missing item index.

[0048] In summary, the present invention has the following advantages: 1. More precise identification of missing items: By constructing a hierarchical inspection system with five core stages (project preparation, construction documents, supervision documents, as-built drawings, and as-built documents) and subdivided data items, it replaces the traditional flat management and can directly pinpoint the stage and specific item to which the missing item belongs, eliminating the need for blind investigation and greatly improving the efficiency of problem diagnosis. 2. The rectification process is more aligned with actual business operations. Customized rectification rules are designed for the characteristics of each stage, enabling full-process linkage of missing item reason recording, file binding and compliance verification. At the same time, the cross-unit collaborative confirmation mechanism is strengthened to ensure that the rectification operation is standardized and implementable, and to guarantee the compliance of the archives. 3. The quantitative assessment is more scientific. The dynamic weighting coefficient can be adapted to different project types and stage risks. The comprehensive missing item index is calculated by combining the proportion of multiple archival documents, which replaces the traditional simple proportion assessment. It accurately reflects the integrity of the archives and solves the problem that the traditional assessment method cannot be adapted to complex scenarios. 4. It has the ability to analyze historical trends, store and analyze missing data from many years of history, support year-on-year and month-on-month comparisons, effectively identify abnormal fluctuations, trace the changing trends and influencing factors, provide data support for optimizing record management, and avoid risks in advance. 5. The system boasts excellent adaptability and processing efficiency, enabling it to efficiently process large-scale archival data. Through standardized stage division and flexible configuration mechanisms, it adapts to engineering projects of different scales and types, significantly improving the standardization and intelligence level of engineering archive management.

[0049] The above specific embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An engineering archive inspection method, characterized by, include: S1. Divide the project archives into multiple core stages according to the preset business logic, and subdivide each core stage into at least one data item to build a hierarchical inspection system. S2. Obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing data of each core stage and corresponding data item. S3. Based on the business characteristics of each core stage, perform differentiated rectification operations, including recording the reasons for missing items, binding files, and verifying compliance. S4. Use dynamically configured weighting coefficients to perform weighted calculations on the missing item-related data of each core stage to obtain the stage missing item rate data; S5. Calculate the project's comprehensive missing item index based on the missing item rate of each core stage and the proportion of multiple archival documents; S6. Visualize the missing data, missing rate, and comprehensive missing index of the core stage and data items.

2. The engineering archive inspection method of claim 1, wherein, The multiple core phases include the project preparation phase, construction document phase, supervision document phase, as-built drawing phase, and as-built document phase; The data items for the project preparation phase include decision-making and project approval, surveying and design, construction land and commencement documents; The data items in the construction document stage include engineering management technical data, construction survey records, construction materials, construction test records and inspection reports, and construction quality acceptance records; The documents in the supervision document stage include supervision control documents, supervision management documents, and supervision acceptance documents; The data items in the as-built drawing stage include as-built drawings covering architecture, structure, and mechanical and electrical engineering. The documents for the completion document stage include handover documents, maintenance information, and special acceptance documents.

3. The engineering archive inspection method of claim 1, wherein, The missing data includes the number of missing files and the total number of files that should be archived. The formula for calculating the stage missing item rate data is as follows: wherein, is a dynamically configured weight coefficient.

4. The engineering archive inspection method of claim 3, wherein, The weight coefficient ranges from 0.5 to 1.

5. The configuration data in JSON format is stored in a preset field added to the task configuration table, which supports customizing the weight coefficient values ​​of each core stage according to the project type.

5. The engineering archive inspection method of claim 1, wherein, The differentiated rectification operations described in step 3 specifically include: Project preparation phase: Record the reasons for missing items and their associated approval process status; bind and verify the document type to be either project approval or land use planning permit. Construction document stage: Supports uploading files in batches by document item and automatically matches classification rules; As-built drawing stage: The file is bound to the drawing version number and design change order, and the file extension is verified to be .dwg; Supervision document stage: The record of reasons for missing items is forcibly associated with the supervision unit, and the rectification process triggers collaborative confirmation from the supervision party; As-built documentation stage: Verify that the archives contain valid signatures and seals from government departments.

6. The engineering archive inspection method of claim 5, wherein, The rectification operations at the supervision document stage and the completion document stage are also linked to the system process configuration module, triggering a multi-level approval process. The supervision document stage requires dual confirmation from the supervising engineer and the project manager.

7. The engineering archive inspection method of claim 1, wherein, The formula for calculating the comprehensive shortage index of the project is as follows: wherein is the total number of archons, is the total number of archons.

8. The engineered archive inspection method of claim 1, wherein, The visualization described in step 6 includes: Color-coded labels are used to mark the risk level of each core stage, with stages where the missing item rate exceeds a preset threshold highlighted in red. A progress bar is set at the bottom of the page, which can be clicked to expand the completion status of each core stage; When you hover the mouse over the core stage name, it displays the total number of files that should be archived and the number of missing files for that stage.

9. The engineered archive inspection method of claim 1, wherein, It also includes historical data comparison and analysis steps: A time-series database is used to store historical missing item rate data for each core stage; Implement year-on-year analysis of the missing item rate in the current stage compared with the same period of the previous year using SQL window functions; By combining the moving average algorithm to reduce noise in the quarterly missing item rate data, abnormal fluctuation points with an increase of more than 15% in two consecutive periods can be identified.

10. An engineering document inspection system, characterized in that, include: The stage hierarchy construction module is used to divide the project archives into multiple core stages according to the preset business logic. Each core stage is further subdivided into at least one data item to build a hierarchical inspection system. The missing data calculation module is used to obtain the archive data corresponding to the engineering archive inspection task, group the archive data based on the hierarchical inspection system, and calculate the missing data related to each core stage and corresponding data items. The differentiated rectification module is used to perform differentiated rectification operations based on the business characteristics of each core stage. The rectification operations include recording the reasons for missing items, binding files, and verifying compliance. The stage missing item rate calculation module is used to perform weighted calculation on the missing item related data of each core stage using dynamically configured weight coefficients to obtain the stage missing item rate data. The comprehensive index calculation module is used to calculate the comprehensive missing item index of the project based on the missing item rate of each core stage and the proportion of multiple archival documents; The visualization module is used to visualize the missing item-related data, the stage missing item rate data, and the comprehensive missing item index.

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