A distribution network construction completion acceptance management method and system

Abstract

The present invention discloses a method and system for the management of completion acceptance of distribution network construction, and relates to the technical field of distribution network engineering. By acquiring the acceptance demand data of distribution network construction projects, establishing an acceptance demand map, defining acceptance rules and standards, constructing a rule engine, and constructing a distribution network acceptance model according to a classification model, complex acceptance requirements and standards are effectively converted into executable models, thereby improving the automation and accuracy of the acceptance process. By utilizing the rule engine and classification algorithm of the distribution network acceptance model, the integrity of the document data of the completed distribution network construction project, the consistency of the equipment function data and the construction quality and safety data are reviewed and verified, and abnormal project documents are identified and marked to ensure the integrity of the document data. By generating a review coefficient and generating an acceptance report for storage, the efficiency of information storage and retrieval is improved, the subjectivity and error risk of manual operation are reduced, and the intelligent management of acceptance data is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network engineering, and in particular to a distribution network construction completion acceptance management method and system. Background Art

[0002] Distribution network projects involve complex construction processes, including cable laying, substation construction, equipment installation, etc. These processes need to follow strict construction process standards to ensure the safe, stable and efficient operation of the distribution network. However, due to the variability of construction environments and conditions, various problems may be encountered during the actual construction process, so strict standardized acceptance is required.

[0003] For example, a Chinese patent with announcement number CN117973947B discloses a method and system for standardized acceptance of construction technology for distribution network projects. The specific steps of the acceptance method are as follows: (1) collecting a large amount of distribution network project construction data and preprocessing it; (2) modeling and organizing professional knowledge in the field of distribution network engineering; (3) generating an initial construction plan and simulating and adjusting it; the invention reduces resource consumption and cost expenditure, reduces costs in the construction process, and improves the efficiency of standardized acceptance of construction technology. At the same time, it can more comprehensively evaluate the feasibility and robustness of the plan, help reduce decision-making risks and improve construction efficiency, effectively improve the accuracy and comprehensiveness of acceptance, make the acceptance process more intelligent and automated, reduce the influence of human subjective factors, and help improve the objectivity and reliability of acceptance, effectively reduce risks and adverse effects in the construction process, and ensure comprehensive quality control of the construction process.

[0004] The above-mentioned system can only accept the distribution network construction plan during the acceptance process, but cannot accept the distribution network construction project after completion. It currently relies on manual operations, including on-site inspection record writing, data recording and report writing. This method has the disadvantages of low efficiency, high risk of errors, strong subjectivity, difficult data management and high resource consumption. The large amount of paper records and documents generated during the manual acceptance process may lead to inconvenience in information management and difficulty in efficient retrieval and sharing. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for completing and accepting a distribution network, which solves the problems of the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a distribution network construction completion acceptance management system, comprising the following modules: a distribution network construction data acquisition module, a distribution network acceptance model construction module, an acceptance module, an abnormal marking module, and an acceptance management module; the distribution network construction data acquisition module is used to acquire the distribution network construction project acceptance demand data and the distribution network construction completion project data, and perform preprocessing; the distribution network acceptance model construction module is used to establish an acceptance demand map based on the distribution network construction project acceptance demand data, define acceptance rules and standards, build a rule engine, and build a distribution network acceptance model according to the classification model; the acceptance module includes an engineering document acceptance unit, an equipment function acceptance unit, and a quality and safety acceptance unit; the engineering document acceptance unit is used to review and verify the integrity of the distribution network construction completion project document data according to the rule engine of the distribution network acceptance model, identify abnormal project documents for primary marking, and send the abnormal project documents to the abnormal marking module; The equipment function acceptance unit is used to review and verify the consistency of the equipment function data of the completed distribution network construction project according to the classification algorithm of the distribution network acceptance model, identify abnormal equipment function data for primary marking, and send the abnormal equipment function data to the abnormal marking module; the quality and safety acceptance unit is used to review and verify the consistency of the distribution network construction quality and safety data according to the rule engine of the distribution network acceptance model, identify the construction quality and safety abnormal data and perform primary marking, and send the construction quality and safety abnormal data to the abnormal marking module; the abnormal marking module is used to receive abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, perform a secondary marking on it and send it to the acceptance management module; the acceptance management module is used to receive the secondary marked abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data, generate an acceptance report and store it.

[0007] Furthermore, the distribution network construction project acceptance requirement data includes distribution network construction project document acceptance requirement data, distribution network construction project equipment function acceptance requirement data, and distribution network construction quality and safety acceptance requirement data; the distribution network construction completed project data includes distribution network construction completed project document data, distribution network construction completed project equipment function data, and distribution network construction quality and safety data.

[0008] Furthermore, the specific process of establishing an acceptance requirement map, defining acceptance rules and standards, and building a rule engine is as follows: based on the acceptance requirement data of distribution network construction projects, text cleaning and word segmentation and annotation are performed, and through named entity recognition and relationship extraction of natural language processing, key entities including engineering documents, equipment functions and quality safety are determined, and the relationship between nodes is defined, and an acceptance requirement map is established, and the identified entities and relationships are visualized to form a structured acceptance requirement map; professional knowledge in the field of distribution network engineering is collected and combined with the acceptance standard data and special requirements data in the acceptance requirement data of distribution network construction projects, specific acceptance rules are written, including project document integrity, construction quality standards, and qualified thresholds are set, and compiled into specification documents; the specification documents are converted into an engine executable format through the Drools rule engine platform.

[0009] Furthermore, the specific process of constructing a distribution network acceptance model based on the classification model is as follows: the equipment function data of the completed distribution network construction project is loaded into the classification model, and the classification results of the classification model are passed as input data to the Drools rule engine to build the distribution network acceptance model.

[0010] Furthermore, according to the rule engine of the distribution network acceptance model, the integrity of the distribution network construction completed project document data is reviewed and verified, and the specific process of identifying abnormal project documents is as follows: the distribution network construction completed project document data, including design drawings, construction record documents, and test report documents, are extracted from the distribution network construction completed project data; the extracted document data is preprocessed, and the rule engine in the distribution network acceptance model is used to compare the preprocessed document data with predefined document integrity rules, including checking the existence of required documents, format correctness, and accuracy of information; document data that does not comply with the rules is identified and marked as abnormal project documents.

[0011] Furthermore, according to the classification algorithm of the distribution network acceptance model, the consistency of the equipment function data of the completed distribution network construction project is reviewed and verified, and the specific process of identifying abnormal equipment function data is as follows: extracting the equipment function data of the completed distribution network construction project from the data of the completed distribution network construction project, including the performance indicator data and test result data of the equipment; using the classification algorithm in the distribution network acceptance model, the preprocessed equipment function data is analyzed, the equipment function data is classified, and it is determined whether the equipment meets the set functional standards and performance requirements, the equipment function data that does not meet the functional standards is identified, and marked as abnormal equipment function data.

[0012] Furthermore, according to the rule engine of the distribution network acceptance model, the consistency of the distribution network construction quality and safety data is reviewed and verified, and the specific process of identifying abnormal construction quality and safety data is as follows: extracting the distribution network construction quality and safety data from the distribution network construction completion project data, including inspection report data, test result data, and safety audit record data; preprocessing the extracted construction quality and safety data, and using the rule engine in the distribution network acceptance model to compare the preprocessed distribution network construction quality and safety data with the set rules to check the consistency of the construction quality and safety data; identifying data that does not meet the quality and safety standards and marking them as abnormal construction quality and safety data.

[0013] Furthermore, the specific process of generating the review coefficient is as follows: integrating the received abnormal project documents, abnormal equipment function data, and construction quality and safety abnormality data into the abnormal data set and sending it to the project reviewer; obtaining the project abnormal review information, calculating the project abnormal review information through the rule engine in the distribution network acceptance model, and generating the review coefficient.

[0014] A distribution network construction completion acceptance management method comprises the following steps: S1. acquiring distribution network construction project acceptance demand data and distribution network construction completion project data, and performing preprocessing; S2. establishing an acceptance demand map based on the distribution network construction project acceptance demand data, defining acceptance rules and standards, constructing a rule engine, and constructing a distribution network acceptance model according to a classification model; S3. reviewing and verifying the integrity of distribution network construction completion project document data according to the rule engine of the distribution network acceptance model, identifying abnormal project documents for primary marking, and sending the abnormal project documents; S4. reviewing and verifying the consistency of distribution network construction completion project equipment function data according to the classification algorithm of the distribution network acceptance model, identifying abnormal project documents for primary marking, and sending the abnormal project documents for primary marking; S5. The normal equipment function data is marked at the first level, and the abnormal equipment function data is sent; S5. According to the rule engine of the distribution network acceptance model, the consistency of the distribution network construction quality and safety data is reviewed and verified, the abnormal construction quality and safety data are identified and marked at the first level, and the abnormal construction quality and safety data are sent; S6. Receive abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, mark it at the second level and send it; S7. Receive the abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data with the second level mark, generate an acceptance report and store it.

[0015] The present invention has the following beneficial effects:

[0016] (1) A distribution network construction completion acceptance management system obtains the acceptance demand data of distribution network construction projects, establishes an acceptance demand map, defines acceptance rules and standards, builds a rule engine, and builds a distribution network acceptance model based on a classification model, effectively transforming complex acceptance requirements and standards into executable models, thereby improving the automation and accuracy of the acceptance process. According to the rule engine and classification algorithm of the distribution network acceptance model, the integrity of the distribution network construction completion project document data, the consistency of the distribution network construction completion project equipment function data and the distribution network construction quality and safety data are reviewed and verified, and abnormal project documents are identified for primary marking to ensure the integrity and accuracy of the document data, the reliability of the equipment function, the compliance of the construction quality and safety standards, and the effectiveness of quality and safety acceptance.

[0017] (2) A distribution network construction completion acceptance management method generates a review coefficient. If the review coefficient exceeds a set threshold, it is marked as secondary and sent to the acceptance management module. It ensures that abnormal data is identified and processed in a timely manner, improves the reliability and accuracy of the acceptance process, receives secondary marked abnormal project documents, abnormal equipment function data, and construction quality and safety abnormal data, generates an acceptance report and stores it, improves the efficiency of information storage and retrieval, and supports subsequent review and improvement work.

[0018] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flow chart of a distribution network construction completion acceptance management system of the present invention.

[0020] Figure 2 The present invention is a flow chart of a distribution network construction completion acceptance management method. DETAILED DESCRIPTION

[0021] The embodiment of the present application solves the problems of non-standard acceptance process, difficult data traceability, inaccurate data, inconsistent data, and untimely data processing during the completion acceptance of distribution network construction through a distribution network construction completion acceptance management method and system, improves the efficiency and reliability of the acceptance process, reduces the subjectivity and error risks of manual operations, and realizes intelligent and automated management of acceptance data.

[0022] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0023] Obtain the distribution network construction project acceptance demand data and distribution network construction completion project data, and perform pre-processing.

[0024] Based on the acceptance demand data of distribution network construction projects, an acceptance demand map is established, acceptance rules and standards are defined, a rule engine is built, and a distribution network acceptance model is constructed based on the classification model.

[0025] According to the rule engine of the distribution network acceptance model, the integrity of the distribution network construction completion project document data is reviewed and verified, abnormal project documents are identified for primary marking, and the abnormal project documents are sent.

[0026] According to the classification algorithm of the distribution network acceptance model, the consistency of the equipment function data of the completed distribution network construction project is reviewed and verified, the abnormal equipment function data is identified and marked at the first level, and the abnormal equipment function data is sent.

[0027] According to the rule engine of the distribution network acceptance model, the consistency of the distribution network construction quality and safety data is reviewed and verified, the abnormal construction quality and safety data are identified and marked at the first level, and the abnormal construction quality and safety data are sent.

[0028] Receive abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, give it a secondary mark and send it.

[0029] Receive secondary marked abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data, generate acceptance reports and store them.

[0030] See also Figure 1The embodiment of the present invention provides a technical solution: a distribution network construction completion acceptance management system, comprising the following modules: a distribution network construction data acquisition module, a distribution network acceptance model construction module, an acceptance module, an abnormal marking module, and an acceptance management module; the distribution network construction data acquisition module is used to acquire the distribution network construction project acceptance demand data and the distribution network construction completion project data, and perform preprocessing; the distribution network acceptance model construction module is used to establish an acceptance demand map based on the distribution network construction project acceptance demand data, define acceptance rules and standards, build a rule engine, and build a distribution network acceptance model according to the classification model; the acceptance module includes an engineering document acceptance unit, an equipment function acceptance unit, and a quality and safety acceptance unit; the engineering document acceptance unit is used to review and verify the integrity of the distribution network construction completion project document data according to the rule engine of the distribution network acceptance model, identify abnormal project documents for primary marking, and send the abnormal project documents to the abnormal marking module; the equipment function The acceptance unit is used to review and verify the consistency of the equipment function data of the completed distribution network construction project according to the classification algorithm of the distribution network acceptance model, identify abnormal equipment function data for primary marking, and send the abnormal equipment function data to the abnormal marking module; the quality and safety acceptance unit is used to review and verify the consistency of the distribution network construction quality and safety data according to the rule engine of the distribution network acceptance model, identify the abnormal construction quality and safety data and perform primary marking, and send the abnormal construction quality and safety data to the abnormal marking module; the abnormal marking module is used to receive abnormal project documents, abnormal equipment function data and abnormal construction quality and safety data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, perform a secondary marking on it and send it to the acceptance management module; the acceptance management module is used to receive the abnormal project documents, abnormal equipment function data and abnormal construction quality and safety data with secondary marking, generate an acceptance report and store it.

[0031] In this implementation scheme, the distribution network construction data acquisition module is responsible for collecting relevant data from various sources, including project requirements and actual completion data. Preprocessing includes data cleaning and formatting to ensure data quality for subsequent processing. The acceptance requirement data represents the various requirements and standard data that the distribution network project needs to meet during completion acceptance. The distribution network acceptance model construction module helps define acceptance criteria and rules by converting the acceptance requirement data into a structured graph. The rule engine is used to convert these rules into a form that can be executed by the system. The classification model is used to classify and predict the data to help automatically determine whether the acceptance data meets the standards. The engineering document acceptance unit checks whether the project documents are complete and meet the requirements, identifies any missing or non-compliant documents, and marks exceptions. All marked documents will be sent to the exception marking module for further processing. The equipment function acceptance unit checks whether the equipment functions meet the project requirements and standards and identifies any equipment function abnormalities. The quality and safety acceptance unit reviews the quality and safety data during the construction process to ensure that it meets the acceptance standards and identifies any quality and safety abnormalities. The acceptance management module receives the secondary marked abnormal data, generates an acceptance report and stores it. Process all secondary marked abnormal data to generate a detailed acceptance report. These reports contain the analysis and handling results of all anomalies, and the final report is stored in the system for subsequent reference and review.

[0032] Specifically, the distribution network construction project acceptance requirement data includes the distribution network construction project document acceptance requirement data, the distribution network construction project equipment function acceptance requirement data, and the distribution network construction quality and safety acceptance requirement data; the distribution network construction completed project data includes the distribution network construction completed project document data, the distribution network construction completed project equipment function data, and the distribution network construction quality and safety data.

[0033] In this implementation plan, the distribution network construction project document acceptance demand data includes all documents and files that need to be submitted, which need to meet the specified standards and requirements, including design drawings, construction reports, test records, and certificates of conformity. The distribution network construction project equipment function acceptance demand data includes the technical requirements and standards of equipment functions, including rated power, operating stability, and response time, to ensure that the equipment can meet the design and operation requirements in actual operation. The distribution network construction quality and safety acceptance demand data includes the quality and safety standards that need to be followed during the construction process. Material standards, construction processes, engineering acceptance standards, as well as safe operating procedures and safety protection measures, the distribution network construction completion project document data represents the project documents actually submitted after construction and acceptance. The distribution network construction completion project equipment function data records the actual function and performance data of the equipment after completion, which is used to verify whether the equipment is configured and operated according to the design standards and requirements, including the actual performance indicators, working status and function test results of the equipment. The distribution network construction quality and safety data reflects the actual quality and safety data during the construction process. Including the quality inspection results of the materials actually used in the construction, the execution of the construction process and the safety records of the construction site, used to confirm whether the construction quality meets the predetermined standards and safety requirements.

[0034] Specifically, the specific process of establishing an acceptance requirement map, defining acceptance rules and standards, and building a rule engine is as follows: based on the acceptance requirement data of distribution network construction projects, text cleaning and word segmentation and annotation are performed, and through named entity recognition and relationship extraction of natural language processing, key entities including engineering documents, equipment functions and quality and safety are determined, and the relationship between nodes is defined, and an acceptance requirement map is established, and the identified entities and relationships are visualized to form a structured acceptance requirement map; professional knowledge in the field of distribution network engineering is collected and combined with the acceptance standard data and special requirements data in the acceptance requirement data of distribution network construction projects, specific acceptance rules are written, including project document integrity, construction quality standards, and qualified thresholds are set, and compiled into specification documents; the specification documents are converted into an engine executable format through the Drools rule engine platform.

[0035] In this implementation scheme, the text cleaning and word segmentation and annotation process based on the acceptance demand data of the distribution network construction project is as follows: Text cleaning: Process the noise and irrelevant information in the original data to ensure the accuracy and consistency of the data. For example, remove irrelevant symbols and incorrect spellings. Word segmentation and annotation: Decompose the text data into smaller units with semantic meaning and annotate these words for further analysis. For example, decompose "construction report" into two words "construction" and "report", and annotate their parts of speech. Named entity recognition and relationship extraction of natural language processing, named entity recognition: Automatically identify important entities in the text (such as engineering documents, equipment functions, quality and safety) and classify them. For example, identify "engineering documents" as an entity. Determine and extract the relationship between these entities, and display the identified entities and relationships in the form of a graph. The graph visualizes the data through nodes (representing entities) and edges (representing relationships), making the structure of the acceptance requirements clearer and easier to understand. Collect professional knowledge in the field of distribution network engineering, combine acceptance standard data and special requirements data, combine these professional knowledge with the standards and special requirements in the acceptance demand data, and form specific acceptance rules. Write acceptance rules: Project document integrity: define what information, format and integrity requirements the document should contain. Construction quality standards: clarify the quality requirements during the construction process, including material standards, construction technology, etc., and set qualified standard values ​​or ranges for each standard. Organize these rules into a standardized document format to guide subsequent acceptance operations. The sample table is as follows:

[0036]

[0037] The specification document is converted into an engine executable format through the Drools rule engine platform. The Drools rule engine represents an open source rule engine for managing and executing business rules. The acceptance rules and standards in the specification document are converted into rule files that can be executed by the Drools rule engine. This includes encoding the rules and standards in the document into the Drools rule format so that the rule engine can automatically apply these rules for acceptance.

[0038] Specifically, the specific process of constructing a distribution network acceptance model based on the classification model is as follows: the equipment function data of the completed distribution network construction project is loaded into the classification model, and the classification results of the classification model are passed as input data to the Drools rule engine to build the distribution network acceptance model.

[0039] In this implementation scheme, the equipment function data of the completed distribution network construction project is loaded into the classification model. The equipment function data generally includes information such as the performance indicators, operating status, and use environment of the equipment, which need to be processed by the classification model. The classification model is a machine learning model that is used to classify data into different categories or labels. The equipment function data can be classified as "normal", "abnormal" or "pending maintenance". In the classification model, the equipment function data of the completed distribution network construction project is processed and analyzed. The model learns to recognize different equipment states through training data and assigns new data points to appropriate categories. These classification results can help identify which equipment functions meet the standards and which equipment may have problems. The output of the classification model is the functional status classification label of the equipment, qualified or abnormal. The output of the classification model (i.e., the functional classification label of the equipment) is passed as input data to the Drools rule engine. The input data is processed according to the defined rules. The rule engine evaluates the functional status of the equipment through a set of predefined rules and generates corresponding decisions or operation suggestions based on the rules. Based on the processing results of the Drools rule engine, a distribution network acceptance model is constructed. This model combines the output of the classification model and the decision of the rule engine to form a complete acceptance system. The distribution network acceptance model will conduct a comprehensive acceptance of distribution network construction projects based on the equipment function classification and the evaluation results of the rule engine.

[0040] Specifically, according to the rule engine of the distribution network acceptance model, the integrity of the distribution network construction completed project document data is reviewed and verified, and the specific process of identifying abnormal project documents is as follows: the distribution network construction completed project document data, including design drawings, construction record documents, and test report documents, are extracted from the distribution network construction completed project data; the extracted document data is preprocessed, and the rule engine in the distribution network acceptance model is used to compare the preprocessed document data with the predefined document integrity rules, including checking the existence of required documents, format correctness, and accuracy of information; document data that does not comply with the rules is identified and marked as abnormal project documents.

[0041] In this implementation, the extracted document data is preprocessed. Preprocessing includes formatting, normalizing, and denoising the document content so that the data can reach a unified standard in the subsequent comparison process. The preprocessed document data is compared with the predefined document integrity rules. The rule matching formula is as follows: Compliance ; In the formula Indicates Rules for data The matching result, True means that the data complies with the rules, False means that the data does not comply with the rules, Compliance indicates the document integrity matching index, 1 means compliance, and 0 means non-compliance. The comparison process is as follows: Existence of required documents: Check whether all necessary documents exist. For example, whether key documents such as design drawings, construction records, and test reports are complete. Format correctness: Check whether the format of the document complies with regulations. For example, whether the title, paragraphs, and charts of the document are typeset as required. Information accuracy: Check whether the information in the document is correct. For example, whether the date in the construction record, the equipment model, and the parameters in the test report are consistent with the actual situation. During the comparison process, document data that does not comply with the rules is identified. These documents that do not comply with the rules are marked as abnormal project documents for further processing and review.

[0042] Specifically, according to the classification algorithm of the distribution network acceptance model, the consistency of the equipment function data of the completed distribution network construction project is reviewed and verified, and the specific process of identifying abnormal equipment function data is as follows: extract the equipment function data of the completed distribution network construction project from the data of the completed distribution network construction project, including the performance indicator data and test result data of the equipment; use the classification algorithm in the distribution network acceptance model to analyze the preprocessed equipment function data, classify the equipment function data, determine whether the equipment meets the set functional standards and performance requirements, identify the equipment function data that does not meet the functional standards, and mark it as abnormal equipment function data.

[0043] In this implementation scheme, the equipment function data is extracted from the distribution network construction completion project data, and the process of analyzing the pre-processed equipment function data using the classification algorithm in the distribution network acceptance model is as follows: The calculation process of the logistic regression analysis is as follows: ; In the formula, : The probability that the equipment functions in accordance with the standard, represents the regression coefficient, Represents the characteristic value of the equipment function data, and e represents the natural constant. The classification result is compared with the set functional standards and performance requirements to identify the equipment function data that does not meet the functional standards. These data that do not meet the standards are marked as abnormal equipment function data and sent to the abnormal marking module for further processing. The classification judgment formula is as follows: ; In the formula, Classification Result represents the classification coefficient, where 1 means compliance and 0 means noncompliance. : The probability that the equipment functions in accordance with the standard, Indicates the classification threshold.

[0044] Specifically, according to the rule engine of the distribution network acceptance model, the consistency of the distribution network construction quality and safety data is reviewed and verified, and the specific process of identifying abnormal construction quality and safety data is as follows: extract the distribution network construction quality and safety data from the distribution network construction completion project data, including inspection report data, test result data, and safety audit record data; pre-process the extracted construction quality and safety data, and use the rule engine in the distribution network acceptance model to compare the pre-processed distribution network construction quality and safety data with the set rules to check the consistency of the construction quality and safety data; identify data that does not meet the quality and safety standards and mark them as abnormal construction quality and safety data.

[0045] In this implementation scheme, data related to construction quality and safety are extracted from project data. These data include inspection reports, test results, and safety audit records. The extracted data is preprocessed. The preprocessing steps include data cleaning (removing outliers and noise) and data standardization. The preprocessed data is compared using the rule engine in the distribution network acceptance model. The rule engine performs consistency checks on the construction quality and safety data based on predefined quality and safety standards, compares the comparison results with the set standards, identifies data that does not meet the quality and safety standards, and marks them as abnormal construction quality and safety data.

[0046] Specifically, the specific process of generating the review coefficient is as follows: integrating the received abnormal project documents, abnormal equipment function data, and construction quality and safety abnormality data into the abnormal data set and sending it to the project reviewer; obtaining the project abnormal review information, and calculating the project abnormal review information through the rule engine in the distribution network acceptance model to generate the review coefficient.

[0047] In this implementation plan, all identified abnormal data are integrated into an abnormal data set and sent to the project reviewer for manual review. The project reviewer conducts a detailed review of each abnormal data and records its evaluation results. Each evaluation result includes severity and impact scope; the project reviewer's evaluation results are input into the rule engine. The formula for the review coefficient is as follows: Review coefficient formula: ; In the formula, represents the comprehensive review coefficient, Indicates the total number of abnormal data Indicates The severity score of the abnormal data. ; In the formula Indicates The severity score of the abnormal data, Represents the weight of the project document data, Indicates The severity of the abnormal project document data, Indicates the weight of the device function data, Indicates The severity of the abnormal device function data, represents the weight of construction quality and safety data, Indicates The severity of abnormal construction quality and safety data.

[0048] See also Figure 2 A distribution network construction completion acceptance management method includes the following steps: S1. Acquire the distribution network construction project acceptance demand data and the distribution network construction completion project data, and perform preprocessing; S2. Based on the distribution network construction project acceptance demand data, establish an acceptance demand map, define acceptance rules and standards, build a rule engine, and build a distribution network acceptance model according to the classification model; S3. According to the rule engine of the distribution network acceptance model, review and verify the integrity of the distribution network construction completion project document data, identify abnormal project documents for primary marking, and send the abnormal project documents; S4. According to the classification algorithm of the distribution network acceptance model, review and verify the consistency of the distribution network construction completion project equipment function data, identify abnormal The normal equipment function data is marked at the first level, and the abnormal equipment function data is sent; S5. According to the rule engine of the distribution network acceptance model, the consistency of the distribution network construction quality and safety data is reviewed and verified, the abnormal construction quality and safety data are identified and marked at the first level, and the abnormal construction quality and safety data are sent; S6. Receive abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, mark it at the second level and send it; S7. Receive the abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data with the second level mark, generate an acceptance report and store it.

[0049] In this embodiment, in the process of establishing the acceptance requirements map and acceptance model in step S2, the acceptance requirements map is to identify and extract the key entities and relationships in the acceptance requirements through natural language processing technology to form a structured map. Acceptance rules and standards are to formulate specific acceptance standards based on professional knowledge and demand data, such as the completeness of project documents, performance standards of equipment functions, and consistency of construction quality and safety. The classification model is based on machine learning or statistical methods to establish a model for classification and evaluation of data consistency.

[0050] In summary, this application has at least the following effects:

[0051] A distribution network construction completion acceptance management method and system obtains the acceptance demand data of distribution network construction projects, establishes an acceptance demand map, defines acceptance rules and standards, builds a rule engine, and builds a distribution network acceptance model based on a classification model, effectively converting complex acceptance requirements and standards into executable models, thereby improving the automation and accuracy of the acceptance process. The rule engine and classification algorithm of the distribution network acceptance model are used to review and verify the integrity of the distribution network construction completion project document data, the consistency of equipment function data and construction quality and safety data, identify and mark abnormal project documents, ensure the integrity, accuracy and reliability of the data, and improve the effectiveness of quality and safety acceptance. By generating a review coefficient, the system can timely identify and process abnormal data to ensure the reliability and accuracy of the acceptance process. After receiving and processing the abnormal project documents, abnormal equipment function data and abnormal construction quality and safety data marked by the secondary mark, the system generates an acceptance report and stores it, improves the efficiency of information storage and retrieval, and supports subsequent review and improvement work. The system significantly improves the automation, efficiency and accuracy of the acceptance process, reduces the subjectivity and error risk of manual operation, and realizes the intelligent management of acceptance data.

[0052] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0054] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0056] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0057] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A distribution network construction completion acceptance management system, characterized in that: It includes the following modules: distribution network construction data acquisition module, distribution network acceptance model construction module, acceptance module, abnormal marking module, and acceptance management module; The distribution network construction data acquisition module is used to acquire the distribution network construction project acceptance demand data and the distribution network construction completion project data, and perform pre-processing; The distribution network acceptance model construction module is used to establish an acceptance requirement map based on the distribution network construction project acceptance requirement data, define acceptance rules and standards, build a rule engine, and build a distribution network acceptance model according to the classification model; The acceptance module includes a project document acceptance unit, an equipment function acceptance unit, and a quality and safety acceptance unit; The engineering document acceptance unit is used to review and verify the integrity of the distribution network construction completion project document data according to the rule engine of the distribution network acceptance model, identify abnormal project documents for primary marking, and send the abnormal project documents to the abnormal marking module; The equipment function acceptance unit is used to review and verify the consistency of equipment function data of the completed distribution network construction project according to the classification algorithm of the distribution network acceptance model, identify abnormal equipment function data for primary marking, and send the abnormal equipment function data to the abnormal marking module; The quality and safety acceptance unit is used to review and verify the consistency of the construction quality and safety data of the distribution network according to the rule engine of the distribution network acceptance model, identify the abnormal construction quality and safety data and perform primary marking, and send the abnormal construction quality and safety data to the abnormal marking module; The abnormal marking module is used to receive abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds a set threshold, give it a secondary mark and send it to the acceptance management module; The acceptance management module is used to receive the abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data marked at the second level, generate an acceptance report and store it; The specific process of establishing an acceptance requirement map, defining acceptance rules and standards, and building a rule engine is as follows: Based on the acceptance demand data of distribution network construction projects, text cleaning and word segmentation and annotation are carried out. Through named entity recognition and relationship extraction of natural language processing, key entities including engineering documents, equipment functions and quality safety are determined, and the relationship between nodes is defined. The acceptance demand map is established, and the identified entities and relationships are visualized to form a structured acceptance demand map; professional knowledge in the field of distribution network engineering is collected and combined with the acceptance standard data and special requirements data in the acceptance demand data of distribution network construction projects, specific acceptance rules are written, including project document integrity, construction quality standards, and qualified thresholds are set, and compiled into specification documents; the specification documents are converted into an engine executable format through the Drools rule engine platform; The specific process of constructing the distribution network acceptance model based on the classification model is as follows: Load the equipment function data of the completed distribution network construction project into the classification model, pass the classification results of the classification model as input data to the Drools rule engine, and build the distribution network acceptance model; According to the rule engine of the distribution network acceptance model, the integrity of the distribution network construction project document data is reviewed and verified, and the specific process of identifying abnormal project documents is as follows: Extract the distribution network construction completion project document data from the distribution network construction completion project data, including design drawings, construction record documents, and test report documents; pre-process the extracted document data, and use the rule engine in the distribution network acceptance model to compare the pre-processed document data with the pre-defined document integrity rules, including checking the existence of required documents, format correctness, and information accuracy; identify document data that does not comply with the rules and mark them as abnormal project documents; According to the classification algorithm of the distribution network acceptance model, the specific process of reviewing and verifying the consistency of the equipment function data of the completed distribution network construction project and identifying abnormal equipment function data is as follows: Extract equipment function data of completed distribution network construction projects from the data of completed distribution network construction projects, including equipment performance indicator data and test result data; use the classification algorithm in the distribution network acceptance model to analyze the pre-processed equipment function data, classify the equipment function data, determine whether the equipment meets the set functional standards and performance requirements, identify equipment function data that does not meet the functional standards, and mark it as abnormal equipment function data; According to the rule engine of the distribution network acceptance model, the specific process of reviewing and verifying the consistency of the distribution network construction quality and safety data and identifying abnormal construction quality and safety data is as follows: Extract distribution network construction quality and safety data from the data of completed distribution network construction projects, including inspection report data, test result data, and safety audit record data; pre-process the extracted construction quality and safety data, and use the rule engine in the distribution network acceptance model to compare the pre-processed distribution network construction quality and safety data with the set rules to check the consistency of the construction quality and safety data; identify data that does not meet quality and safety standards and mark it as abnormal construction quality and safety data; The specific process of generating the review coefficient is as follows: The received abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data are integrated into the abnormal data set and sent to the project reviewer; the project abnormal review information is obtained, and the project abnormal review information is calculated through the rule engine in the distribution network acceptance model to generate the review coefficient.

2. A distribution network construction completion acceptance management system according to claim 1, characterized in that: The distribution network construction project acceptance demand data includes distribution network construction project document acceptance demand data, distribution network construction project equipment function acceptance demand data, distribution network construction quality and safety acceptance demand data; The distribution network construction completed project data includes distribution network construction completed project document data, distribution network construction completed project equipment function data, distribution network construction quality and safety data.

3. A distribution network construction completion acceptance management method, using a distribution network construction completion acceptance management system as described in any one of claims 1-2, characterized in that: The following steps are involved: S1. Obtain the distribution network construction project acceptance demand data and the distribution network construction completion project data, and perform pre-processing; S2. Based on the acceptance demand data of distribution network construction projects, establish an acceptance demand map, define acceptance rules and standards, build a rule engine, and build a distribution network acceptance model based on the classification model; S3. According to the rule engine of the distribution network acceptance model, review and verify the integrity of the distribution network construction completion project document data, identify abnormal project documents for primary marking, and send the abnormal project documents; S4. Review and verify the consistency of the equipment function data of the completed distribution network construction project according to the classification algorithm of the distribution network acceptance model, identify abnormal equipment function data for primary marking, and send the abnormal equipment function data; S5. According to the rule engine of the distribution network acceptance model, review and verify the consistency of the distribution network construction quality and safety data, identify and mark the abnormal construction quality and safety data, and send the abnormal construction quality and safety data; S6. Receive abnormal project documents, abnormal equipment function data, and abnormal construction quality and safety data, and send them to the project reviewer for review, generate a review coefficient, and if the review coefficient exceeds the set threshold, mark it as a secondary mark and send it; S7. Receive secondary marked abnormal project documents, abnormal equipment function data and construction quality and safety abnormal data, generate an acceptance report and store it.

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