Anti-counterfeiting robot process automation method and system and computer readable storage medium
By applying robot process automation technology in the nuclear power field, automated processing and verification of electronic documents, the problem of illegal fraud in the nuclear power field has been solved, verification efficiency and accuracy have been improved, human-caused risks have been reduced, and the quality and safety of nuclear power construction have been ensured.
Patent Information
- Application Number
- CN202510199635.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-21
- Publication Date
- 2025-06-17
AI Technical Summary
There are illegal fraud in the field of nuclear power, which affects the quality and safe operation of nuclear power construction. Especially in terms of material quality certificates, factory records and personnel qualifications, manual verification tasks are heavy and there are human-caused risks.
Robot process automation technology is used to obtain the electronic documents to be tested, judge their type, extract the authentication number or specific fields, upload them to the corresponding website or perform preset standard data analysis, obtain verification results, and realize automated document verification and anti-falsification process.
It effectively solves the problem of preventing falsification of electronic documents, improves the accuracy and efficiency of document verification, reduces the time and workload of manual operations, reduces human errors, promptly discovers and prevents the circulation of forged documents, and ensures the quality and safe operation of nuclear power construction.
Smart Images
Figure CN120162473A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automation technology, and particularly to a method, system, and computer-readable storage medium for anti-counterfeiting robot process automation. Background Art
[0002] The full name of RPA is "Robotic Process Automation". Through specific "robot software", it simulates human operations on a computer and automatically executes process tasks according to rules, with advantages such as universality, precise control, and rapid application. In recent years, the problem of illegal counterfeiting in the nuclear power field has brought huge challenges to the quality of nuclear power construction and safe operation, affecting the healthy development of the nuclear power industry. Counterfeiting mainly focuses on material quality certification documents, in-plant record reports, personnel qualifications, etc. The number of relevant quality documents is huge, the manual verification task is heavy, and there are human factor risks. Therefore, it is urgent to adopt technical prevention measures for the digital transformation of anti-counterfeiting work. Summary of the Invention
[0003] This application provides a method, system, and computer-readable storage medium for anti-counterfeiting robot process automation to solve the problem of illegal counterfeiting in the nuclear power field.
[0004] The technical solution adopted by this application to solve its technical problems is: providing a method for anti-counterfeiting robot process automation, the method includes the following steps:
[0005] Step S1: Obtain the electronic document to be tested;
[0006] Step S2: Determine whether the electronic document to be tested is of the certification report type;
[0007] Step S3: If it is the certification type document, extract the certification number of the electronic document to be tested as the key identification information, and upload the key identification information to the corresponding website query page for query to obtain and output the first verification result;
[0008] Step S4: If it is not the certification report type, extract the specific field of the electronic document to be tested as the information to be verified, obtain the preset standard data, and perform analysis and processing on the information to be verified and the preset standard data to obtain and output the second verification result.
[0009] In an embodiment, before extracting the electronic document, it includes:
[0010] Determine whether the electronic document to be tested is in picture format;
[0011] If it is not in picture type, convert the electronic document to be tested into a picture format electronic document.
[0012] In one embodiment, after extracting the specific fields of the electronic document to be tested as the information to be verified, the following steps are included:
[0013] Determine whether the information to be verified meets the preset abnormal conditions;
[0014] If it meets the preset abnormal conditions, mark the electronic document to be tested as an abnormal document and perform abnormal processing on the abnormal document.
[0015] In one embodiment, the electronic document to be tested includes an authentication number and basic information;
[0016] After uploading the key identification information to the corresponding website query page for query, the following steps are included:
[0017] Create a new result display document;
[0018] Input the basic information and the result information returned by the query into the result display document for integrated display to obtain the first verification result.
[0019] In one embodiment, the analysis and processing of the information to be verified and the preset standard data includes:
[0020] Mark the abnormal data that appears in the information data to be verified and the preset standard data to obtain the second verification result.
[0021] In one embodiment, the method further includes:
[0022] Send the first verification result or the second verification result to the corresponding email address by email.
[0023] In one embodiment, the extraction of the authentication number of the electronic document to be tested as the key identification information includes:
[0024] Based on the character recognition technology, recognize and extract the authentication number in the electronic document to be tested as the key identification information;
[0025] The extraction of the specific fields of the electronic document to be tested as the information to be verified includes:
[0026] Based on the character recognition technology, recognize and extract the specific fields of the electronic document to be tested as the information to be verified.
[0027] In one embodiment, the electronic document to be tested includes one of a detection authentication report, an investigation authentication report, and a personnel qualification report.
[0028] The present application also provides a system for the automation of the anti-counterfeiting robot process, including a memory, a processor, and a computer program stored on the memory. The processor executes the computer program to implement the steps of the method described in any one of the above.
[0029] The present application also provides a computer-readable storage medium, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of the method described in any one of the above are implemented.
[0030] Implementing the present application has the following beneficial effects: The present application provides a method, a system, and a computer-readable storage medium for the automation of the anti-counterfeiting robot process. The steps of the method for the automation of the anti-counterfeiting robot process include: obtaining an electronic document to be tested; determining whether the electronic document to be tested is of the type of authentication report; if it is an authentication type document, extracting the authentication number of the electronic document to be tested as the key identification information, and uploading the key identification information to the query page of the corresponding website for querying to obtain and output a first verification result; if it is not of the type of authentication report, extracting the specific field of the electronic document to be tested as the information to be verified, obtaining preset standard data, and performing analysis and processing on the information to be verified and the preset standard data to obtain and output a second verification result. By using the robot process automation technology and combining the authentication report query website and the preset standard data, the present application effectively solves the problem of anti-counterfeiting of electronic documents and improves the accuracy and efficiency of electronic document verification. Description of the Drawings
[0031] The following will further illustrate the present application in conjunction with the drawings. In the drawings:
[0032] Figure 1 is a flow schematic diagram of the method for the automation of the anti-counterfeiting robot process of the present application;
[0033] Figure 2 is a flow schematic diagram of the anti-counterfeiting verification process of the third-party test report of the present application;
[0034] Figure 3 is a flow schematic diagram of the anti-counterfeiting verification process of the debugging report of the present application;
[0035] Figure 4 is a flow schematic diagram of the anti-counterfeiting verification process of the special personnel qualification of the present application. Detailed Embodiments
[0036] The present application will be further described in detail below in conjunction with specific embodiments and the accompanying drawings. Similar elements in different embodiments are denoted by related similar element numbers. In the following embodiments, many detailed descriptions are provided to enable a better understanding of the present application. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.
[0037] As Figure 1 shown, Figure 1 it is a schematic flowchart of the method for anti-counterfeiting robot process automation of the present application.
[0038] Step S1: Obtain the electronic document to be tested;
[0039] In this step, it should be noted that the electronic document to be tested is obtained from a specified folder, network shared location, or a file uploaded by the user. These documents can be various file formats, such as PDF, Word, Excel, etc. The document is loaded into the system through a file reading module for subsequent processing.
[0040] Step S2: Determine whether the electronic document to be tested is of the certification report type;
[0041] In this step, it should be noted that it is determined whether the electronic document to be tested is of the certification report type by the file name, file extension, or specific identifier in the file content. For example, a certification report usually has a specific file name format or contains specific keywords, such as "certification report", "certificate", etc. If the document is determined to be of the certification report type, go to step S3; otherwise, go to step S4.
[0042] Step S3: If it is a certification type document, extract the certification number of the electronic document to be tested as the key identification information, and upload the key identification information to the corresponding website query page for query to obtain and output the first verification result;
[0043] In this step, it should be noted that for the certification report type document, the certification number in the document is extracted as the key identification information. The certification number is usually located in specific positions of the document, such as the title, header, or footer. The certification number is accurately extracted through the text recognition module and then uploaded to the corresponding website query page for query. The query results include the validity of the certification number, the validity of the key, the information of the certification agency, the certification date, etc. After obtaining the query results, they are output as the first verification result for further analysis and processing by the user or system.
[0044] Step S4: If it is not a certification report type, extract specific fields of the electronic document to be tested as the information to be verified, obtain the preset standard data, and perform analysis and processing on the information to be verified and the preset standard data to obtain and output the second verification result.
[0045] In this step, it should be noted that for non-certification report type documents, specific fields in the document are extracted as the information to be verified. These specific fields can be key data in the document, such as product model, production date, batch number, etc. These fields are extracted through the text recognition module, and then the preset standard data is obtained. The standard data can be from a database, an Excel table, or predefined rules. The extracted information to be verified is analyzed and processed with the preset standard data, and the authenticity of the document is determined by methods such as comparison and matching. The analysis result is output as the second verification result for further analysis and processing by the user or system.
[0046] The anti-counterfeiting robot process automation method of this application effectively solves the problem of illegal counterfeiting in the nuclear power field through an automated and intelligent document processing and verification process. This method significantly improves the efficiency and accuracy of document verification, reduces the time and workload of manual operations, and reduces human errors. Through the automated verification process, it can timely detect and prevent the circulation of forged documents, effectively prevent counterfeiting behaviors, and ensure the quality and safe operation of nuclear power construction. In addition, this method has good flexibility and scalability, can be flexibly configured and extended according to different document types and verification requirements, and adapts to various complex anti-counterfeiting scenarios. It can also monitor the verification process of the document in real time and timely feedback the verification results to provide timely and accurate information support for the user or system. In summary, the anti-counterfeiting robot process automation method of this application realizes the digital transformation of anti-counterfeiting work, improves the efficiency and accuracy of document verification, reduces human factor risks, effectively prevents counterfeiting behaviors, and ensures the quality and safe operation of nuclear power construction.
[0047] Further, before extracting the electronic document, it includes:
[0048] Judge whether the electronic document to be tested is in picture format;
[0049] If it is not a picture type, convert the electronic document to be tested into an electronic document to be tested in picture format.
[0050] It should be noted that before extracting the electronic document, first determine whether the electronic document to be tested is in picture format. If the document is not in picture format, convert the electronic document to be tested into an electronic document to be tested in picture format. The conversion process can use optical character recognition (OCR) technology to convert the non-picture format document into a picture format to ensure the consistency and accuracy of subsequent processing.
[0051] Furthermore, after extracting the specific fields of the electronic document to be tested as the information to be verified, it includes:
[0052] Judge whether the information to be verified meets the preset abnormal conditions;
[0053] If it meets the preset abnormal conditions, mark the electronic document to be tested as an abnormal document and perform abnormal processing on the abnormal document.
[0054] It should be noted that after completing the above verification steps, further judge whether the information to be verified meets the preset abnormal conditions. The preset abnormal conditions can include but are not limited to: invalid authentication number, non-existent certification agency, expiration of the certification date, mismatch between key data and standard data, etc. If the information to be verified meets any one of the preset abnormal conditions, abnormal processing will be performed. Abnormal processing includes marking the abnormal part and giving corresponding abnormal prompts so that users can quickly identify and understand the problem.
[0055] Furthermore, the electronic document to be tested includes an authentication number and basic information;
[0056] After uploading the key identification information to the corresponding website query page for query, it includes:
[0057] Create a new result display document;
[0058] Input the basic information and the result information returned by the query into the result display document for integrated display to obtain the first verification result.
[0059] It should be noted that after uploading the key identification information (authentication number) to the corresponding website query page for query, create a new result display document. Input the basic information (such as product model, production date, batch number, etc.) and the result information returned by the query (such as the validity of the authentication number, information of the certification agency, certification date, etc.) into the result display document for integrated display to obtain the first verification result. The result display document can be a PDF, Word or other format file, which is convenient for users to view and archive.
[0060] Furthermore, the analysis and processing of the information to be verified and the preset standard data includes:
[0061] Annotate the abnormal data that appears in the information data to be verified and the preset standard data to obtain the second verification result.
[0062] It should be noted that first, data comparison is performed. The information to be verified is compared item by item with the preset standard data to check for differences. If differences are found, abnormal data is annotated. For example, abnormal situations such as product model mismatch, production date exceeding the expiration date, and batch number not existing will have these abnormal data annotated. Finally, based on the annotated abnormal data, a second verification result is generated, which includes the authenticity judgment of the information to be verified, the specific information of the abnormal data, etc.
[0063] Furthermore, the method further includes:
[0064] Send the first verification result or the second verification result to the corresponding email address by email.
[0065] It should be noted that the first verification result or the second verification result is sent to the corresponding email address by email. According to the preset email template, the verification result is organized into the email content, including the detailed information of the verification result, the annotation of the abnormal data, etc. The email sending function ensures that the verification result can be conveyed to relevant personnel or systems in a timely and accurate manner, facilitating subsequent processing and decision-making.
[0066] Furthermore, extracting the authentication number of the electronic document to be tested as the key identification information includes:
[0067] Based on the text recognition technology, identify and extract the authentication number in the electronic document to be tested as the key identification information;
[0068] Extracting the specific field of the electronic document to be tested as the information to be verified includes:
[0069] Based on the text recognition technology, identify and extract the specific field of the electronic document to be tested as the information to be verified.
[0070] It should be noted that for the authentication report type document, based on the text recognition technology, identify and extract the authentication number in the electronic document to be tested as the key identification information. The authentication number is usually located in a specific position of the document, such as the title, header, or footer. The authentication number is accurately extracted through the text recognition module and then uploaded to the corresponding website query page for query. The query results include the validity of the authentication number, the information of the certification institution, the certification date, etc. After obtaining the query results, they are output as the first verification result for further analysis and processing by users or systems.
[0071] Furthermore, the electronic document to be tested includes one of a test authentication report, an investigation authentication report, and a personnel qualification report.
[0072] As Figure 2 shownFigure 2 Schematic diagram of the anti-counterfeiting verification process for third-party inspection reports
[0073] The first step: Generate the front page picture of the report. The second step: Detect the file encoding recognition. The third step: Download the inspection report.
[0074] Specifically, first, use robotic process automation technology to automatically capture the front page of the inspection report, and ensure the accuracy and integrity of the screenshot according to the preset screenshot area and parameters to generate a clear front page picture. Subsequently, process the screenshot, such as resizing and format conversion, to ensure the compatibility of the picture with subsequent processing tools. Then, use optical character recognition (OCR) technology to extract the encoding information of the inspection document from the processed front page picture, and accurately extract the document encoding through the preset recognition area and character recognition algorithm to provide key information for subsequent operations. After that, compare the extracted encoding with the preset rules for verification. If the encoding does not conform to the rules, mark it as an abnormal document and process it. If it conforms, continue. Finally, according to the verified document encoding, download the inspection report through automation technology on the official website of the third-party inspection agency, and ensure the complete download of the report using the preset download path and parameters. After downloading, save the report according to the preset file naming rule and storage path, for example, store it in a specified folder with the file encoding as the file name for subsequent query and processing.
[0075] As Figure 3 shown Figure 3 Schematic diagram of the anti-counterfeiting verification process for debugging reports
[0076] When conducting the anti-counterfeiting verification of the debugging report, first put the electronic debugging report, the personnel access records exported from the access control system, and the measurement instrument ledger into the specified folder, and start the "RPA anti-counterfeiting robot". The robot quickly scans the debugging report, extracts the signatures of the TS (Technical Supervisor) personnel, the time, and the measurement instrument information, and imports this information into a newly created EXCEL table. Subsequently, the robot automatically compares the information extracted from the report with the personnel access records and the measurement instrument ledger, and outputs a comparison result EXCEL table. If any abnormalities are found, such as no access records for the personnel within the corresponding time or the extracted measurement instrument information being inconsistent with the ledger, the robot will mark the abnormality in the output comparison result to achieve rapid verification.
[0077] Specifically, first convert the PDF file into a picture format, and determine whether there are any abnormalities during the conversion process. If the instrument data, access record data, and authorization data in the picture are not recognized, it indicates that there is an abnormality in the PDF conversion and recognition, and abnormal handling is required. Next, identify the data in the picture content. If there are any abnormalities in the recognition result, abnormal handling is also required. Subsequently, check the instrument data, and compare the information such as the instrument number, calibration time, and calibration result recognized from the PDF-to-picture conversion with the data in the instrument ledger to determine whether there are any abnormalities. Next, compare the access record data. Extract the signature and date of the debugging person in charge from a fixed position in the PDF and compare them with the data in the personnel access record ledger. If there is no access record corresponding to the signature period, it can be determined that there is fraud. Then, process the authorization data, and compare the system code and the name of the debugging person in charge recognized from the PDF-to-picture conversion with the authorization ledger list. If the person in charge does not have the relevant system debugging authorization, it is determined as fraud. Finally, send the verification result to the relevant personnel or departments via email.
[0078] As Figure 4 shown, Figure 4 it is a schematic diagram of the anti-fraud verification process for special personnel qualifications.
[0079] Specifically, in the anti-fraud verification process for special personnel qualifications, first use robotic process automation technology to achieve automated extraction, accurately capture the key information of personnel from the special personnel ledger, such as name, ID number, and job type, etc.; then perform automated matching and access. The robot, relying on the pre-set corresponding table of job type and qualification query website, opens the corresponding official website according to the job type information of the special personnel and enters the qualification query page to ensure the correctness of the verification path and provide an accurate platform for subsequent queries; finally, it is automated filling and submission. On the opened query page, the robot uses automated interaction technology that simulates manual operations to accurately fill in the personnel information such as name and ID number into the specified query input box and automatically triggers the query operation. With accurate information matching and automated operation processes, it ensures the accuracy of information filling and timely obtains the query result. Throughout the process, the robot realizes the efficiency and accuracy of the verification process through accurate data capture and flexible page operations.
[0080] Implementing the method of the anti-fraud robotic process automation of the present invention, by using digital means to replace manual work and carrying out anti-fraud management work in various fields such as reports, personnel qualifications, and tools and equipment, not only reduces human errors, but also can improve efficiency and save a large amount of labor costs for the company.
[0081] This application also provides a system for anti-fraud robotic process automation, including a memory, a processor, and a computer program stored on the memory. The processor executes the computer program to implement the steps of any of the above methods.
[0082] The present application also provides a computer-readable storage medium, on which computer programs / instructions are stored. When the computer programs / instructions are executed by a processor, the steps of any of the above methods are implemented.
[0083] It should be understood that the above embodiments only represent the preferred embodiments of the present invention, and the description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, by freely combining the above technical features and making several deformations and improvements, these all belong to the protection scope of the present invention. Therefore, all equivalent transformations and modifications made to the scope of the claims of the present invention shall fall within the scope covered by the claims of the present invention.
Claims
1. A method for automating a process of anti-counterfeiting robots, characterized in that: include: Step S1: Obtain the electronic document to be tested; Step S2: Determine whether the electronic document to be tested is a certification report type; Step S3: If it is the certification type document, extract the certification number of the electronic document to be tested as key identification information, and upload the key identification information to the corresponding website query page for query, so as to obtain and output the first verification result; Step S4: If it is not the authentication report type, extract the specific field of the electronic document to be tested as the information to be verified, obtain the preset standard data, analyze and process the information to be verified and the preset standard data to obtain and output a second verification result.
2. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: Before extracting electronic documents include: Determine whether the electronic document to be tested is in a picture format; If it is not a picture type, the electronic document to be tested is converted into an electronic document to be tested in a picture format.
3. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: The step of extracting the specific field of the electronic document to be tested as the information to be verified includes: Determining whether the information to be verified meets a preset abnormal condition; If the preset abnormal condition is met, the electronic document to be tested is marked as an abnormal document, and an abnormal process is performed on the abnormal document.
4. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: The electronic document to be tested includes a certification number and basic information; The step of uploading the key identification information to the corresponding website query page for querying includes: Create a new result presentation document; The basic information and the result information returned by the query are input into the result display document for integrated display to obtain the first verification result.
5. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: The analyzing and processing the information to be verified and the preset standard data includes: Abnormal data between the information data to be verified and the preset standard data are marked to obtain the second verification result.
6. The method for automating the process of anti-counterfeiting robots according to claim 5, characterized in that: The method further comprises: Send the first verification result or the second verification result to the corresponding mailbox via email.
7. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: The step of extracting the authentication number of the electronic document to be tested as key identification information includes: Based on the text recognition technology, identifying and extracting the authentication number in the electronic document to be tested as the key identification information; The extracting the specific field of the electronic document to be tested as the information to be verified includes: Based on the text recognition technology, the specific field of the electronic document to be tested is identified and extracted as the information to be verified.
8. The method for automating the process of anti-counterfeiting robots according to claim 1, characterized in that: The electronic document to be tested includes one of a test certification report, an investigation certification report and a personnel qualification report.
9. A system for automating a process of anti-counterfeiting robotics, comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.
10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.