A method and system for automatically identifying special equipment inspection reports

Abstract

The invention relates to the technical field of detection report identification, and discloses an automatic identification method and system for special equipment detection reports. The method comprises the following steps: a user calls a special equipment detection report, identifies special equipment report information, calls special equipment inspection criteria, performs duplicate information cleaning and interference information identification and filtering on the special equipment report information, preliminarily screens the content of the special equipment report information, screens a sequence of inspection items in the special equipment report information sorted by weight by calculating the weight of the inspection items in the special equipment report information, analyzes and evaluates the screened inspection item sequence by evaluating the special equipment report information, feeds back the analysis result of the special equipment report information to a special equipment report information evaluation storage module, and updates the generated special equipment information evaluation report. The invention realizes intelligent analysis and evaluation of special equipment detection reports, and greatly reduces the cost and subjectivity of manual review.

Description

Technical Field

[0001] The invention relates to the technical field of detection report recognition, and discloses an automatic recognition method and system for a special equipment detection report. Background Art

[0002] The special equipment reporting information evaluation system plays a significant role in improving the level and efficiency of equipment safety management, but it still needs to be continuously improved and perfected in terms of cost control, unified technical standards, human resource training, safety assurance and ease of operation. The construction and maintenance costs of the special equipment reporting information evaluation system are high. Special equipment produced by different equipment manufacturers use different monitoring and reporting systems, resulting in inconsistent technical standards and poor data compatibility. This difference affects the integration of the system and the efficiency of data exchange. The operation and management of the system still requires support and maintenance from professional technicians, including data analysts, system engineers and equipment maintenance personnel. This has caused the problem of insufficient human resource allocation for some enterprises. Although the system is designed to monitor and warn of equipment problems, in some cases, the system's own failures or data transmission delays affect the timeliness of fault diagnosis and response speed.

[0003] For example, the existing patent with publication number CN106971273A discloses a control system and control method for the acceptance workflow of a substation with intelligent alarm prompts, including an intelligent alarm, a rule judgment module, a process flow module, a main controller, a timer, a memory, a data processing module and an automatic assessment module; the acceptance work of the substation is divided into the acceptance application of the substation, the import of point table information and protection configuration table, the preprocessing of the information point table and the review of the acceptance application, the drawing of the main station model and the system configuration of the main and substations, the import of the monitoring information table, the acceptance of the substation, the acceptance of the main station, the review of the acceptance report, the sampling of the acceptance results, and the formation of the final acceptance report and evaluation report. The invention avoids the omission of information during the acceptance process, coordinates the work of various departments, avoids errors in the handover process of departments, improves work efficiency, and ensures the accuracy and efficiency of the acceptance work of the substation; the standardized acceptance model improves the accuracy of the acceptance of power equipment and ensures the safe and stable operation of the power grid.

[0004] The above patent manages the report and the result reports of other indicators of the substation through mechanical manual operations. Although it coordinates the work of various departments, it does not reflect the intelligent analysis and evaluation of the results. At the same time, the report generation process and the report review process are mostly operated manually, which greatly increases the subjectivity of the evaluation and greatly reduces the objectivity of the results. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and system for automatically identifying special equipment inspection reports.

[0006] The present invention discloses a method for automatically identifying a special equipment test report, comprising:

[0007] S1. The user calls the special equipment inspection report and identifies the special equipment report information;

[0008] S2. Call the special equipment inspection criteria to clean duplicate information and identify and filter interference information in special equipment report information;

[0009] S3. Conduct preliminary screening of special equipment report information content, conduct report quality inspection and audit status verification;

[0010] S4. Filter the inspection item sequence in the special equipment report information sorted by weight by calculating the inspection item weight of the special equipment report information;

[0011] S5. Analyze and evaluate the selected inspection item sequence through the special equipment report information assessment;

[0012] S6. Feedback the analysis results of the special equipment report information to the special equipment report information evaluation storage module;

[0013] S7. Update the generated special equipment information evaluation report based on feedback and evaluation results.

[0014] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0015] The duplicate information cleaning includes text similarity analysis and duplicate record representation;

[0016] The interference information identification and filtering includes stop word filtering and keyword extraction;

[0017] Special equipment inspection criteria are used to screen and clean special equipment report information.

[0018] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0019] The report quality check includes completeness check and format structure check;

[0020] The audit status verification includes audit field checking and audit process tracking;

[0021] Conduct preliminary screening of special equipment report information content through data analysis models;

[0022] The data analysis model calculates the quality similarity of the data points in the special equipment report information inspection items. If the data point quality similarity is greater than a preset threshold, it is a correct item, and the correct item is used as the basic data for calculating the weight of the special equipment report information inspection item. If the data point quality similarity is less than the preset threshold, it is a data point with low report quality, missing data, and abnormal audit status verification, and the corresponding inspection items are removed. The data analysis model is pruned and optimized through the inspection model;

[0023] The quality similarity is used to describe the accuracy of the inspection items in the special equipment report information.

[0024] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0025] The data analysis model calculation expression is as follows:

[0026] ;

[0027] in, is the quality similarity between the data points x in the test item C, is the circumference constant, is a data point in the inspection item C of the special equipment report information, C is the inspection item of the special equipment, C is the inspection item sequence number, which is 1, 2, 3, ..., n, n is the total number of inspection items, and n is a positive integer; is the mean of all data points of test item C, is the covariance matrix of all data points of test item C, is the expected degree that the data point x belongs to the test item C;

[0028] The test model optimizes the data analysis model by calculating the error similarity of the mixed data in the data analysis model and fitting it as a difference coefficient. The calculation expression of the test model is as follows:

[0029] ;

[0030] Among them, Q is the error similarity of mixed data in the data analysis model, is the quality similarity between the data points in the kth inspection item in the special equipment report information output by the data analysis model, is the density similarity of the data points in the input test item k, where k is an ordinal number ranging from 1, 2, 3, ..., n;

[0031] The inspection model adds optimization coefficients to the data analysis model through the optimization port, automatically corrects the analysis errors of the data analysis model on the inspection items and makes corrections.

[0032] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0033] The inspection item data of the special equipment report information is output through the inspection item monitoring function. The expression of the inspection item monitoring function is as follows:

[0034] ;

[0035] in, is the weight of the i-th inspection item in the special equipment report information, To input the data corresponding to the i-th inspection item of the special equipment report information, is the deviation constant value, H is the inspection item data of the special equipment monitoring report information;

[0036] By calculating the weight difference between the i-th and i+1-th inspection items in the special equipment report information, the inspection item with the largest inspection item weight in the special equipment report information is screened out;

[0037] The calculation expression for filtering out the inspection item with the largest inspection item weight in the special equipment report information is as follows:

[0038] ;

[0039] in, is the weight of the i+1th inspection item in the special equipment report information, is the weight screening coefficient, Report inspection item data for special equipment information, Mathematical symbols for deviation.

[0040] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0041] After screening out the inspection item with the largest inspection item weight in the special equipment report information, the method further includes:

[0042] Eliminate the inspection item with the largest inspection item weight from the inspection items of the special equipment report information, and obtain the inspection item with the largest inspection item weight in the inspection items of the special equipment report information again, until all inspection items are sorted according to the weight;

[0043] Obtain the test results of the test items in the screened test item sequence, evaluate the test results through the error function and output the error term, if the error term is greater than the preset error threshold, the test result of the test item is unqualified, and the unqualified test item is scored by the error value, if the error term is less than the preset error threshold, the test result of the test item is qualified, and the qualified test item is scored by the error value;

[0044] The error function calculation expression is as follows:

[0045] ;

[0046] in, Output the error term for the error function, The test result of the i-th test item of the special equipment report information, The theoretical value of the i-th test item in the special equipment report information.

[0047] As a preferred solution of the automatic recognition system of a special equipment test report of the present invention, wherein:

[0048] Feedback the analysis results of special equipment report information to the special equipment report information evaluation storage module, including data format conversion, data transmission and reception, data verification and quality control, storage and archiving of the analysis results;

[0049] The data format conversion includes ensuring that the analysis results are output in a format acceptable to the special equipment report information evaluation storage module;

[0050] The data transmission and reception includes establishing a stable and secure data transmission channel;

[0051] The data verification and quality control includes performing data verification and quality control before transmitting the analysis results to the special equipment report information evaluation storage module;

[0052] The storage and archiving include storing the analysis results in a special equipment report information evaluation storage module.

[0053] As a preferred solution of the method for automatically identifying a special equipment test report of the present invention, wherein:

[0054] The updating of the generated special equipment information assessment report includes data integration and updating, report structure adjustment, quality review and verification, notification and communication, and regular updating and maintenance;

[0055] The data integration and update includes integrating new feedback and evaluation results with existing special equipment information evaluation reports;

[0056] The report structure adjustment adjusts the structure and format of the special equipment inspection report through new feedback and evaluation results;

[0057] The quality review and verification mentioned above includes quality review of special equipment inspection reports;

[0058] The notification and communication include notification of updates and changes to the special equipment information evaluation report.

[0059] The present invention also discloses an automatic recognition system for special equipment test reports, comprising:

[0060] Collection module, used to collect and integrate special equipment report information;

[0061] A storage module, used for storing the integrated special equipment report information and the special equipment report information evaluation results;

[0062] The processing module includes a preliminary processing unit for retrieving special equipment inspection criteria and preliminarily processing special equipment report information, a screening unit for reviewing special equipment report information, and a weight marking unit for marking and stratifying inspection items in the special equipment report information;

[0063] The report analysis module includes a calculation unit for calculating the weight of the inspection item in the special equipment report information, and an analysis unit for receiving the weight of the inspection item in the special equipment report information and analyzing the inspection result of the inspection item;

[0064] Report evaluation module, used to evaluate and assess special equipment report information;

[0065] A feedback module, comprising a feedback data unit for feeding back the evaluation result of the special equipment report information to the storage module, and a feedback user unit for feeding back the evaluation result of the special equipment report information to the user end;

[0066] The report updating module includes a printing unit for generating a special equipment information evaluation report and an updating unit for updating the special equipment information evaluation report according to the evaluation result of the special equipment report information.

[0067] Beneficial effects of the present invention:

[0068] The present invention combines the category of special equipment and the evaluation criteria for the category, greatly improving the accuracy of special equipment inspection and the objectivity of special equipment inspection report evaluation; establishing a report evaluation module to ensure the authenticity and referenceability of the report, and giving reasonable suggestions to ensure that the design, installation, maintenance, inspection and other aspects of the equipment meet safety standards; establishing a feedback module and a report update module to update the database, test criteria and evaluation criteria in real time to ensure that the analysis algorithm and criteria remain consistent. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0070] Figure 1A method flow chart of an automatic identification method of a special equipment test report of the present invention;

[0071] Figure 2 The present invention is a system composition diagram of an automatic recognition system for special equipment inspection reports. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Embodiment 1

[0076] The contents of special equipment inspection include but are not limited to installation supervision inspection, regular inspection, and safety performance inspection.

[0077] Installation supervision inspection is mainly a one-time formal test for pressure piping components, large amusement facilities, lifting machinery, elevators, passenger ropeways, on-site motor vehicles, bursting discs and bursting disc devices, etc., aiming to verify whether the safety performance of new products and their key components meets the basic safety technical requirements.

[0078] Regular inspections cover the regular inspections and supervisory inspections of boilers, pressure vessels, pressure pipes, elevators (excluding explosion-proof types), lifting machinery, and on-site special motor vehicles (excluding explosion-proof types). Specifically, they include appearance inspections of boilers, condition inspections of safety accessories, and insulation and anti-corrosion layer inspections of pressure pipes.

[0079] Safety performance inspection involves all aspects of special equipment, including reliability inspection of boiler liquid level, temperature alarm interlocking devices, inspection of external surface corrosion of pressure pipes, functional testing of elevator floor doors, car doors, and brakes, and air tightness inspection of pressure vessels.

[0080] like Figure 1As shown in the figure, an automatic recognition method for special equipment inspection reports includes:

[0081] S1. The user calls the special equipment inspection report and identifies the special equipment report information;

[0082] Among them, the special equipment inspection reports are stored in the database. The user retrieves and calls the data through the interface or API provided by the system, and quickly locates, searches, and filters the required report information according to conditions such as time range, special equipment type, report status, etc.;

[0083] The special equipment inspection criteria are used to screen the special equipment report information and clean the special equipment report information. The special equipment inspection criteria include important inspection items for special equipment.

[0084] The important inspection items for special equipment are used to set the weights of the special equipment inspection items, that is, to screen the important detection indicators among all the inspection items of special equipment;

[0085] S2. Call the special equipment inspection criteria to perform duplicate information cleaning and interference information identification and filtering on the special equipment report information;

[0086] The duplicate information cleaning includes text similarity analysis and duplicate record representation;

[0087] The text similarity analysis compares the report texts through a text similarity algorithm to identify and mark highly similar or identical reports;

[0088] The duplicate record representation marks the duplicate report records as "duplicate" and decides to retain the latest or most complete copy while deleting other duplicate copies;

[0089] Among them, the special equipment inspection criteria are not only used to clean the special equipment report information, but also include the focus points corresponding to different special equipment inspection items, and are thus used to set the initial weights of the special equipment inspection items;

[0090] The interference information identification and filtering include stop word filtering and keyword extraction;

[0091] Further, for stop word filtering: use a stop word list to filter out common words and meaningless information in the report, such as "de", "shi", "zai", etc., to reduce interference;

[0092] The keyword extraction identifies and retains key information related to special equipment, problem types, etc. through keyword extraction technology, and filters out content irrelevant to the theme;

[0093] The cleaning tools include text processing libraries and algorithms, which help to identify and delete duplicate and interference information, and optimize the cleaning process and algorithms to ensure efficient processing of a large amount of report information while maintaining the report quality and accuracy.

[0094] S3. Conduct preliminary screening of special equipment report information content, conduct report quality inspection and audit status verification;

[0095] Report quality checks include completeness checks and format structure checks;

[0096] Furthermore, integrity checks are used to ensure the integrity of necessary fields and information items in the report, such as the model of special equipment, operator authentication information, and report timestamp.

[0097] Format and structure checks are used to verify that the format of the report complies with the predetermined template or standard, ensuring the consistency and understandability of the data structure.

[0098] Among them, audit status verification includes audit field checking and audit process tracking;

[0099] Furthermore, the audit field check is used to confirm whether there are any identifiers or fields in the report with abnormal audit status, such as the auditor's signature or audit time.

[0100] Audit process tracking is used to record and track the audit history of reports to determine whether they have passed the internal audit process;

[0101] Conduct preliminary screening of special equipment report information content through data analysis models;

[0102] The data analysis model calculates the quality similarity of the data points in the special equipment report information inspection items. If the data point quality similarity is greater than a preset threshold, it is a correct item, and the correct item is used as the basic data for calculating the weight of the special equipment report information inspection item. If the data point quality similarity is less than the preset threshold, it is a data point with low report quality, missing data, and abnormal audit status verification, and the corresponding inspection items are removed. The data analysis model is pruned and optimized through the inspection model;

[0103] The quality similarity is used to describe the accuracy of the inspection items in the special equipment report information;

[0104] The data analysis model calculation expression is as follows:

[0105] ;

[0106] in, is the quality similarity between the data points x in the test item C, is the circumference constant, is a data point in the inspection item C of the special equipment report information, C is the inspection item of the special equipment, C is the inspection item sequence number, which is 1, 2, 3, ..., n, n is the total number of inspection items, and n is a positive integer; is the mean of all data points of test item C, is the covariance matrix of all data points of test item C, is the expected degree that the data point x belongs to the test item C;

[0107] The data analysis model determines the correct item by calculating the quality similarity between the data points in the inspection items. Different data analysis models are trained for different inspection items. Different special equipment uses different data analysis models, but the principles of the data analysis models are the same.

[0108] Furthermore, The value is greater than 0 and less than 1;

[0109] The test model optimizes the data analysis model by calculating the error similarity of the mixed data in the data analysis model and fitting it as a difference coefficient. The calculation expression of the test model is as follows:

[0110] ;

[0111] Among them, Q is the error similarity of mixed data in the data analysis model, is the quality similarity between the data points in the kth inspection item in the special equipment report information output by the data analysis model, is the density similarity of the data points in the input test item k, where k is an ordinal number ranging from 1, 2, 3, ..., n;

[0112] Both k and C are test items. To avoid ambiguity in algorithm logic, two letters are used to represent the same meaning;

[0113] Mixed data includes data with a mixture of numerical and categorical attributes;

[0114] The inspection model adds optimization coefficients to the data analysis model through the optimization port, automatically corrects the analysis errors of the data analysis model on the inspection items and makes corrections;

[0115] Density similarity refers to the probability of an event occurring randomly. The similarity density is equal to the similarity of an interval divided by the length of the interval. Its value is non-negative and can be large or small.

[0116] S4. Filter the inspection item sequence in the special equipment report information sorted by weight by calculating the inspection item weight of the special equipment report information;

[0117] The inspection item data of the special equipment report information is output through the inspection item monitoring function. The expression of the inspection item monitoring function is as follows:

[0118] ;

[0119] in, is the weight of the i-th inspection item in the special equipment report information, To input the data corresponding to the i-th inspection item of the special equipment report information, is the deviation constant value, H is the inspection item data of the special equipment monitoring report information;

[0120] The data corresponding to the i-th inspection item of the input special equipment report information is the data point data corresponding to the i-th inspection item;

[0121] The weight of the i-th inspection item in the special equipment information report is determined by calling the special equipment inspection criteria. Since different special equipment inspection items have different emphases in the requirements of the special equipment inspection criteria, the weights of the inspection items in the special equipment information report are also different.

[0122] By calculating the weight difference between the i-th and i+1-th inspection items in the special equipment report information, the inspection item with the largest inspection item weight in the special equipment report information is screened out;

[0123] The calculation expression for filtering out the inspection item with the largest inspection item weight in the special equipment report information is as follows:

[0124] ;

[0125] in, is the weight of the i+1th inspection item in the special equipment report information, is the weight screening coefficient, Report inspection item data for special equipment information, Mathematical symbols for deviation.

[0126] S5. Analyze and evaluate the selected inspection item sequence through the special equipment report information assessment;

[0127] After screening out the inspection item with the largest inspection item weight in the special equipment report information, the method further includes:

[0128] Eliminate the inspection item with the largest inspection item weight from the inspection items of the special equipment report information, and obtain the inspection item with the largest inspection item weight in the inspection items of the special equipment report information again, until all inspection items are sorted according to the weight;

[0129] Obtain the test results of the test items in the screened test item sequence, evaluate the test results through the error function and output the error term, if the error term is greater than the preset error threshold, the test result of the test item is unqualified, and the unqualified test item is scored by the error value, if the error term is less than the preset error threshold, the test result of the test item is qualified, and the qualified test item is scored by the error value;

[0130] The error function calculation expression is as follows:

[0131] ;

[0132] in, Output the error term for the error function, The test result of the i-th test item of the special equipment report information, The theoretical value of the i-th inspection item of the special equipment report information;

[0133] The scoring mechanism is determined by the error value; the error value is the difference between the error term and the error threshold.

[0134] S6. Feedback the analysis results of the special equipment report information to the special equipment report information evaluation storage module;

[0135] Feedback the analysis results of special equipment report information to the special equipment report information evaluation storage module, including data format conversion, data transmission and reception, data verification and quality control, storage and archiving of the analysis results;

[0136] Furthermore, the data format conversion includes ensuring that the analysis results are output in a format acceptable to the special equipment report information evaluation storage module. This involves converting the data into a specific structured format, such as JSON, XML, etc., for subsequent processing and storage.

[0137] The data transmission and reception includes establishing a stable and secure data transmission channel to ensure that the analysis results can be safely and timely transmitted to the special equipment report information evaluation storage module. Common methods include using API interface, file transfer protocol (such as FTP), or direct database connection.

[0138] The data verification and quality control includes data verification and quality control before the analysis results are transmitted to the special equipment report information evaluation storage module. This includes ensuring the integrity, consistency and accuracy of the data and avoiding data loss or damage during the transmission process.

[0139] The storage and archiving includes storing the analysis results in a special equipment report information evaluation storage module, which is a database system, data warehouse or a specific information management system to ensure that data can be stored and retrieved for a long time.

[0140] S7. Update the generated special equipment information evaluation report based on feedback and evaluation results.

[0141] Updating the generated special equipment information assessment report involves integrating new feedback and assessment results into the existing report to ensure the completeness and timeliness of the report, including data integration and updating, report structure adjustment, quality review and verification, notification and communication, and regular update and maintenance;

[0142] The data integration and update includes integrating new feedback and evaluation results with existing special equipment information assessment reports, including adding new data fields to the report, updating existing data entries, or marking changes and corrections to existing information;

[0143] The report structure adjustment adjusts the structure and format of the special equipment inspection report through new feedback and evaluation results. Ensure the logic and information flow of the report, and reflect the latest data and analysis results;

[0144] The quality review and verification include quality review of special equipment inspection reports, verification of the accuracy and consistency of updated report contents, and ensuring that all updated data and information undergo the correct verification and review process.

[0145] Notification and communication are used to notify report users, management or other relevant teams of updates and changes to the report to ensure that everyone is using the latest and accurate information.

[0146] Establish a regular update strategy through regular updates and maintenance to ensure that the special equipment information evaluation report reflects the latest feedback and evaluation results at any time.

[0147] Embodiment 2

[0148] like Figure 2 As shown, an automatic recognition system for special equipment inspection reports includes:

[0149] Collection module, used to collect and integrate special equipment report information;

[0150] A storage module, used for storing the integrated special equipment report information and the special equipment report information evaluation results;

[0151] The processing module includes a preliminary processing unit for retrieving special equipment inspection criteria and preliminarily processing special equipment report information, a screening unit for reviewing special equipment report information, and a weight marking unit for marking and stratifying inspection items in the special equipment report information;

[0152] The report analysis module includes a calculation unit for calculating the weight of the inspection item in the special equipment report information, and an analysis unit for receiving the weight of the inspection item in the special equipment report information and analyzing the inspection result of the inspection item;

[0153] Report evaluation module, used to evaluate and assess special equipment report information;

[0154] A feedback module, comprising a feedback data unit for feeding back the evaluation result of the special equipment report information to the storage module, and a feedback user unit for feeding back the evaluation result of the special equipment report information to the user end;

[0155] The report updating module includes a printing unit for generating a special equipment information evaluation report and an updating unit for updating the special equipment information evaluation report according to the evaluation result of the special equipment report information.

[0156] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only two embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are, for example, the size, scale, structure, shape and proportion of various elements, as well as parameter values ​​(e.g., temperature, pressure, etc.), installation arrangements, use of materials, color, directional changes, etc., without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method steps can be changed or reordered according to alternative embodiments. Any "device plus function" clause is intended to cover the structure of the execution function described herein, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0157] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment may not be described (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those features that are not relevant to implementing the invention).

[0158] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort is complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0159] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for automatically identifying a special equipment inspection report, characterized in that: include: S1. The user calls the special equipment inspection report and identifies the special equipment report information; S2. Call the special equipment inspection criteria to clean duplicate information and identify and filter interference information in special equipment report information; S3. Conduct preliminary screening of special equipment report information content, conduct report quality inspection and audit status verification; The report quality check includes completeness check and format structure check; The audit status verification includes audit field checking and audit process tracking; Conduct preliminary screening of special equipment report information content through data analysis models; The data analysis model calculates the quality similarity of the data points in the special equipment report information inspection items. If the data point quality similarity is greater than a preset threshold, it is a correct item, and the correct item is used as the basic data for calculating the weight of the special equipment report information inspection item. If the data point quality similarity is less than the preset threshold, it is a data point with low report quality, missing data, and abnormal audit status verification, and the corresponding inspection items are removed. The data analysis model is pruned and optimized through the inspection model; The quality similarity is used to describe the accuracy of the inspection items in the special equipment report information. The data analysis model calculation expression is as follows: ； in, is the quality similarity between the data points x in the test item C, is the circumference constant, is a data point in the inspection item C of the special equipment report information, C is the inspection item of the special equipment, C is the inspection item sequence number, which is 1, 2, 3, ..., n, n is the total number of inspection items, and n is a positive integer; is the mean of all data points of test item C, is the covariance matrix of all data points of test item C, is the expected degree that the data point x belongs to the test item C; The test model optimizes the data analysis model by calculating the error similarity of the mixed data in the data analysis model and fitting it as a difference coefficient. The calculation expression of the test model is as follows: ； Among them, Q is the error similarity of mixed data in the data analysis model, is the quality similarity between the data points in the kth inspection item in the special equipment report information output by the data analysis model, is the density similarity of the data points in the input test item k, where k is an ordinal number ranging from 1, 2, 3, ..., n; The inspection model adds optimization coefficients to the data analysis model through the optimization port, automatically corrects the analysis errors of the data analysis model on the inspection items and makes corrections; S4. Filter the inspection item sequence in the special equipment report information sorted by weight by calculating the inspection item weight of the special equipment report information; S5. Analyze and evaluate the selected inspection item sequence through the special equipment report information assessment; S6. Feedback the analysis results of the special equipment report information to the special equipment report information evaluation storage module; S7. Update the generated special equipment information evaluation report based on feedback and evaluation results.

2. The method for automatically identifying a special equipment test report according to claim 1, characterized in that: The duplicate information cleaning includes text similarity analysis and duplicate record representation; The interference information identification and filtering includes stop word filtering and keyword extraction; Special equipment inspection criteria are used to screen and clean special equipment report information.

3. The method for automatically identifying a special equipment test report according to claim 2, characterized in that: The inspection item data of the special equipment report information is output through the inspection item monitoring function. The expression of the inspection item monitoring function is as follows: ； in, is the weight of the i-th inspection item in the special equipment report information, To input the data corresponding to the i-th inspection item of the special equipment report information, is the deviation constant value, H is the inspection item data of the special equipment monitoring report information; By calculating the weight difference between the i-th and i+1-th inspection items in the special equipment report information, the inspection item with the largest inspection item weight in the special equipment report information is screened out; The calculation expression for filtering out the inspection item with the largest inspection item weight in the special equipment report information is as follows: ； in, is the weight of the i+1th inspection item in the special equipment report information, is the weight screening coefficient, Report inspection item data for special equipment information, Mathematical symbols for deviation.

4. The automatic identification method of a special equipment test report according to claim 3 is characterized in that: After screening out the inspection item with the largest inspection item weight in the special equipment report information, the method further includes: Eliminate the inspection item with the largest inspection item weight from the inspection items of the special equipment report information, and obtain the inspection item with the largest inspection item weight in the inspection items of the special equipment report information again, until all inspection items are sorted according to the weight; Obtain the test results of the test items in the screened test item sequence, evaluate the test results through the error function and output the error term, if the error term is greater than the preset error threshold, the test result of the test item is unqualified, and the unqualified test item is scored by the error value, if the error term is less than the preset error threshold, the test result of the test item is qualified, and the qualified test item is scored by the error value; The error function calculation expression is as follows: ； in, Output the error term for the error function, The test result of the i-th test item of the special equipment report information, The theoretical value of the i-th test item in the special equipment report information.

5. The method for automatically identifying a special equipment test report according to claim 4, characterized in that: Feedback the analysis results of special equipment report information to the special equipment report information evaluation storage module, including data format conversion, data transmission and reception, data verification and quality control, storage and archiving of the analysis results; The data format conversion includes ensuring that the analysis results are output in a format acceptable to the special equipment report information evaluation storage module; The data transmission and reception includes establishing a stable and secure data transmission channel; The data verification and quality control includes performing data verification and quality control before transmitting the analysis results to the special equipment report information evaluation storage module; The storage and archiving include storing the analysis results in a special equipment report information evaluation storage module.

6. The method for automatically identifying a special equipment test report according to claim 5, characterized in that: The updating of the generated special equipment information assessment report includes data integration and updating, report structure adjustment, quality review and verification, notification and communication, and regular updating and maintenance; The data integration and update includes integrating new feedback and evaluation results with existing special equipment information evaluation reports; The report structure adjustment adjusts the structure and format of the special equipment inspection report through new feedback and evaluation results; The quality review and verification mentioned above includes quality review of special equipment inspection reports; The notification and communication include notification of updates and changes to the special equipment information evaluation report.

7. An automatic recognition system for special equipment test reports, used to implement an automatic recognition method for special equipment test reports according to any one of claims 1 to 6, characterized in that: include: Collection module, used to collect and integrate special equipment report information; A storage module, used for storing the integrated special equipment report information and the special equipment report information evaluation results; The processing module includes a preliminary processing unit for retrieving special equipment inspection criteria and preliminarily processing special equipment report information, a screening unit for reviewing special equipment report information, and a weight marking unit for marking and stratifying inspection items in the special equipment report information; The report analysis module includes a calculation unit for calculating the weight of the inspection item in the special equipment report information, and an analysis unit for receiving the weight of the inspection item in the special equipment report information and analyzing the inspection result of the inspection item; Report evaluation module, used to evaluate and assess special equipment report information; A feedback module, comprising a feedback data unit for feeding back the evaluation result of the special equipment report information to the storage module, and a feedback user unit for feeding back the evaluation result of the special equipment report information to the user end; The report updating module includes a printing unit for generating a special equipment information evaluation report and an updating unit for updating the special equipment information evaluation report according to the evaluation result of the special equipment report information.

8. An electronic device, characterized in that: include: A memory for storing instructions; A processor is used to execute the instruction so that the device executes a method for automatically identifying a special equipment detection report as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, it implements a method for automatically identifying a special equipment inspection report as described in any one of claims 1 to 6.

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