LDAR evaluation system and method based on big data mining and analysis

Abstract

The embodiment of the present invention provides an LDAR evaluation system based on big data mining and analysis, the system includes: a data storage layer for storing raw data of leak detection and repair; a data application layer for providing data analysis applications for the data storage layer, the data application layer includes a data analysis module and a project review module; the data analysis module is used to respond to the user's data analysis operation to obtain the association between the raw data of leak detection and repair, and form decision-making knowledge; the project review module is used to establish an audit project for leak detection and repair, and review the compliance of the audit project, and output an evaluation report. At the same time, an LDAR evaluation method based on big data mining and analysis is also provided. The above technical solution of the present invention realizes the rapid evaluation of the operating effect of the LDAR device, which is conducive to the formulation and implementation of key control measures for unorganized emissions of equipment.

Description

Technical Field

[0001] The present invention relates to the field of environmental technology, and in particular to an LDAR evaluation system based on big data mining and analysis, an LDAR evaluation method based on big data mining and analysis, and a corresponding storage medium. Background Art

[0002] LDAR (Leak Detection And Repair): Leak detection and repair is to detect potential leak points in refining and chemical equipment, promptly identify components with leaks, and repair or replace them, thereby reducing leakage emissions.

[0003] Equipment leakage is an important source of VOCs unorganized emissions. The Air Pollution Prevention and Control Law and other laws and regulations have put forward the requirements for leak detection and repair LDAR to control the unorganized VOCs leaking from equipment and pipeline components such as pumps, compressors, valves, flanges, etc., and strengthen the control of equipment and pipeline component leakage. For equipment and pipeline components in enterprises that carry gaseous and liquid VOCs materials and have more than or equal to 2,000 sealing points, LDAR work should be carried out as required.

[0004] With the implementation of the LDAR system, a petrochemical enterprise has tens of thousands to hundreds of thousands of LDAR controlled sealing points. According to national standards, at least 2-4 tests are required each year. Each unit has a continuous operation cycle of 3-6 years. Therefore, in each operation cycle, a petrochemical enterprise has hundreds of thousands to millions of LDAR data. In view of the current status of LDAR operation and management, how to evaluate the leakage control effect of the enterprise's equipment and how the enterprise or a third party can optimize and improve the LDAR performance are issues of great concern to domestic VOCs-related enterprises and government environmental protection departments. However, a large petrochemical enterprise has as many as 700,000 sealing points. According to the above principles, more than 20,000 sealing points need to be sampled. The sampling test requires a lot of manpower and time, which is not feasible and is not conducive to the comprehensive implementation of the audit work. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide an LDAR evaluation system and method based on big data mining and analysis, so as to at least solve the problem of low evaluation efficiency caused by the large data scale of the existing LDAR.

[0006] In order to achieve the above object, in a first aspect of the present invention, a LDAR evaluation system based on big data mining and analysis is provided, the system comprising:

[0007] The data access layer is used to provide the original data of the LDAR project to be analyzed; the original data includes historical original data and real-time original data;

[0008] A data storage layer, used for storing the raw data of the LDAR project to be analyzed;

[0009] The data application layer is used to provide data analysis applications for the data storage layer.

[0010] Optionally, the data access layer includes a data acquisition module, an on-site inspection and detection module, and an interface module;

[0011] The data acquisition module is used to respond to the user's data acquisition operation, extract data from the historical raw data of the LDAR project to be analyzed, and store it in the data storage layer;

[0012] The on-site inspection and detection module is used to respond to the on-site inspection and detection operation of the user, to inspect and detect the extracted devices, groups and sealing points on-site, and to store the generated real-time raw data into the data storage layer;

[0013] The interface module is used to respond to the reading and storage operations of user data, and connect the data acquisition module with the historical original data of the LDAR project to be analyzed and the data storage layer respectively; at the same time, the on-site inspection and detection module is connected with the data storage layer to complete the original data transmission.

[0014] Optionally, the data application layer includes a data analysis module and a project review module;

[0015] The data analysis module is used to respond to the data analysis operation of the user to obtain the association between the original data of the LDAR project to be analyzed and form decision-making knowledge;

[0016] The project review module is used to establish an audit of the LDAR project, evaluate the compliance of the LDAR project, and output an evaluation report.

[0017] Optionally, the data acquisition module includes: a project establishment data acquisition submodule, a detection and repair data acquisition submodule, and an operation and management data acquisition submodule;

[0018] The project establishment data acquisition submodule is used to collect project establishment related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer;

[0019] The detection and repair data acquisition submodule is used to collect detection and repair related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer;

[0020] The operation and management data acquisition submodule is used to collect operation and management related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer.

[0021] Optionally, the on-site inspection and detection module includes: an on-site sampling submodule, a project establishment on-site inspection submodule, a detection and repair on-site inspection submodule, a detection and repair on-site detection submodule, and an operation and management on-site inspection submodule;

[0022] The field sampling submodule is used to extract devices, groups and sealing points from the LDAR items to be analyzed to form device samples, group samples and sealing point samples;

[0023] The project establishes an on-site inspection submodule for on-site inspection of the consistency between the relevant data of the device samples, group samples and sealing point samples and the actual on-site conditions, including: the components and concentrations (quality) of the raw materials, additives, intermediate products and products processed by the controlled device, the components and concentrations (quality) of the materials contacting the equipment and pipelines, group codes, group location information, sealing point codes, sealing point location information, sealing point categories and material forms;

[0024] The detection and repair on-site inspection submodule is used to check the compliance of the detection and repair related operations of the sealing point samples on-site; including instrument calibration, background detection, detection distance, detection speed, detection reading, instrument drift verification, leakage sealing point identification, delayed repair leakage sealing point identification and delayed repair reasons;

[0025] The detection and repair on-site detection submodule is used for on-site detection of the sealing point samples, and includes a gas leakage detection instrument based on hydrogen flame ionization and / or gas optical imaging.

[0026] The operation and management on-site inspection submodule is used for on-site inspection of the actual operation of LDAR on the sealing point samples, including detection task allocation, detection task downloading, detection path management, detection data uploading, calibration management, leakage identification and emission calculation.

[0027] Optionally, the interface module includes: a historical original data transmission interface submodule, a project establishment on-site inspection data transmission interface submodule, a detection and repair on-site inspection data transmission interface submodule, a detection and repair on-site inspection data transmission interface submodule, and an operation and management on-site inspection data transmission interface submodule;

[0028] The historical original data transmission interface submodule is used to connect to the data acquisition module, and the data acquisition module accesses and reads the historical original data of the LDAR project to be analyzed through the historical original data transmission interface submodule, and stores the relevant data in the data storage layer;

[0029] The on-site inspection data transmission interface submodule of the project establishment is connected to the on-site inspection submodule of the project establishment, and the relevant real-time data generated by the on-site inspection submodule of the project establishment is stored in the data storage layer through the on-site inspection data transmission interface submodule of the project establishment.

[0030] The detection and repair on-site inspection data transmission interface submodule is used to connect the detection and repair on-site inspection submodule, and the relevant real-time data generated by the detection and repair on-site inspection submodule is stored in the data storage layer through the detection and repair on-site inspection data transmission interface submodule.

[0031] The detection and repair on-site detection data transmission interface submodule is used to connect the detection and repair on-site detection submodule, and the relevant real-time data generated by the detection and repair on-site detection submodule is transmitted to the data storage layer through the detection and repair on-site detection data transmission interface submodule.

[0032] The operation and management on-site inspection data transmission interface submodule is used to connect the operation and management on-site inspection submodule, and the relevant real-time data of the operation and management on-site inspection submodule is transmitted to the data storage layer through the operation and management on-site inspection data transmission interface submodule.

[0033] The data analysis module is used to respond to the user's data analysis operation to obtain the association between the original data of the LDAR and form decision-making knowledge;

[0034] The project review module is used to establish LDAR review projects, review the compliance of the review projects, and output an evaluation report.

[0035] Optionally, the data analysis module includes: an LDAR data extraction submodule, an LDAR data preprocessing submodule, an LDAR data mining and analysis submodule, and an LDAR decision-making knowledge application submodule;

[0036] The LDAR data extraction submodule is used to extract the raw data to be analyzed from the data storage layer;

[0037] The LDAR data preprocessing submodule is used to clean the raw data to be analyzed to obtain cleaned data;

[0038] The LDAR data mining and analysis submodule is used to form decision-making knowledge based on the cleaned data and the data analysis algorithm configured by the user; and

[0039] The LDAR decision knowledge application submodule is used to form a number of measures and suggestions based on the decision knowledge.

[0040] Optionally, the project review module includes: a project establishment status submodule, a detection and repair status submodule, an operation and management status submodule, and an evaluation report generation submodule;

[0041] The project establishment status submodule is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant;

[0042] The detection and repair status submodule is used to check whether the detection and repair related data of the LDAR project to be analyzed are compliant;

[0043] The operation and management status submodule is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant;

[0044] The evaluation report generation submodule is used to generate an evaluation report for the LDAR project to be analyzed according to the evaluation results.

[0045] Optionally, the project establishment related data of the LDAR project to be analyzed includes: controlled scope and basic data;

[0046] The controlled scope includes: the components and concentration (quality) of raw materials, additives, intermediate products and products processed by the controlled device, and the components and concentration (quality) of materials contacted by equipment and pipelines;

[0047] The basic data includes: group code, group location information, sealing point code, sealing point location information, sealing point category and material form.

[0048] Optionally, the detection and repair related data of the LDAR project to be analyzed include: detection related data and repair related data;

[0049] The detection-related data include: instrument calibration, background detection, detection distance, detection speed, detection data, detection frequency, and instrument drift verification;

[0050] The repair-related data include: the first maintenance time and repair time of the leaking sealing point, retest data and the reason for delayed repair of the leaking sealing point.

[0051] Optionally, the operation and management related data to be analyzed include: operation related data, management related data;

[0052] The operation-related data include: group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification and emission calculation, maintenance task allocation, and repair record upload;

[0053] The management-related data include: system LDAR regulations, system emission calculation methods, and pollutant emission permit thresholds.

[0054] In a second aspect of the present invention, a LDAR evaluation method based on big data mining analysis is also provided, the method comprising:

[0055] The data collection step is used to collect relevant data from the historical raw data of the LDAR project to be analyzed through the interface according to the user operation, and store it in the data storage layer;

[0056] The on-site inspection and detection step is used to carry out inspection and / or detection on the devices, groups and sealing points extracted on-site according to the user operation, and store the generated relevant real-time raw data to the data storage layer through the interface;

[0057] The data analysis step is used to obtain the association between the original data of the LDAR according to the user operation and form decision-making knowledge;

[0058] The project review step is used to establish an LDAR review project based on the user operation, review the compliance of the LDAR project, and output an evaluation report.

[0059] Optionally, the data collection step includes the following sub-steps: a project establishment data collection sub-step, a detection and repair data collection sub-step, and an operation and management data collection sub-step;

[0060] The project establishment data collection sub-step is used to collect project establishment related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer;

[0061] The detection and repair data collection sub-step is used to collect detection and repair related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer;

[0062] The operation and management data collection sub-step is used to collect operation and management related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer.

[0063] Optionally, the on-site inspection and testing step includes the following sub-steps: an on-site sampling sub-step, a project establishment on-site inspection sub-step, a detection and repair on-site inspection sub-step, a detection and repair on-site inspection sub-step, and an operation and management on-site inspection sub-step;

[0064] The on-site sampling sub-step is used to extract devices, groups and sealing points from the LDAR items to be analyzed to form device samples, group samples and sealing point samples;

[0065] The project establishment on-site inspection sub-step is used to inspect on-site whether the relevant data of the project establishment of the device samples, group samples and sealing point samples are consistent with the actual situation on site, including: the components and concentrations (quality) of the raw materials, additives, intermediate products and products processed by the controlled device, the components and concentrations (quality) of the materials contacting the equipment and pipelines, group codes, group location information, sealing point codes, sealing point location information, sealing point categories and material forms;

[0066] The detection and repair on-site inspection sub-step is used to check on-site whether the relevant operations of the detection and repair of the sealing point samples are in compliance; including instrument calibration, background detection, detection distance, detection speed, detection reading, instrument drift verification, leakage sealing point identification, delayed repair of leakage sealing point identification and delayed repair reasons;

[0067] The detection and repair on-site detection sub-step is used for on-site detection of the sealing point samples; the detection and repair on-site detection sub-step includes but is not limited to using a hydrogen flame ionization and / or gas optical imaging gas leakage detection instrument to detect the extracted sealing points.

[0068] The operation and management on-site inspection sub-step is used to conduct on-site inspection of the compliance of the actual operation of LDAR on the sealing point samples, including detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification and emission calculation.

[0069] Carry out project analysis based on the LDAR raw data in the data storage layer.

[0070] In response to user operations, analyzing and applying the data in the data storage layer, wherein the analyzing and applying includes data analysis and project review;

[0071] The data analysis is used to obtain the association between the raw data of the LDAR according to the user operation and form decision-making knowledge;

[0072] The project review is used to establish LDAR review projects based on the user operations, review the compliance of the review projects, and output an evaluation report.

[0073] Optionally, the data analysis includes the following sub-steps: LDAR data extraction sub-step, LDAR data pre-processing sub-step, LDAR data mining analysis sub-step and LDAR decision-making knowledge application sub-step;

[0074] The LDAR data extraction sub-step is used to extract the raw data to be analyzed from the data storage layer;

[0075] The LDAR data preprocessing sub-step is used to clean the raw data to be analyzed to obtain cleaned data;

[0076] The LDAR data mining and analysis sub-step is used to form decision-making knowledge based on the cleaned data and the data analysis algorithm configured by the user; and

[0077] The LDAR decision knowledge application sub-step is used to form a number of measures and suggestions based on the decision knowledge.

[0078] Optionally, the project review includes: a LDAR project establishment review sub-step, a detection and maintenance review sub-step, a LDAR operation and management review sub-step, and an evaluation report generation sub-step;

[0079] The LDAR project establishment status review sub-step is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant;

[0080] The inspection and repair status review sub-step is used to check whether the inspection and repair related data of the LDAR project to be analyzed are compliant;

[0081] The LDAR operation and management status review sub-step is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant;

[0082] The evaluation report generation sub-step is used to generate an evaluation report for the LDAR project to be analyzed based on the inspection results.

[0083] Optionally, the project establishment related data of the LDAR project to be analyzed includes: controlled scope and basic data;

[0084] The controlled scope includes: the components and concentration (quality) of raw materials, additives, intermediate products and products processed by the controlled device, and the components and concentration (quality) of materials contacted by equipment and pipelines;

[0085] The basic data includes: group code, group location information, sealing point code, sealing point location information, sealing point category and material form.

[0086] Optionally, the detection and repair related data of the LDAR project to be analyzed include: detection related data, repair related data;

[0087] The test-related data include: instrument calibration, background detection, test speed, test data, test frequency, and instrument drift verification;

[0088] The repair-related data include: the first maintenance time and repair time of the leaking sealing point, retest data and the reason for delayed repair of the leaking sealing point.

[0089] Optionally, the operation and management related data to be analyzed include: operation related data, management related data;

[0090] The operation-related data includes: group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification, emission calculation, maintenance task allocation, and repair record upload;

[0091] The management-related data include: system LDAR regulations, system emission calculation methods, and pollutant emission permit thresholds.

[0092] Optionally, the evaluation report of the LDAR project to be analyzed includes: evaluation overview, enterprise overview, overview of the LDAR project to be analyzed, evaluation method and process, and evaluation conclusion;

[0093] The evaluation overview includes: evaluation basis, evaluation scope, and evaluation procedures;

[0094] The company overview includes: main production processes, production capacity and / or processing capabilities, and geographical location;

[0095] The overview of the LDAR project to be analyzed includes: the number of controlled devices and their operating conditions, the number of sealing points, the number of inaccessible points, the start time of the LDAR project to be analyzed, and the operating mode;

[0096] The evaluation method and process include: evaluation start and completion dates, on-site sampling methods and results, testing instruments and operation procedures used for on-site inspection and testing, and data analysis and mining methods;

[0097] The evaluation conclusions include: compliance of project establishment, compliance of detection and repair, compliance of operation and management, and suggestions for project improvement.

[0098] In the third aspect of the present invention, a server is also provided, on which the aforementioned LDAR evaluation system based on big data mining and analysis is loaded.

[0099] In a fourth aspect of the present invention, a machine-readable storage medium is provided, on which instructions are stored, and when the machine-readable storage medium is run on a computer, the computer executes the aforementioned LDAR evaluation method based on big data mining analysis.

[0100] The above technical scheme of the present invention proposes a LDAR evaluation system and method based on big data mining and analysis, which realizes the rapid evaluation of the LDAR operation effect of the device, is conducive to the formulation and implementation of optimization measures for equipment leakage control, reduces the unorganized emissions of VOCs, and improves the social and economic benefits of LDAR.

[0101] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0103] Figure 1 It is a structural diagram of an LDAR evaluation system based on big data mining and analysis provided by one embodiment of the present invention;

[0104] Figure 2 It is a structural diagram and a data acquisition flow chart of a data acquisition module provided by an optional implementation mode of the present invention;

[0105] Figure 3 is a structural diagram of an on-site inspection and detection module provided by an optional embodiment of the present invention;

[0106] Figure 4 is a structural diagram of a data analysis module provided by an optional embodiment of the present invention;

[0107] Figure 5 is a structural diagram of a project review module provided by an optional implementation mode of the present invention;

[0108] Figure 6 It is a flow chart of an LDAR evaluation method based on big data mining and analysis provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0109] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0110] In the embodiments of the present invention, unless otherwise specified, directional words such as "up, down, top, bottom" are usually used with reference to the directions shown in the drawings or are used to describe the relative positional relationships of components in the vertical, perpendicular or gravity direction.

[0111] Figure 1 FIG. 1 is a structural diagram of an LDAR evaluation system based on big data mining and analysis provided by an embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides an LDAR evaluation system based on big data mining and analysis, and the system includes:

[0112] The data access layer is used to provide historical raw data and real-time raw data of the LDAR project to be analyzed, and the data access layer includes a data acquisition module, an on-site inspection and detection module, and an interface module;

[0113] Data storage layer, used for storing the original data of LDAR;

[0114] A data application layer, used to provide data analysis applications for the data storage layer, the data application layer includes a data analysis module and a project review module;

[0115] The data acquisition module is used to respond to the user's data acquisition operation, extract data from the historical raw data of the LDAR project to be analyzed, and store it in the data storage layer;

[0116] The on-site inspection and detection module is used to respond to the on-site inspection and detection operation of the user, to inspect and detect the extracted devices, groups and sealing points on-site, and to store the generated real-time raw data into the data storage layer;

[0117] The interface module is used to respond to the reading and storage operations of user data, connect the data acquisition module with the historical raw data of the LDAR project to be analyzed and the data storage layer respectively; and connect the on-site inspection and detection module with the data storage layer to complete the raw data transmission;

[0118] The data analysis module is used to respond to the user's data analysis operation to obtain the association between the original data of the LDAR and form decision-making knowledge;

[0119] The project review module is used to establish LDAR review projects, review the compliance of the review projects, and output an evaluation report.

[0120] In this way, the data access layer transmits the historical raw data of the LDAR to be analyzed and the real-time data of the controlled sealing points sampled on site to the data storage layer through the interface module. The raw data of the LDAR project to be analyzed is stored in the data storage layer, and the data application layer provides the function of external data analysis application, so that the structure of the entire big data LDAR evaluation system is clear and the data interaction between modules is simplified. The unified management of data by the data storage layer reduces the maintenance cost of LDAR data; the free configuration of the business layer modules enriches the functions of the system. This embodiment provided by the present invention realizes the rapid evaluation of the operating effect of the LDAR device, which is conducive to the formulation and implementation of optimization measures for equipment leakage control and the reduction of unorganized emissions of VOCs.

[0121] Specifically, the data access layer is used to collect the historical original data of the LDAR project and the real-time original data of the controlled sealing points sampled on site; the historical original data refers to the operation data of the LDAR project to be analyzed in the time period to be evaluated before the evaluation. Real-time original data refers to the operation and related data generated by the evaluator during the evaluation process when he or she extracts some devices, groups and sealing points, and conducts on-site inspection and testing of the devices, groups and sealing points. Through the interface, the LDAR historical original data is connected and the historical original data is transmitted to the data storage layer; further. The detection instrument is connected to transmit the real-time original data to the data storage layer.

[0122] The data storage layer is used to store the original data of LDAR. The original data mainly refers to the massive historical original data accumulated during the operation of LDAR and the real-time original data of random sampling, such as sealing point coding, sealing point type, material form, test data, background records, quality control records and repair records, etc. Therefore, the software system can be used to collect the data and save it in the database to more safely protect the operating data integrity of the LDAR evaluation system.

[0123] The data application layer is used to provide data analysis applications for the data storage layer, and the application layer includes a data analysis module and a project review module; the data analysis module is used to respond to the user's data analysis operations to obtain the association between the original data of the LDAR and form decision-making knowledge; the project review module is used to establish LDAR audit projects, review the compliance of the audit projects, and output an evaluation report. Data analysis and project review are the two major functions provided by this embodiment. Data analysis can derive the overall status and characteristics of device equipment leakage through data mining, so that the current status of device VOCs emissions can be quickly evaluated and the direction of improvement of equipment leakage control can be determined. Project review reduces the cost of manual evaluation to a certain extent and improves the evaluation accuracy of the existing LDAR management system.

[0124] The following describes the data collection module of the data access layer, the on-site inspection and detection module, and the data analysis module and project review module of the data application layer respectively.

[0125] Figure 2 is a structural diagram and a data acquisition flow chart of a data acquisition module provided by an optional embodiment of the present invention, such as Figure 2 As shown, the data acquisition module includes: a project establishment data acquisition submodule, a detection and repair data acquisition submodule, and an operation and management data acquisition submodule;

[0126] The project establishment data acquisition submodule is used to collect project establishment related data from the historical original data of the LDAR project to be analyzed. The detection and repair data acquisition submodule is used to collect detection and repair related data from the historical original data of the LDAR project to be analyzed. The operation and management data acquisition submodule is used to collect operation and management related data from the historical original data of the LDAR project to be analyzed. The data acquisition module is connected to the LDAR project operation platform to be analyzed through the historical original data transmission interface submodule. The database storing the enterprise LDAR operation records can be accessed through the LDAR project operation platform, and the collected data is stored in the data storage layer. The details are as follows:

[0127] (1) Project establishment data collection submodule. The project establishment data collection submodule is used to extract data such as the composition and concentration (quality) of raw materials, additives, intermediate products and products processed by the controlled device, the composition and concentration (quality) of materials contacting the equipment and pipelines, group codes, group location information, sealing point codes, sealing point location information, sealing point categories and material forms from the LDAR project operation platform and database through the interface;

[0128] (2) Detection and repair data acquisition submodule. The detection and repair data acquisition submodule is used to extract data such as instrument calibration, background detection, detection data, instrument drift verification, first repair time and repair time of leaking seals, retest data, and reasons for delayed repair of leaking seals during the time period to be evaluated from the LDAR project operation platform and database through an interface;

[0129] (3) Operation and management data collection submodule. The operation and management data collection submodule is used to extract the operation and management related data of the time period to be evaluated from the LDAR project operation platform and database through the interface, including: group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification and emission calculation, maintenance task allocation, repair record upload, system LDAR regulations, system emission calculation method, pollutant discharge permit threshold, etc.

[0130] Figure 3 is a structural diagram of an on-site inspection and detection module provided by an optional embodiment of the present invention, such as Figure 3 As shown, the on-site inspection and detection module includes: an on-site sampling submodule, a project establishment on-site inspection submodule, a detection and repair on-site inspection submodule, a detection and repair on-site detection submodule, and an operation and management on-site inspection submodule;

[0131] The on-site sampling submodule is used to extract devices, groups and sealing points from the LDAR project to be analyzed to form device samples, group samples and sealing point samples; the project establishment on-site inspection submodule is used to conduct on-site inspection of the consistency between the relevant data of the project establishment of the device samples, group samples and sealing point samples and the actual situation on site; the detection and repair on-site inspection submodule is used to conduct on-site inspection of the compliance of the detection and repair related operations of the sealing point samples; the detection and repair on-site inspection submodule is used to conduct on-site inspection of the sealing point samples; the operation and management on-site inspection submodule is used to conduct on-site inspection of the actual operation of the LDAR for the sealing point samples; the details are as follows:

[0132] (1) On-site sampling submodule. The on-site sampling submodule is used to randomly select devices, groups and sealing points from the LDAR project operation platform or PFD or P&ID or device site. The overall sampling of sealing points can be carried out by simple random sampling or systematic sampling or stratified random sampling. The stratified random sampling can be stratified based on the device or sealing point type or material form, or the device, sealing point type and material form can be combined and stratified in the form of "and (indicated by *)" or "or (indicated by +)". For example, the gas valve and light liquid valve of the constant pressure reduction device can be expressed as: constant pressure reduction device*(gas+light liquid)*valve; the gas flange and gas connector of the constant pressure reduction device can be expressed as: constant pressure reduction device*gas*(flange+connector); constitute device samples, group samples and sealing point samples;

[0133] (2) Project establishment on-site inspection submodule. The project establishment on-site inspection submodule is used to check the components and concentrations of the processing raw materials, additives, intermediate products and products that the device samples, group samples and sealing point samples come into contact with, and to verify whether the controlled scope of the LDAR project to be analyzed is compliant; to verify the accuracy of the location description of the group samples and the sealing point samples, the uniqueness of the coding, and the consistency of the type of the sealing point samples and their material form with the on-site;

[0134] (3) Inspection and repair on-site inspection submodule. The inspection and repair on-site inspection submodule is used to check the compliance of the LDAR implementer's on-site operation of the sealing point sample; including instrument calibration, background detection, detection distance, detection speed, detection reading, instrument drift verification; check the compliance of the leakage sealing point identification, delayed repair leakage sealing point identification and delayed repair reasons;

[0135] (4) Inspection and repair on-site inspection submodule. The inspection and repair on-site inspection submodule is used to inspect the sealing point samples on-site. It includes using a hydrogen flame ionization gas leak detection instrument (FID) or a gas optical imaging gas leak detection instrument (OGI) to detect the extracted sealing points. Record the inspection data or video in accordance with standard requirements to provide real-time raw data for comparison with historical raw data;

[0136] (5) Operation and management on-site inspection submodule. The operation and management on-site inspection submodule is used to check the actual operation of the LDAR project operation platform during the LDAR project for the sealing point samples; including detection task allocation, detection task download, detection path management, detection data upload, calibration management, leakage identification and emission calculation;

[0137] Figure 4 is a structural diagram of a data analysis module provided by an optional embodiment of the present invention, such as Figure 4 As shown, the data analysis module includes: LDAR data extraction submodule, LDAR data preprocessing submodule, LDAR data mining and analysis submodule and LDAR decision knowledge application submodule;

[0138] The LDAR data extraction submodule is used to extract the raw data to be analyzed from the data storage layer; the LDAR data preprocessing submodule is used to clean the raw data to be analyzed to obtain cleaned data; the LDAR data mining and analysis submodule is used to form decision knowledge based on the cleaned data and the data analysis algorithm configured by the user; and the LDAR decision knowledge application submodule is used to form a number of measures and suggestions based on the decision knowledge. The details are as follows:

[0139] (1) LDAR historical raw data and LDAR real-time raw data. LDAR historical raw data mainly refers to the massive amount of information accumulated during the LDAR operation during the period to be evaluated, including but not limited to:

[0140] a) Project establishment related data. The components and concentrations (quality) of raw materials, additives, intermediate products and products processed by the controlled device, the components and concentrations (quality) of materials contacted by equipment and pipelines, group codes, group location information, sealing point codes, sealing point location information, sealing point categories and material forms;

[0141] b) Detection and repair related data. Instrument calibration, background detection, detection speed, detection data, detection frequency, instrument drift verification, first repair time and repair time of leaking seals, retest data, reasons for delayed repair of leaking seals;

[0142] c) Operation and management related data. Group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, maintenance task allocation, repair record upload, system LDAR regulations, system emission calculation method, pollution discharge permit threshold;

[0143] LDAR real-time raw data mainly refers to the data generated by on-site inspection and testing of the device samples, group samples and sealing point samples during the evaluation of the LDAR project. Including but not limited to:

[0144] a) Project establishment related data. The components and concentration (quality) of raw materials, additives, intermediate products and products processed by the controlled device, the components and concentration (quality) of materials contacted by equipment and pipelines, group codes, group location information, sealing point codes, sealing point location information, sealing point categories, and material forms;

[0145] b) Detection and repair related data. Instrument calibration, background detection, detection distance, detection speed, detection readings, instrument drift verification, leak seal point identification, delayed repair leak seal point identification and delayed repair reasons;

[0146] c) Operation and management related data. Detection task allocation, detection task download, detection path management, detection data upload, calibration management and system emission calculation;

[0147] (2) LDAR data preprocessing. There is a lot of noise information in the LDAR raw data, such as the net detection value <0μmol / mol or the material state is inconsistent with the national standard or the Ministry of Ecology and Environment specification or the sealing type is inconsistent with the national standard or the Ministry of Ecology and Environment document. Use methods such as data cleaning and sorting to further improve the quality of the data. Data preprocessing can unify the data generated by the LDAR operation of different devices, units or equipment, and can simplify the sparse attributes in the data. These attributes have little or no contribution to the evaluation or generate interference, thereby improving the accuracy of LDAR data mining;

[0148] (3) LDAR data mining and analysis. After the imported data is preprocessed, data mining technology can be used to mine and analyze the data. The embodiment of the present invention uses data mining technologies such as K-means algorithm, support vector machine, BP neural network, genetic algorithm, etc. to analyze the relationship between material form, sealing form, detection data, leakage frequency, and maintenance effect, obtain the hidden patterns in the data set, and form decision-making knowledge;

[0149] (4) Application of LDAR decision-making knowledge. Decision-making knowledge can predict the risk and development trend of sealing point leakage. Set a risk threshold. If the sealing point leakage risk exceeds the threshold, the warning indication and disposal suggestions for the detection and evaluation will be derived. At the same time, guide enterprises to carry out leakage risk-based detection, shorten the duration of leakage, and significantly reduce the unorganized emission of VOCs; in addition, it can also discover the adaptability level of certain equipment or seals to processes and environments, form an iterative optimization model for equipment and its seals and processes and environments, and improve the reliability of long-term operation of equipment.

[0150] Figure 5 is a structural diagram of a project review module provided by an optional implementation mode of the present invention, such as Figure 5 As shown, the project review module includes: a project establishment status submodule, a detection and repair status submodule, an operation and management status submodule, and an evaluation report generation submodule;

[0151] The project establishment submodule is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant; the detection and repair submodule is used to check whether the detection and repair related data of the LDAR project to be analyzed is compliant; the operation and management submodule is used to check whether the operation and management related data of the LDAR project to be analyzed is compliant; the evaluation report generation submodule is used to generate an evaluation report of the LDAR project to be analyzed based on the evaluation results. The details are as follows:

[0152] (1) Project establishment status submodule

[0153] The project establishment status submodule is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant, as follows:

[0154] a) Completeness of the implementation scope. Analyze the device operation process manual and process principle flow chart (PFD), analyze the components and concentration (quality) of the processing raw materials, additives, intermediate products and products of the device, and compare the VOCs component mass concentration of the materials with the thresholds set by relevant standards or specifications to determine the controlled devices that should be included in the LDAR; further, extract the pipeline instrumentation diagram (P&ID) from the controlled devices by simple random sampling, systematic sampling or stratified random sampling, analyze the components and concentration (quality) of the materials in contact with the equipment and pipelines, and compare them with the thresholds set by relevant standards or specifications to determine the controlled equipment and pipelines that should be included in the LDAR; extract sealing point samples from the sealing points of the equipment and pipelines by simple random sampling, systematic sampling or stratified random sampling, analyze the components and concentration (quality) of the materials in contact with the sealing point samples, and determine the controlled sealing points that should be included in the LDAR. Evaluate the misjudgment of the implementation scope of the LDAR and calculate the misjudgment rate of the controlled sealing points.

[0155]

[0156] Where: i - controlled misjudgment rate of type i sealing point; n io - The number of Class I controlled sealing points omitted during the project establishment process; n is - The number of uncontrolled sealing points of type i that were mistakenly included in the controlled scope during the project establishment process; N i - Total number of Class I controlled sealing points.

[0157] b) Standardization of basic data description of groups and sealing points. The combination of data analysis and on-site inspection of the device is used to evaluate whether the description of groups and sealing points is standardized, including but not limited to: uniqueness of group codes and sealing point codes; standardization of material forms (gas, light liquid or volatile organic liquid, heavy liquid); standardization of sealing point categories (pumps, compressors, agitators, valves, pressure relief equipment, sampling connection systems, open valves or open pipelines, flanges, connectors, and others); accuracy of group and sealing point location descriptions (including photos, P&ID and multiple filing modes); and accessibility of sealing points.

[0158] (2) Detection and repair submodule

[0159] The detection and repair situation submodule is used to check whether the relevant data of the detection and repair of the LDAR project to be analyzed is compliant. The relevant data of the detection and repair of the LDAR project includes: detection-related data and repair-related data; the details are as follows:

[0160] a) Check the compliance of relevant data

[0161] Assess the compliance of the following data: calibration of detection instruments (including standard gas type, concentration, expanded relative uncertainty, validity period, instrument model and number, indication error, calibration time, and calibration personnel), background detection (including detection time, detection concentration, detection position, detection instrument model and number, and detection personnel), detection distance (the distance between the sampling port of the hydrogen flame ionization detection instrument and the tested sealing point in the detection and repair on-site detection submodule), detection speed (the time difference between two adjacent sealing point detection readings or the detection speed of the sampling port of the hydrogen flame ionization gas leakage detection instrument based on the detection and repair on-site detection submodule moving on the surface of the tested sealing point), detection data (including sealing point coding, detection time, detection concentration, detection instrument model and number, and detection personnel), detection frequency (the time difference between two adjacent detections of the same sealing point), instrument drift verification (including standard gas type, concentration, expanded relative uncertainty, validity period, instrument model and number, instrument drift error, verification time, and verification personnel).

[0162] b) Repair relevant data compliance

[0163] Evaluate the compliance of the following data: first maintenance time and repair time of leaking sealing points, retest data (including sealing point code, retest time, retest concentration, retest instrument model and number, retest personnel), and reasons for delayed repair of leaking sealing points.

[0164] (3) LDAR operation and management submodule

[0165] The operation and management status submodule is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant. They are described as follows:

[0166] a) Compliance of operation-related data

[0167] Analyze the feasibility and compliance of processes such as group data upload and / or change, sealing point data upload and / or change, inspection task allocation, inspection task download, inspection path management, inspection data upload, calibration management, leak identification and emission calculation, maintenance task allocation, and repair record upload.

[0168] b) Suitability of management-related data

[0169] Relevant management data can be retrieved through the enterprise LDAR project operation platform to analyze the applicability of system LDAR regulations, system emission calculation methods, and pollutant emission permit thresholds.

[0170] (4) Evaluation report generation submodule

[0171] The evaluation report generation submodule is used to form an evaluation report of the LDAR project to be analyzed, including: evaluation overview, enterprise overview, LDAR project overview to be analyzed, evaluation method and process, and evaluation conclusion;

[0172] The evaluation overview includes: evaluation basis, evaluation scope, and evaluation procedures; the enterprise overview includes: main production processes, production capacity and / or processing capacity, and geographical location; the LDAR project overview to be analyzed includes: the number of controlled devices and operating conditions, the number of sealing points, the number of inaccessible points, the start time of the LDAR project to be analyzed, and the operating mode; the evaluation method and process include: evaluation start and completion dates, on-site sampling methods and results, testing instruments and operating procedures used for on-site inspections and tests, and data analysis and mining methods; the evaluation conclusions include: compliance of project establishment, compliance of inspection and repair, compliance of operation and management, and suggestions for project improvement.

[0173] Figure 6 is a flow chart of a LDAR evaluation method based on big data mining and analysis provided by one embodiment of the present invention, such as Figure 6As shown: In one embodiment provided by the present invention, a LDAR evaluation method based on big data mining analysis is also provided, and the method comprises:

[0174] Store LDAR raw data (including historical raw data and real-time raw data) in the data storage layer;

[0175] In response to user operations, analyzing and applying the data in the data storage layer, wherein the analyzing and applying includes data analysis and project review;

[0176] The data analysis is used to obtain the association between the raw data of the LDAR according to the user operation and form decision-making knowledge;

[0177] The project review is used to establish LDAR review projects based on the user operations, review the compliance of the review projects, and output an evaluation report.

[0178] In an optional embodiment, the data analysis includes the following sub-steps: LDAR data extraction sub-step, LDAR data pre-processing sub-step, LDAR data mining analysis sub-step and LDAR decision knowledge application sub-step;

[0179] The LDAR data extraction sub-step is used to extract the raw data to be analyzed from the data storage layer;

[0180] The LDAR data preprocessing sub-step is used to clean the raw data to be analyzed to obtain cleaned data;

[0181] The LDAR data mining and analysis sub-step is used to form decision-making knowledge based on the cleaned data and the data analysis algorithm configured by the user; and

[0182] The LDAR decision knowledge application sub-step is used to form a number of measures and suggestions based on the decision knowledge.

[0183] In an optional implementation, the project review includes: a LDAR project establishment review sub-step, a detection and maintenance review sub-step, a LDAR operation and management review sub-step, and an evaluation report generation sub-step;

[0184] The LDAR project establishment status review sub-step is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant;

[0185] The inspection and repair status review sub-step is used to check whether the inspection and repair related data of the LDAR project to be analyzed are compliant;

[0186] The LDAR operation and management status review sub-step is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant;

[0187] The evaluation report generation sub-step is used to generate an evaluation report for the LDAR project to be analyzed based on the inspection results.

[0188] In an optional implementation, the relevant data of the LDAR project establishment status review sub-step includes: controlled scope, basic data;

[0189] The controlled scope includes: the components and concentration (quality) of raw materials, additives, intermediate products and products processed by the controlled device, and the components and concentration (quality) of materials contacted by equipment and pipelines;

[0190] The basic data includes: group code, group location information, sealing point code, sealing point location information, sealing point category and material form;

[0191] In an optional implementation, the relevant data of the inspection and maintenance status review sub-step includes: inspection-related data and repair-related data;

[0192] The detection related data include: instrument calibration, background detection, detection distance, detection speed, detection data, detection frequency, and instrument drift verification;

[0193] The repair-related data include: the first maintenance time and repair time of the leaking sealing point, retest data and the reason for delayed repair of the leaking sealing point.

[0194] In an optional implementation, the relevant data of the LDAR operation and management status review sub-step includes: operation-related data, management-related data;

[0195] The operation-related data includes: group data upload and / or change, sealing point data upload and / or change, inspection task allocation, inspection task download, inspection path management, inspection data upload, calibration management, maintenance task allocation, and repair record upload;

[0196] The management-related data include: system LDAR regulations, system emission calculation methods, and emission permit thresholds;

[0197] In an optional implementation, the relevant contents of the evaluation report generation sub-step include: evaluation overview, enterprise overview, LDAR project overview to be analyzed, evaluation method and process, and evaluation conclusion;

[0198] The evaluation overview includes: evaluation basis, evaluation scope, and evaluation procedures;

[0199] The company overview includes: main production processes, production capacity and / or processing capabilities, and geographical location;

[0200] The overview of the LDAR project to be analyzed includes: the number of controlled devices and their operating conditions, the number of sealing points, the number of inaccessible points, the start time of the LDAR project to be analyzed, and the operating mode;

[0201] The evaluation method and process include: evaluation start and completion date, on-site sampling method and results, testing instruments and operation process used for on-site inspection and testing, and data analysis and mining methods;

[0202] The evaluation conclusions include: compliance of project establishment, compliance of detection and repair, compliance of operation and management, and suggestions for project improvement.

[0203] The method provided in the implementation manner here refers to the technical details of the aforementioned system and will not be repeated here.

[0204] In one embodiment of the present invention, a server is also provided, on which the LDAR evaluation system based on big data mining and analysis as described above is loaded. The server includes a processing unit and a storage system, and the processing unit is preferably a server group or a server group cluster, which mainly considers the load sharing and business response requirements under large data volume. It provides business response through network access. The storage system includes a physical medium for storing LDAR data and a media driver, and the currently commonly used physical medium is a disk array.

[0205] In one embodiment of the present invention, a machine-readable storage medium is also provided, on which instructions are stored, and when the machine-readable storage medium is run on a computer, the computer executes the aforementioned LDAR evaluation method based on big data mining analysis.

[0206] In this way, the implementation mode of the present invention adds LDAR big data mining, which can discover the degradation and leakage development trends of massive equipment seals, and at the same time provide positive reference for enterprises to optimize equipment selection, installation, operation and maintenance in the next step.

[0207] The optional embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all belong to the protection scope of the embodiments of the present invention.

[0208] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0209] Those skilled in the art will understand that all or part of the steps in the method for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a single-chip microcomputer, a chip or a processor (processor) perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0210] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A LDAR evaluation method based on big data mining and analysis, characterized in that: The method comprises: The data collection step is used to collect relevant data from the historical raw data of the LDAR project to be analyzed through the interface according to user operations, and store it in the data storage layer; On-site inspection and testing steps, for carrying out inspection and / or testing of devices, groups and sealing points extracted on-site according to user operations, and storing the generated relevant real-time raw data to the data storage layer through the interface; A data analysis step, for obtaining the association between the raw data of the LDAR according to user operations and forming decision-making knowledge; The project review step is used to establish the LDAR review project according to the user operation, review the compliance of the LDAR project, and output the evaluation report; the data collection step includes the following sub-steps: A project establishment data collection sub-step is used to collect project establishment related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer; A detection and repair data collection sub-step is used to collect detection and repair related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer; The operation and management data collection sub-step is used to collect operation and management related data from the historical raw data of the LDAR project to be analyzed, and store it in the data storage layer; the on-site inspection and detection step includes the following sub-steps: A field sampling sub-step for extracting devices, groups and sealing points from the LDAR items to be analyzed to form device samples, group samples and sealing point samples; The project establishment on-site inspection sub-step is used to inspect on-site whether the relevant data of the project establishment of the device sample, group sample and sealing point sample are consistent with the actual situation on site; The detection and repair on-site inspection sub-step is used to check on-site whether the related operations of the detection and repair of the sealing point sample are in compliance with regulations; Inspection and repair on-site inspection sub-step, for on-site inspection of the sealing point samples; The operation and management on-site inspection sub-step is used to conduct on-site inspection of the compliance of the actual operation of the LDAR on the sealing point sample; the data analysis step includes the following sub-steps: LDAR data extraction sub-step, used to extract the raw data to be analyzed from the data storage layer; The LDAR data preprocessing sub-step is used to clean the raw data to be analyzed to obtain cleaned data; LDAR data mining and analysis sub-step, for forming decision-making knowledge based on the cleaned data and the data analysis algorithm configured by the user; and The LDAR decision knowledge application sub-step is used to form a number of measures and suggestions based on the decision knowledge.

2. The method according to claim 1, characterized in that The project review steps include: The LDAR project establishment status review sub-step is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant; The inspection and repair status review sub-step is used to check whether the inspection and repair related data of the LDAR project to be analyzed are compliant; The LDAR operation and management status review sub-step is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant; The evaluation report generation sub-step is used to generate an evaluation report for the LDAR project to be analyzed based on the inspection results.

3. The method according to claim 2, characterized in that Project establishment related data of the LDAR project to be analyzed, including: controlled scope and basic data; The controlled scope includes: the components and concentrations of raw materials, additives, intermediate products and products processed by the controlled device, and the components and concentrations of materials contacted by equipment and pipelines; The basic data includes: group code, group location information, sealing point code, sealing point location information, sealing point category and material form.

4. The method according to claim 2, characterized in that: The detection and repair related data of the LDAR project to be analyzed include: detection related data and repair related data; The detection related data include: instrument calibration, background detection, detection distance, detection speed, detection data, detection frequency, and instrument drift verification; The repair-related data include: the first maintenance time and repair time of the leaking sealing point, retest data and the reason for delayed repair of the leaking sealing point.

5. The method according to claim 2, characterized in that: The operation and management related data include: operation related data and management related data; The operation-related data includes: group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification and emission calculation, maintenance task allocation, and repair record upload; The management-related data include: system LDAR regulations, system emission calculation methods, and pollutant emission permit thresholds.

6. The method according to claim 2, characterized in that The evaluation report of the LDAR project to be analyzed includes: evaluation overview, enterprise overview, overview of the LDAR project to be analyzed, evaluation method and process, and evaluation conclusion; The evaluation overview includes: evaluation basis, evaluation scope, and evaluation procedures; The company overview includes: main production processes, production capacity and / or processing capabilities, and geographical location; The overview of the LDAR project to be analyzed includes: the number of controlled devices and their operating conditions, the number of sealing points, and the number of inaccessible points; the start time and operating mode of the LDAR project to be analyzed; The evaluation method and process include: evaluation start and completion date, on-site sampling method and results, testing instruments and operation process used for on-site inspection and testing, and data analysis and mining methods; The evaluation conclusions include: compliance of project establishment, compliance of detection and repair, compliance of operation and management, and suggestions for project improvement.

7. A LDAR evaluation system based on big data mining and analysis, used to implement the LDAR evaluation method based on big data mining and analysis as claimed in any one of claims 1 to 6, characterized in that: The system comprises: The data access layer is used to provide the original data of the LDAR project to be analyzed; the original data includes historical original data and real-time original data; A data storage layer, used for storing the raw data of the LDAR project to be analyzed; The data application layer is used to provide data analysis applications for the data storage layer; the data access layer includes a data acquisition module, an on-site inspection and detection module, and an interface module; The data acquisition module is used to respond to the user's data acquisition operation, extract data from the historical raw data of the LDAR project to be analyzed, and store it in the data storage layer; The on-site inspection and detection module is used to respond to the on-site inspection and detection operation of the user, to inspect and detect the extracted devices, groups and sealing points on-site, and to store the generated real-time raw data into the data storage layer; The interface module is used to respond to the reading and storage operations of user data, connect the data acquisition module with the historical raw data of the LDAR project to be analyzed and the data storage layer respectively; at the same time, connect the on-site inspection and detection module with the data storage layer to complete the original data transmission; the data application layer includes a data analysis module and a project review module; The data analysis module is used to respond to the data analysis operation of the user to obtain the association between the original data of the LDAR project to be analyzed and form decision-making knowledge; The project review module is used to establish the review of the LDAR project, evaluate the compliance of the LDAR project, and output the evaluation report; the data collection module includes: a project establishment data collection submodule, a detection and repair data collection submodule, and an operation and management data collection submodule; The project establishment data acquisition submodule is used to collect project establishment related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer; The detection and repair data acquisition submodule is used to collect detection and repair related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer; The operation and management data acquisition submodule is used to collect operation and management related data from the historical original data of the LDAR project to be analyzed, and store it in the data storage layer; The data analysis module includes: an LDAR data extraction submodule, an LDAR data preprocessing submodule, an LDAR data mining and analysis submodule, and an LDAR decision-making knowledge application submodule; The LDAR data extraction submodule is used to extract the original data to be analyzed from the data storage layer; the LDAR data preprocessing submodule is used to clean the original data to be analyzed to obtain cleaned data; the LDAR data mining and analysis submodule is used to form decision knowledge based on the cleaned data and the data analysis algorithm configured by the user; and the LDAR decision knowledge application submodule is used to form a number of measures and suggestions based on the decision knowledge.

8. The system according to claim 7, characterized in that The on-site inspection and detection module includes: an on-site sampling submodule, a project establishment on-site inspection submodule, a detection and repair on-site inspection submodule, a detection and repair on-site detection submodule, and an operation and management on-site inspection submodule; The field sampling submodule is used to extract devices, groups and sealing points from the LDAR items to be analyzed to form device samples, group samples and sealing point samples; The project establishment on-site inspection submodule is used to inspect on-site the consistency between the relevant data of the project establishment of the device samples, group samples and sealing point samples and the actual situation on site; The detection and repair on-site inspection submodule is used to inspect the compliance of the detection and repair related operations of the sealing point samples on-site; The detection and repair on-site detection submodule is used for on-site detection of the sealing point samples; The operation and management on-site inspection submodule is used for on-site inspection of the actual operation of LDAR on the sealing point samples.

9. The system according to claim 8, characterized in that The interface module comprises: A historical original data transmission interface submodule, connected to the data acquisition module, the data acquisition module accesses and reads the historical original database of the LDAR project to be analyzed through the historical original data transmission interface submodule, and stores the relevant data in the data storage layer; The project establishment on-site inspection data transmission interface submodule is connected to the project establishment on-site inspection submodule, and the relevant real-time data generated by the project establishment on-site inspection submodule is stored in the data storage layer through the project establishment on-site inspection data transmission interface submodule; A detection and repair on-site inspection data transmission interface submodule, connected to the detection and repair on-site inspection submodule, and the relevant real-time data generated by the detection and repair on-site inspection submodule is stored in the data storage layer through the detection and repair on-site inspection data transmission interface submodule; A detection and repair on-site detection data transmission interface submodule, connected to the detection and repair on-site detection submodule, and the relevant real-time data generated by the detection and repair on-site detection submodule is transmitted to the data storage layer through the detection and repair on-site detection data transmission interface submodule; The operation and management on-site inspection data transmission interface submodule is connected to the operation and management on-site inspection submodule, and the relevant real-time data of the operation and management on-site inspection submodule is transmitted to the data storage layer through the operation and management on-site inspection data transmission interface submodule.

10. The system according to claim 7, characterized in that The project review module includes: a project establishment status submodule, a detection and repair status submodule, an operation and management status submodule and an evaluation report generation submodule; The project establishment status submodule is used to check whether the project establishment related data of the LDAR project to be analyzed is compliant; The detection and repair status submodule is used to check whether the detection and repair related data of the LDAR project to be analyzed are compliant; The operation and management status submodule is used to check whether the operation and management related data of the LDAR project to be analyzed are compliant; The evaluation report generation submodule is used to generate an evaluation report for the LDAR project to be analyzed according to the evaluation results.

11. The system according to claim 10, characterized in that The project establishment status submodule is used to detect the project establishment related data of the LDAR project to be analyzed, and the project establishment related data includes: controlled scope and basic data; The controlled scope includes: the components and concentrations of raw materials, additives, intermediate products and products processed by the controlled device, and the components and concentrations of materials contacted by equipment and pipelines; The basic data includes: group code, group location information, sealing point code, sealing point location information, sealing point category and material form.

12. The system according to claim 10, characterized in that The detection and repair related data include: detection related data and repair related data; The detection related data include: instrument calibration, background detection, detection distance, detection speed, detection data, detection frequency, and instrument drift verification; The repair-related data include: the first maintenance time and repair time of the leaking sealing point, retest data and the reason for delayed repair of the leaking sealing point.

13. The system according to claim 10, characterized in that The operation and management related data include: operation related data and management related data; The operation-related data includes: group data upload and / or change, sealing point data upload and / or change, detection task allocation, detection task download, detection path management, detection data upload, calibration management, leak identification and emission calculation, maintenance task allocation and repair record upload; The management-related data include: system LDAR regulations, system emission calculation methods and pollution discharge permit thresholds.

14. The system according to claim 10, characterized in that The evaluation report of the LDAR project to be analyzed, including: evaluation overview, enterprise overview, overview of the LDAR project to be analyzed, evaluation method and process, and evaluation conclusion; The evaluation overview includes: evaluation basis, evaluation scope, and evaluation procedures; The company overview includes: main production processes, production capacity and / or processing capabilities, and geographical location; The overview of the LDAR project to be analyzed includes: the number of controlled devices and their operating conditions, the number of sealing points, the number of inaccessible points, the start time of the LDAR project to be analyzed, and the operating mode; The evaluation method and process include: evaluation start and completion date, on-site sampling method and results, testing instruments and operation process used for on-site inspection and testing, and data analysis and mining methods; The evaluation conclusions include: compliance of project establishment, compliance of detection and repair, compliance of operation and management, and suggestions for project improvement.

15. A server, characterized in that: The server is loaded with the LDAR evaluation system based on big data mining and analysis as described in any one of claims 7 to 14.

16. A machine-readable storage medium, characterized in that: The machine-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the LDAR evaluation method based on big data mining analysis as described in any one of claims 1 to 6.

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