PI database automatic point building method and device, storage medium and electronic equipment

Abstract

This disclosure relates to a method, apparatus, storage medium, and electronic device for automatically building points in a PI database, which can efficiently and systematically build points automatically. The method includes: responding to user operations on the point building interface, generating data information corresponding to the data to be built, the data information including the point number, description, unit, and type of the data to be built; determining whether the data to be built is a duplicate point based on the data information; if the data to be built is not a duplicate point, configuring data points corresponding to the data to be built according to preset configuration parameters, the preset configuration parameters including basic data, data source, and source site; and storing the data points in the PI database if the data points meet the preset configuration conditions.

Description

Technical Field

[0001] This disclosure relates to the field of data management technology, and more specifically, to a method, apparatus, storage medium, and electronic device for automatically creating points in a PI database. Background Technology

[0002] PI databases are long-term online storage systems for all production data in a factory, enabling rapid and efficient data acquisition, storage, and display. They have been widely used in petroleum information technology infrastructure, such as in oil and gas fields. However, with the increasing informatization of oil and gas fields, various types of production data have emerged during exploration, development, production, transportation, and sales. The uniqueness and standardization of the point numbers and descriptions for these various data types are particularly important.

[0003] A 17-point naming rule was developed for real-time production data points in oil and gas fields, including the composition of the points and the naming specifications for each component. However, the point numbers and descriptions for real-time production data are manually compiled according to the naming rules. Verification of the standardization, completeness, and uniqueness of the point numbers and descriptions cannot be digitized and must be done manually, one by one. Over time, this has led to a large amount of duplicate, non-standard, or erroneous point numbers or descriptions in the PI database. This not only results in inaccurate data analysis results in the PI database but also increases the difficulty of data governance. Summary of the Invention

[0004] The purpose of this disclosure is to provide a method, apparatus, storage medium, and electronic device for automatically constructing PI databases, in order to solve the aforementioned technical problems.

[0005] To achieve the above objectives, firstly, this disclosure provides a method for automatically constructing a PI database, the method comprising:

[0006] In response to the user's operation on the point creation interface, data information of the corresponding point data to be created is generated, including the point number, description, unit and type of the point data to be created;

[0007] Based on the data information, determine whether the data for the point to be built is a duplicate point;

[0008] If there are no duplicate data points in the data to be built, the data points corresponding to the data to be built are configured according to the preset configuration parameters, which include basic data, data source, and source site.

[0009] If the data point meets the preset configuration conditions, the data point will be stored in the PI database.

[0010] Optionally, the method further includes:

[0011] Compare the data information corresponding to the data point with the data information of the point to be built;

[0012] If the data information corresponding to the data point is the same as the data information of the data to be built, determine whether the data source of the data point is consistent with the data source of the data to be built.

[0013] If the data source of the data point is consistent with the data source corresponding to the data to be built, it is determined that the data point meets the preset configuration conditions;

[0014] If the data source of the data point is inconsistent with the data source corresponding to the data to be built, the data point is determined to be abnormal and an early warning is issued.

[0015] Optionally, the method further includes:

[0016] The data information corresponding to the data point is compared with the data information of the point to be built to obtain the comparison result;

[0017] If the comparison result shows that the data information corresponding to the data point is the same as the data information of the point to be built, then determine whether the data point should be refreshed based on the timestamp of the data point.

[0018] If the data point is not refreshed, it is determined that the data point meets the preset configuration conditions;

[0019] If the data point is refreshed, an anomaly is identified and an alert is issued.

[0020] Optionally, determining whether the data to be built is a duplicate point based on the data information includes:

[0021] Based on the point number, traverse the storage point numbers in the PI database to determine whether the point number is duplicated with the storage point number in the PI database;

[0022] If the point number is not duplicated with the stored point number in the PI database, it is determined that the data of the point to be built has no duplicate points.

[0023] Optionally, determining whether the data to be built is a duplicate point based on the data information includes:

[0024] Semantic analysis is performed on the description and all stored descriptions in the PI database to obtain the similarity value between the description and all stored descriptions in the PI database.

[0025] If all the similarity values ​​are less than the similarity threshold, it is determined that the data to be built has no duplicate points.

[0026] Optionally, the step of configuring data points corresponding to the data to be built according to preset configuration parameters, wherein the preset configuration parameters include basic data, data source, and source site, including:

[0027] Based on the basic data, configure the decimal places and acquisition interface corresponding to the data of the points to be built;

[0028] Configure the data address corresponding to the data of the point to be built based on the data source;

[0029] Configure the data collection type for the points to be built based on the source site;

[0030] Data points corresponding to the data to be built are generated based on the number of decimal places, the acquisition interface, the data address, and the acquisition type.

[0031] Optionally, the step of generating data information corresponding to the data to be built in response to the user's operation on the point creation interface includes:

[0032] In response to the user's operation of the virtual configuration tool on the site construction interface, data information corresponding to the site to be constructed is generated. The virtual configuration tool includes a station virtual configuration tool, a regional virtual configuration tool, and a signal function virtual configuration tool.

[0033] Secondly, this disclosure provides an automatic PI database point creation device, the device comprising:

[0034] The response module is configured to respond to user operations on the point creation interface and generate corresponding data information for the point to be created, including the point number, description, unit, and type of the point to be created.

[0035] The judgment module is configured to determine whether the data to be built is a duplicate point based on the data information.

[0036] The data point creation module is configured to configure data points corresponding to the data to be created according to preset configuration parameters, provided that there are no duplicate data points in the data to be created. The preset configuration parameters include basic data, data source, and source site.

[0037] The storage module is configured to store the data points into the PI database when the data points meet preset configuration conditions.

[0038] Thirdly, this disclosure provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described automatic PI database point construction method.

[0039] Fourthly, this disclosure provides an electronic device, comprising:

[0040] A memory on which computer programs are stored;

[0041] A processor is configured to execute the computer program in the memory to implement the steps of the above-described automatic point construction method for the PI database.

[0042] Through the above technical solution, this disclosure responds to the user's operation on the point construction interface, generates data information of the corresponding point data to be constructed, and, if it is determined from the data information that there are no duplicate points to be constructed, configures the data points of the point data to be constructed according to the preset configuration parameters. If the data points meet the preset configuration conditions, the data points are stored in the PI database, which standardizes the data information of the point data to be constructed, realizes automatic point construction in the PI database, reduces the amount of manual work, shortens the point construction time and point construction cost.

[0043] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0044] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0045] Figure 1 This is a flowchart illustrating an automatic point creation method for a PI database according to an exemplary embodiment of the present disclosure.

[0046] Figure 2 This is a schematic diagram illustrating the database label naming rules of an automatic point creation method for a PI database according to an exemplary embodiment of the present disclosure.

[0047] Figure 3 This is a functional diagram illustrating an automatic point creation method for a PI database according to an exemplary embodiment of the present disclosure.

[0048] Figure 4 This is another flowchart illustrating an automatic point creation method for a PI database according to an exemplary embodiment of the present disclosure.

[0049] Figure 5 This is a block diagram illustrating an automatic point creation device for a PI database according to exemplary embodiments of the present disclosure.

[0050] Figure 6 This is a block diagram illustrating an electronic device according to exemplary embodiments of the present disclosure. Detailed Implementation

[0051] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0052] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with authorization from the owner of the relevant device.

[0053] As mentioned in the background technology, the point numbers and descriptions for real-time production data in oil and gas fields are manually compiled according to naming rules. The verification of the standardization, completeness, and uniqueness of the point numbers and descriptions for real-time production data cannot be done through information technology, and can only be checked manually one by one.

[0054] Currently, there are two main ways to add points to the PI database: the first is to add points one by one using PI SMT (System Management Tools); the second is to manually import points from an Excel spreadsheet. The first method is less efficient, while the second method is prone to errors when importing into the real-time PI database due to non-standard data in the spreadsheet.

[0055] In view of this, this disclosure provides a method, apparatus, storage medium, and electronic device for automatically creating data points in a PI database. The method automatically generates data information and creates data points based on the data to be created, standardizes the naming of data points, avoids duplicate data point creation, improves the screening efficiency of data point naming, and ensures the consistency and reliability of data in the PI database.

[0056] Figure 1 This is a flowchart illustrating an automatic point-building method for a PI database according to an exemplary embodiment of this disclosure. See also... Figure 1 The method includes the following steps:

[0057] In step S101, in response to the user's operation on the point creation interface, data information corresponding to the point data to be created is generated. The data information includes the point number, description, unit, and type of the point data to be created.

[0058] Specifically, the data for the sites to be built can be real-time production data of oil and gas fields.

[0059] In step S102, it is determined whether the data to be built is a duplicate data point based on the data information.

[0060] Specifically, by using data information to determine whether the data to be built is duplicated, duplicate data point creation can be avoided, thus preventing the PI database from storing the same data point information for the same production implementation data repeatedly.

[0061] In step S103, if there are no duplicate data points to be built, the data points of the corresponding data points to be built are configured according to the preset configuration parameters, which include basic data, data source, and source site.

[0062] Specifically, the automatic point creation in the PI database involves the configuration of three parts of data: basic data, data source, and source site.

[0063] In step S104, if the data points meet the preset configuration conditions, the data points are stored in the PI database.

[0064] Specifically, refer to Figure 2 Each real-time production data point that needs to be established includes data information such as point number, description, unit, and type. Each parameter is determined according to... Figure 2 The "Database Tag Naming Implementation Rules" shown generate data information.

[0065] Specifically, refer to Figure 2 The point number consists of 8 groups of 17 characters (including letters and numbers): station (well station) type, unit number, station (single well) number, signal function, signal function extension, station area code, instrument loop number, and extension number. The description mainly includes the unit name, production unit name, station (well station) name, station area name, signal function name, and instrument loop number. The unit and data type are determined by the signal function.

[0066] Specifically, according to Figure 2 The “Database Tag Naming Implementation Rules” shown above sort out real-time production data and determine 6 of the 8 sets of codes for generating point numbers: station (well) type, unit number, station (single well) number, signal function, signal function extension and station area code, and point numbers can be generated automatically.

[0067] This disclosure responds to user operations on the data point creation interface, generates corresponding data information for the data points to be created, standardizes the naming rules for data points, and, if it is determined from the data information that there are no duplicate data points to be created, configures the data points for the data points to be created according to preset configuration parameters, avoiding duplicate data point creation and improving the screening efficiency of data point naming. If the data point meets the preset configuration conditions, the data point is stored in the PI database, realizing automatic data point creation in the PI database, ensuring the consistency and reliability of data in the PI database, reducing manual workload, shortening data point creation time and cost.

[0068] To help those skilled in the art better understand the automatic PI database construction method provided in this disclosure, the above method is illustrated in detail below.

[0069] In one feasible embodiment, the method further includes:

[0070] Compare the data information corresponding to the data points with the data information of the points to be built;

[0071] If the data information corresponding to the data point is the same as the data information of the data point to be built, determine whether the data source of the data point is consistent with the data source of the data point to be built.

[0072] If the data source of the data point is consistent with the data source of the data to be built, it is determined that the data point meets the preset configuration conditions;

[0073] If the data source of a data point is inconsistent with the data source of the data to be built, the data point is identified as abnormal and an alert is issued.

[0074] Specifically, the point number, description, and unit corresponding to the data point are compared for consistency with those of the data to be created. If the point number, description, and unit are all consistent, it is further determined whether the source data of the data point is consistent with the data source corresponding to the data to be created. If the source data is consistent, the data point is successfully created. If the source data is inconsistent, it is also necessary to check whether the attributes of the source data are set incorrectly.

[0075] For example, the point number, description, and unit corresponding to the newly created data point in the PI database are compared with the point number, description, and unit corresponding to the data to be created. If the point number, description, and unit are all consistent, it is further determined whether the source data of the newly created data point is consistent with the source data of the data to be created. If the source data is consistent, the data point is successfully created; otherwise, it is necessary to check whether the source attributes are set incorrectly.

[0076] This disclosure verifies the data point creation results by using data information and data source, thereby proactively issuing warnings in the event of data point creation failure or data point anomalies, avoiding omissions or errors in data point creation, and ensuring the reliability of data points in the PI database.

[0077] In one feasible embodiment, the method further includes:

[0078] The data information corresponding to the data points is compared with the data information of the points to be built, and the comparison results are obtained.

[0079] If the comparison result shows that the data information corresponding to the data point is the same as the data information of the point to be built, determine whether the data point should be refreshed based on the timestamp of the data point.

[0080] If the data points are not refreshed, determine that the data points meet the preset configuration conditions;

[0081] When data points are refreshed, identify data point anomalies and issue an alert.

[0082] Specifically, the point number, description, and unit corresponding to the data point are compared with the point number, description, and unit corresponding to the data to be created. If the point number, description, and unit are consistent, the data point is further determined based on the timestamp of the data point. If the data point is refreshed, a new data point needs to be created.

[0083] For example, the point number, description, and unit corresponding to the newly created data point in the PI database are compared with the point number, description, and unit corresponding to the data to be created. If the point number, description, and unit are all consistent, the timestamp of the newly created data point is used to determine whether the newly created data point should be refreshed. If the data point is refreshed, the new data point is created.

[0084] For example, if the source value of a pressure data point with the number "A213210PI00005010" is 3.54 MPa, and the value of the data point automatically added in the PI database is also 3.54 MPa, then the data point has been added correctly. If they are inconsistent, it means that the parameter settings of the data point added in the PI database are incorrect and need to be corrected before adding the data point.

[0085] This disclosure verifies the data point creation results by using data information and timestamps, thereby providing proactive warnings in the event of data point creation failure or data point anomalies, avoiding omissions or errors in data point creation, and ensuring the reliability of data points in the PI database.

[0086] In a feasible embodiment, in step S102, determining whether the data to be built is a duplicate data point based on the data information includes:

[0087] Iterate through the storage point numbers in the PI database based on the point number to determine if there are any duplicate point numbers in the PI database.

[0088] If the point number is not duplicated with the stored point number in the PI database, it is determined that the data to be created for the point is not duplicated.

[0089] Specifically, the point number of the data to be built is compared one by one with all the point numbers stored in the PI database to avoid duplicate point construction.

[0090] In a feasible embodiment, in step S102, determining whether the data to be built is a duplicate data point based on the data information includes:

[0091] Semantic analysis was performed on the description and all stored descriptions in the PI database to obtain the similarity values ​​between the description and all stored descriptions in the PI database.

[0092] If all similarity values ​​are less than the similarity threshold, it is determined that there are no duplicate data points in the data to be constructed.

[0093] The similarity threshold can be preset according to the point construction requirements. In this disclosure, the similarity threshold is set to 98%.

[0094] For example, semantic analysis is performed on the description corresponding to the data to be constructed and all descriptions stored in the PI database. If the similarity between the description corresponding to the data to be constructed and the data to be constructed in the PI database is greater than or equal to 98%, it is determined that the description already exists and a duplicate construction point is indicated. If the similarity between all descriptions in the PI database and the description corresponding to the data to be constructed is less than 98%, it is determined that the data to be constructed is not a duplicate construction point.

[0095] This disclosure performs repeatability checks on data points by using point numbers and / or descriptions, thereby avoiding duplicate point construction, saving point construction costs, and reducing point construction time.

[0096] In a feasible embodiment, in step S103, data points corresponding to the data to be built are configured according to preset configuration parameters. The preset configuration parameters include basic data, data source, and source site, including:

[0097] Based on the basic data, configure the decimal places and data acquisition interface for the corresponding data points to be built;

[0098] Configure the data address of the corresponding point data to be built based on the data source;

[0099] Configure the data collection type for the corresponding points to be built based on the source site;

[0100] Data points corresponding to the data to be built are generated based on the number of decimal places, the acquisition interface, the data address, and the acquisition type.

[0101] Specifically, determine the data type of the data to be built, and configure the corresponding data points according to the preset configuration parameters. The data to be built includes two data types: analog quantity and state quantity. When the data to be built is a state quantity, it is also necessary to configure the representation information of the two states of the data to be built according to the basic data.

[0102] For example, when the data to be built is an analog quantity, the decimal places and acquisition interface (Pointsource) of the data to be built are configured according to the basic data; the data address (Instrumenttag) of the data to be built is configured according to the data source; the acquisition type (Llocation3) of the data to be built is configured according to the source site; and the data points corresponding to the data to be built are generated according to the decimal places, Pointsource, Instrumenttag, and Location3.

[0103] When the data to be built is a state variable, the decimal places, acquisition interface (Pointsource), and representation information (Pointtypex) of the data to be built are configured according to the basic data. According to the data source, the data address (Instrumenttag) of the data to be built is configured. According to the source site, the acquisition type (Location3) of the data to be built is configured. Data points corresponding to the data to be built are generated according to the decimal places, Pointsource, Pointtypex, Instrumenttag, and Location3.

[0104] In a feasible embodiment, in step S101, in response to the user's operation on the point creation interface, data information corresponding to the point to be created is generated, including:

[0105] In response to the user's operation of the virtual configuration tool on the site construction interface, the corresponding data information of the site to be constructed is generated. The virtual configuration tool includes the station virtual configuration tool, the area virtual configuration tool, and the signal function virtual configuration tool.

[0106] Specifically, the system maps six sets of basic data—station (well) type, unit number, station (single well) number, signal function, signal function extension, and station area code—to the station, area, and signal function where the data is located. Responding to user operations using the virtual configuration tools on the data point creation interface—including the area virtual configuration tool and the signal function virtual configuration tool—the system determines the station, area, and signal function of the data to be created. Based on the self-numbering of the instrument loop filled in on-site (with the extension code defaulting to zero), the system automatically generates the corresponding point number, description, unit, and data type. This data is then compared with existing data points in the PI database to achieve automatic control of the data's repeatability, standardization, and completeness.

[0107] For details, see Figure 3 The point creation interface mainly consists of two parts:

[0108] The first part is the dot tool, which can manage and set various parameters in the naming of data information, as well as automatically generate dot numbers and descriptions and perform duplicate checks. The description check uses intelligent semantic analysis to perform similarity checks with existing dot number descriptions in the PI library. When the similarity with existing dot number descriptions reaches 98%, a duplicate is indicated.

[0109] The second part is the point creation tool, which enables one-click point creation. After manually setting the data information of the data to be created, the point can be created automatically. After the point is created, the creation results are evaluated. The tool judges and analyzes the refresh status of each data point and the consistency with the source data value, and actively reminds users of the points that have failed to be created or have problems.

[0110] For example, see Figure 4 The automatic creation of PI database points includes the following steps:

[0111] First, the six sets of basic data—station (well) type, unit number, station (single well) number, signal function, signal function extension, and station area code—are mapped to the station, area, and signal function where the data is located. Then, in response to the user's operation of the virtual configuration tool on the point construction interface, the station, area, and signal function of the data to be constructed are determined, and the data information is automatically generated. The data information includes 17 point numbers, descriptions, units, and data types.

[0112] Secondly, two repetition rules are used to check for duplicate point creation and avoid redundant additions. The first is to directly compare the point numbers of the generated data information with the point numbers of existing data in the PI database to see if they are duplicates. The second is to use intelligent semantic analysis to compare the description of the generated data information with the description of existing data in the PI database to see if the similarity is too high. If the similarity is greater than 98%, it is determined that the data description already exists and a prompt is given.

[0113] Secondly, a data source determination process is performed. The generated data points are identified by their data source. Only after confirming the existence of a data source can points be automatically added to the PI database; otherwise, point addition is not allowed. Data information can be generated before the data source exists. If the data source does not exist, the added points will have no data values ​​and are considered invalid.

[0114] Secondly, the PI database allows for one-click point creation, automatically adding data points based on pre-defined information, with different parameter settings for state and analog quantities. For analog quantities, settings include the number of decimal places, pointsource (the acquisition interface to which the data belongs), instrumenttag (data address), and location3 (defining the acquisition type of the point). For state quantities, settings include the number of decimal places, pointsource (the acquisition interface to which the data belongs), instrumenttag (data address), location3 (defining the acquisition type of the point), and Pointtypex (representation information for the two states).

[0115] Finally, the data point creation results are verified. The verification process consists of two steps. The first step is to check whether the data points added to the PI database are consistent with the generated data information, including the data point number, description, and unit. The second step is to check whether the data source of the data points added to the PI database is consistent with the data source of the data to be created, or whether the data values ​​added to the PI database are being refreshed.

[0116] This disclosure responds to user operations on the data point creation interface, generating corresponding data information for the data points to be created, standardizing the naming rules for data points, and configuring the data points according to preset configuration parameters after confirming that there are no duplicate data points based on the data information. This avoids duplicate data point creation and improves the efficiency of data point naming screening. If the data point meets the preset configuration conditions, it is stored in the PI database. While ensuring the normal storage of data points, it also ensures that data points can be updated normally in real time, assisting in subsequent intelligent analysis, problem diagnosis, and localization of data quality. This reduces the need for maintenance personnel to screen and efficiently handle data point naming, ensuring the consistency and reliability of data in the PI database, reducing manual workload, shortening data point creation time, and reducing costs.

[0117] Based on the same inventive concept, this disclosure also provides an automatic PI database point creation device 500, see [link to relevant documentation]. Figure 5 The device 500 includes a response module 501, a judgment module 502, a point establishment module 503, and a storage module 504.

[0118] The response module 501 is configured to respond to the user's operation on the point creation interface and generate data information corresponding to the point data to be created. The data information includes the point number, description, unit and type of the point data to be created.

[0119] The judgment module 502 is configured to determine whether the data to be built is a duplicate point based on the data information.

[0120] The data point creation module 503 is configured to configure the corresponding data points of the data to be created according to preset configuration parameters when there are no duplicate data points in the data to be created. The preset configuration parameters include basic data, data source, and source site.

[0121] Storage module 504 is configured to store data points into the PI database when the data points meet preset configuration conditions.

[0122] This disclosure responds to user operations on the data point creation interface, generating corresponding data information for the data points to be created, standardizing the naming rules for data points, and configuring the data points according to preset configuration parameters after confirming that there are no duplicate data points based on the data information. This avoids duplicate data point creation and improves the efficiency of data point naming screening. If the data point meets the preset configuration conditions, it is stored in the PI database. While ensuring the normal storage of data points, it also ensures that data points can be updated normally in real time, assisting in subsequent intelligent analysis, problem diagnosis, and localization of data quality. This reduces the need for maintenance personnel to screen and efficiently handle data point naming, ensuring the consistency and reliability of data in the PI database, reducing manual workload, shortening data point creation time, and reducing costs.

[0123] Furthermore, the judgment module 502 is also configured to compare the data information corresponding to the data point with the data information of the point to be built;

[0124] If the data information corresponding to the data point is the same as the data information of the data point to be built, determine whether the data source of the data point is consistent with the data source of the data point to be built.

[0125] If the data source of the data point is consistent with the data source of the data to be built, it is determined that the data point meets the preset configuration conditions;

[0126] If the data source of a data point is inconsistent with the data source of the data to be built, the data point is identified as abnormal and an alert is issued.

[0127] Furthermore, the judgment module 502 is also configured to compare the data information corresponding to the data point with the data information of the point to be built, and obtain the comparison result;

[0128] If the comparison result shows that the data information corresponding to the data point is the same as the data information of the point to be built, determine whether the data point should be refreshed based on the timestamp of the data point.

[0129] If the data points are not refreshed, determine that the data points meet the preset configuration conditions;

[0130] When data points are refreshed, identify data point anomalies and issue an alert.

[0131] Furthermore, the judgment module 502 is configured to traverse the stored point numbers in the PI database based on the point number to determine whether the point number is duplicated with the stored point number in the PI database.

[0132] If the point number is not duplicated with the stored point number in the PI database, it is determined that the data to be created for the point is not duplicated.

[0133] Furthermore, the judgment module 502 is also configured to perform semantic analysis on the description and all stored descriptions in the PI database respectively, and obtain the similarity value between the description and all stored descriptions in the PI database.

[0134] If all similarity values ​​are less than the similarity threshold, it is determined that there are no duplicate data points in the data to be constructed.

[0135] Furthermore, the point establishment module is configured to configure the number of decimal places and the acquisition interface for the corresponding point data to be established based on the basic data;

[0136] Configure the data address of the corresponding point data to be built based on the data source;

[0137] Configure the data collection type for the corresponding points to be built based on the source site;

[0138] Data points corresponding to the data to be built are generated based on the number of decimal places, the acquisition interface, the data address, and the acquisition type.

[0139] Furthermore, the response module 501 is configured to respond to the user's operation of the virtual configuration tool on the point construction interface and generate data information corresponding to the point to be constructed. The virtual configuration tool includes a station virtual configuration tool, a regional virtual configuration tool, and a signal function virtual configuration tool.

[0140] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0141] Based on the same inventive concept, this disclosure also provides an electronic device, comprising:

[0142] A memory on which computer programs are stored;

[0143] A processor is configured to execute the computer program in the memory to implement the steps of the above-described automatic point construction method for the PI database.

[0144] Figure 6 This is a block diagram illustrating an electronic device 600 according to an exemplary embodiment. For example... Figure 6As shown, the electronic device 600 may include a processor 601 and a memory 602. The electronic device 600 may also include one or more of a multimedia component 603, an input / output (I / O) interface 604, and a communication component 605.

[0145] The processor 601 controls the overall operation of the electronic device 600 to complete all or part of the steps in the aforementioned automatic PI database point construction method. The memory 602 stores various types of data to support the operation of the electronic device 600. This data may include, for example, instructions for any application or method operating on the electronic device 600, and application-related data. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 603 may include a screen and audio components. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 602 or transmitted via communication component 605. The audio component also includes at least one speaker for outputting audio signals. I / O interface 604 provides an interface between processor 601 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 605 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0146] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described automatic point construction method for the PI database.

[0147] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described automatic PI database construction method. For example, the computer-readable storage medium may be the memory 602 including the program instructions, which may be executed by the processor 601 of the electronic device 600 to complete the above-described automatic PI database construction method.

[0148] In another exemplary embodiment, a computer program product is also provided, which includes a computer program executable by a programmable device, the computer program having a code portion for performing the above-described automatic PI database point construction method when executed by the programmable device.

[0149] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0150] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0151] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for automatically constructing PI database points, characterized in that, The method includes: In response to the user's operation on the point creation interface, data information of the corresponding point to be created is generated, including the point number, description, unit and type of the point to be created; Based on the data information, determine whether the data for the point to be built is a duplicate point; If there are no duplicate data points in the data to be built, the data points corresponding to the data to be built are configured according to the preset configuration parameters, which include basic data, data source, and source site. If the data point meets the preset configuration conditions, the data point will be stored in the PI database; The method further includes: Compare the data information corresponding to the data point with the data information of the point to be built; If the data information corresponding to the data point is the same as the data information of the data to be built, determine whether the data source of the data point is consistent with the data source of the data to be built. If the data source of the data point is consistent with the data source of the data to be built, it is determined that the data point meets the preset configuration conditions; If the data source of the data point is inconsistent with the data source corresponding to the data of the point to be built, the data point is determined to be abnormal and an early warning is issued; The step of determining whether the data to be built is a duplicate point based on the data information includes: Based on the point number, traverse the storage point numbers in the PI database to determine whether the point number is duplicated with the storage point number in the PI database; If the point number does not duplicate the stored point number in the PI database, it is determined that the data of the point to be built has no duplicate points. The step of determining whether the data to be built is a duplicate point based on the data information includes: Semantic analysis is performed on the description and all stored descriptions in the PI database to obtain the similarity value between the description and all stored descriptions in the PI database. If all the similarity values ​​are less than the similarity threshold, it is determined that the data to be built has no duplicate points.

2. The method for automatically constructing PI database points according to claim 1, characterized in that, The method further includes: The data information corresponding to the data point is compared with the data information of the point to be built to obtain the comparison result; If the comparison result shows that the data information corresponding to the data point is the same as the data information of the point to be built, it is determined whether the data point should be refreshed based on the timestamp of the data point. If the data point is not refreshed, it is determined that the data point meets the preset configuration conditions; If the data point is refreshed, an anomaly is identified and an alert is issued.

3. The method for automatically constructing PI database points according to claim 1 or 2, characterized in that, The step of configuring data points corresponding to the data to be built according to preset configuration parameters, wherein the preset configuration parameters include basic data, data source, and source site, including: Based on the basic data, configure the decimal places and acquisition interface corresponding to the data of the points to be built; Configure the data address corresponding to the data of the point to be built based on the data source; Configure the data collection type for the points to be built based on the source site; Data points corresponding to the data to be built are generated based on the number of decimal places, the acquisition interface, the data address, and the acquisition type.

4. The method for automatically constructing PI database points according to claim 1 or 2, characterized in that, The data information generated in response to the user's operation on the point creation interface, corresponding to the data of the point to be created, includes: In response to the user's operation of the virtual configuration tool on the site construction interface, data information corresponding to the site to be constructed is generated. The virtual configuration tool includes a station virtual configuration tool, a regional virtual configuration tool, and a signal function virtual configuration tool.

5. An automatic point-building device for a PI database, characterized in that, The device includes: The response module is configured to respond to user operations on the point creation interface and generate corresponding data information for the point to be created, including the point number, description, unit, and type of the point to be created. The judgment module is configured to determine whether the data to be built is a duplicate point based on the data information. The data point creation module is configured to configure data points corresponding to the data to be created according to preset configuration parameters, provided that there are no duplicate data points in the data to be created. The preset configuration parameters include basic data, data source, and source site. The storage module is configured to store the data point into the PI database when the data point meets the preset configuration conditions; The judgment module is further configured to compare the data information corresponding to the data point with the data information of the data to be built; if the data information corresponding to the data point is the same as the data information of the data to be built, determine whether the data source of the data point is consistent with the data source of the data to be built; if the data source of the data point is consistent with the data source of the data to be built, determine that the data point meets the preset configuration conditions; if the data source of the data point is inconsistent with the data source of the data to be built, determine that the data point is abnormal and issue an early warning; traverse the storage point numbers in the PI database according to the point number to determine whether the point number is duplicated with the storage point number in the PI database; if the point number is not duplicated with the storage point number in the PI database, determine that the data to be built has no duplicate points; perform semantic analysis on the description and all storage descriptions in the PI database respectively to obtain the similarity value between the description and all storage descriptions in the PI database; if all the similarity values ​​are less than the similarity threshold, determine that the data to be built has no duplicate points.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method described in any one of claims 1-4.

7. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-4.

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