Power station equipment measurement data association method

Abstract

The invention belongs to the technical field of power station equipment data processing, and particularly relates to a power station equipment measurement data association method. The method comprises the following steps: acquiring a device name and a measurement field; obtaining an equipment name keyword according to the equipment name; according to a pre-obtained equipment and measurement data matching rule and by utilizing the equipment name keyword, carrying out equipment and measurement data matching; if equipment matching succeeds, adding an equipment unique identifier in a measurement model corresponding to the measurement data; if the equipment is not successfully matched, modifying a matching rule of the equipment and the measurement data, and re-matching the equipment and the measurement data; the pre-obtained equipment and measurement data matching rule comprises character string matching of the equipment name keyword and the measurement field by utilizing a logic rule in a character string matching rule. The technical problem of low matching success rate in the prior art is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power station equipment data processing, and in particular relates to a method for associating power station equipment measurement data. Background Art

[0002] Digital UHV stations (including digital converter stations and digital UHV substations) play an important role in UHV transmission systems. At present, there are many types of primary and secondary equipment and information subsystems in UHV substations, which brings a great burden to the supervision and management of station operators. At present, in order to strengthen the operation and maintenance of digital UHV station subsystems and equipment, the construction of digital station informatization and digitization is being carried out. Due to the demand for equipment data analysis and diagnosis, a data aggregation and sharing platform for the entire station centered on equipment should be created during the digital construction of digital stations. It is necessary to associate the telemetry and telesignaling of the entire station with the equipment. A device generally contains multiple telemetry and telesignaling, and in order to distinguish the types of multiple telemetry and telemetering in the equipment, the types of telemetry and telemetering need to be determined. There are more than 100,000 telemetry and telemetering data in the converter station, about 2,000 primary equipment and about 1,500 secondary equipment. There are about 8,000 types of measurement in the entire station. If the telemetry and telemetering types are manually associated and the telemetry and telemetering are associated with the equipment, the workload is huge.

[0003] The Chinese invention patent application with application publication number CN117591899A and application publication date 2024.02.23 discloses a method for automatic matching of substation alarm signals and equipment locations. After extracting keywords from the alarm signal information and equipment location information respectively, the method uses a similarity matching method to associate and match the alarm signal with the equipment location. The alarm signal with a higher similarity is automatically associated with the equipment location, and the alarm signal with a lower similarity is manually associated with the equipment location. After extracting keywords, the above method only performs association matching based on the similarity matching rule, resulting in a low matching success rate. Summary of the invention

[0004] The purpose of the present invention is to provide a method for associating power station equipment measurement data to solve the technical problem of low matching success rate in the prior art.

[0005] In order to solve the above technical problems, the present invention provides a technical solution for a method for associating power station equipment measurement data: a method for associating power station equipment measurement data, the method comprising: obtaining a device name and a measurement field; and obtaining a device name keyword according to the device name; matching the device with the measurement data according to a pre-acquired device and measurement data matching rule and using the device name keyword: if the device is successfully matched, a unique device identifier is added to the measurement model of the corresponding measurement data; if the device is not successfully matched, the matching rule between the device and the measurement data is modified, and the device and the measurement data are matched again; the pre-acquired device and measurement data matching rule includes using the logical rule in the string matching rule to perform string matching between the device name keyword and the measurement field.

[0006] The beneficial effect of the above technical solution is that the technical solution of the power plant equipment measurement data association method of the present invention belongs to an improved invention. When performing association matching, the present invention regenerates new matching rules according to keywords and re-matches, and the cross-use of multiple matching rules greatly improves the matching success rate. The present invention solves the technical problem of low matching success rate in the prior art.

[0007] Furthermore, the method also includes: obtaining a measurement type keyword; after the device and the measurement data are matched, matching the measurement data and the measurement type under the device according to a pre-acquired measurement type matching rule; if the measurement type is matched successfully, adding a measurement type unique identifier to the measurement model of the corresponding measurement data; if the measurement type is not matched successfully, modifying the measurement type matching rule, and re-matching the measurement and the measurement type under the device; the pre-acquired measurement type matching rule includes using the logical rules in the string matching rule to perform string matching between the device name keyword and the measurement field.

[0008] Furthermore, the device name keyword includes a typical naming feature keyword or an alias keyword.

[0009] Furthermore, for a device with a typical naming feature, the typical naming feature is extracted as a device name keyword of the device.

[0010] Furthermore, for a device with an alias, the alias is used as a device name keyword of the device.

[0011] Furthermore, the device name keywords also include keywords extracted by performing syntactic analysis on the device name.

[0012] Furthermore, after extracting keywords from the device name by syntactic analysis, the pre-acquired device and measurement matching rules are automatically generated according to the keywords.

[0013] Furthermore, the string matching rule includes at least one of a regular expression, and, or, before-contains, after-contains, contains, equals and not equals.

[0014] Furthermore, the pre-acquired device and measurement data matching rule and / or the pre-acquired measurement type matching rule further includes a similarity matching rule. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A method flow chart of an embodiment of a method for associating power plant equipment measurement data according to the present invention;

[0016] Figure 2 This is a schematic diagram of extracting keywords from devices with aliases according to an embodiment of a method for associating power plant equipment measurement data of the present invention. DETAILED DESCRIPTION

[0017] The present invention regenerates new matching rules according to keywords and re-matches when performing association matching, and greatly improves the matching success rate by cross-using multiple matching rules. The present invention solves the technical problem of low matching success rate in the prior art.

[0018] Power station equipment measurement data association method embodiment:

[0019] A method for associating power station equipment measurement data, comprising the following steps:

[0020] 1) Create data templates for equipment type, measurement data belonging to the equipment, and measurement type;

[0021] It should be noted that the measurement data referred to in the present invention refers to a collection of data of a certain measurement data of a certain device at any time, and does not specifically refer to a specific value of the measurement data detected at a certain time.

[0022] 2) Import equipment, telemetry, and telesignaling models;

[0023] 3) Extract typical naming features or aliases and other keywords from the device name for matching telemetry and telesignaling; the device name feature keywords can be automatically extracted or manually edited.

[0024] a) For equipment with typical naming features, extract the typical naming features as the equipment name keywords of the equipment. For example, for the circuit breaker operation number, such as T082 circuit breaker and T062 circuit breaker, extract the equipment name keywords T082 and T062.

[0025] b) Perform syntactic analysis on the device name to extract keywords, and use the keywords to automatically generate device and measurement matching rules. For example, if the device name is: Pole I low-end Y / Y8121B converter transformer A phase, use syntactic analysis to extract the keywords pole I, low-end, Y / Y, A phase.

[0026] c) Representation method for equipment with aliases in the converter station, such as Figure 2 As shown, the breaker number 5111 is WB.W1-Q1, and WB.W1-Q1 is used as the keyword for the equipment name of the 5111 breaker.

[0027] After obtaining the keyword, use the keyword to automatically generate a matching rule, and use the keyword to automatically generate a regular matching rule such as [{Pole I.*Low-end.*Y / Y.*Phase A}], or a string matching rule [{%Pole I%}&{%Low-end%}&{%Y / Y%}&{%Phase A%}].

[0028] Rule expression rule definition:

[0029] [field1:{%filter1}&{filter2}&{!filter3}]&[field2:{%filter4}]

[0030] The square brackets [] indicate string matching for a certain field of the measurement. field1 and field2 are the measurement fields to be matched; the curly braces {} indicate a string matching rule, and filter1 to filter4 are the obtained keywords for the equipment name; logical calculations of AND (&), OR (|), and NOT (!) can be performed between [] and [], and multiple {} expressions can be included within a single field. The {} expressions can perform AND, OR, and NOT calculations on the keywords. The rules inside {} support rule parsing such as regular expressions, front inclusion, back inclusion, and string similarity matching comparison. Among them, when there is only a string without an operator inside the {} parentheses, it indicates a default inclusion operation, such as {filter2}.

[0031] 4) Match the equipment keyword with the measurement according to the equipment and measurement data matching rule. For those that match successfully, add the equipment unique identifier to the measurement matching rule model; for those without telemetry and telecontrol matching, modify the equipment keyword matching rule and then associate it with telemetry and telecontrol.

[0032] For example: If the initial equipment and measurement data matching rule is generated based on the string matching rule and uses "front inclusion" to connect each keyword, then after the matching fails, generate a new equipment and measurement data matching rule based on the similarity matching rule and re-match, or modify "front inclusion" to "back inclusion" and re-match.

[0033] 5) After the measurement data is associated with the equipment, match the measurement data under the equipment with the measurement type;

[0034] 6) Write the measurement type matching rules as shown in Table 1. The measurement type matching rules are the same as the equipment and measurement data matching rules to associate the types of telesignaling and telemetering. For successfully matched telesignaling and telemetering, the unique identifier of the measurement type is recorded in its model.

[0035] Table 1 Measurement type matching rules

[0036] Type Description Class Name Matching rules hydrogen H2 [{% Hydrogen}]|[{% H2}] Carbon monoxide CO [{% Carbon monoxide}]|[{% CO}] carbon dioxide CO2 [{% Carbon dioxide}]|[{% CO2}] Ethylene C2H4 [{% ethylene}]|[{% C2H4}] Ethane C2H6 [{%Ethane}]|[{%C2H6}] oxygen O2 <![CDATA[[{%O2}]|[{% oxygen}]|[{%O2}]]]>

[0037] The flow chart of the method in this embodiment is as follows Figure 1 As shown below, combined with the attached Figure 1 The present invention is further explained.

[0038] First, create physical models of the device type and device measurement type and import the device and measurement data.

[0039] Then, add keywords of device name and measurement type to the device table and device measurement type table, and compile device matching rules (i.e., device and measurement data matching rules) and device measurement type matching rules (i.e., measurement type matching rules) based on the keywords. Specifically, the device name keyword can automatically extract keywords using a syntactic analysis method, and automatically generate device matching rules based on the extracted keywords. Matching rules (including device and measurement data matching rules and measurement type matching rules) support regular expressions, starting with a certain string (i.e., including before) / ending with a certain string (i.e., including after) / including / equal to / not equal to, and support various forms of AND or NOT logical operations.

[0040] In the matching process, the device and the measurement data are matched first. The device and the measurement data are matched according to the matching rules of the device and the measurement data. If the match is successful, the unique device identifier is added to the measurement model; if the match fails, the matching rules of the device and the measurement data are regenerated, and the device and the measurement are matched again.

[0041] After the device and measurement are matched, the measurement and measurement type under the same device are matched according to the device measurement type matching rules. If the match is successful, the measurement type unique identifier is added to the measurement model; if the match fails, the device measurement matching rules are regenerated and the measurement and measurement type are matched again.

[0042] After completing the matching of equipment and measurement data and the matching of measurement data and measurement type under the equipment, all data collected during the subsequent operation of the power station can be conveniently integrated and processed based on the matched model, which is conducive to the subsequent equipment data analysis and diagnosis as well as the digitalization and informatization construction of the power station.

[0043] It should be noted that the method of the present invention can be applied to centralized control stations, substations, converter stations, digital stations and other systems that require model power stations.

[0044] The following is an example of the device matching measurement of "extreme I low-end Y / Y8121B commutation transformer A phase":

[0045] Step 1: The device name is Pole I Low-End Y / Y8121B Converter A Phase. Use syntax analysis to extract the keywords Pole I, Low-End, Y / Y, 8121B, Converter, and A Phase. Generate the device and measurement data matching rule [path:{Pole I}&{Low-End}&{Y / Y}&{8121B}&{Converter}&{A Phase}] based on the syntax analysis results, and match the telemetry and telesignaling data according to the rule. The matching results are shown in Table 2:

[0046] Table 2 The first equipment and measurement data matching results

[0047]

[0048]

[0049] Step 2: It is found from Table 2 that some telemetry is not matched successfully. After checking, it is found that the formats of "Pole I" and "Pole Ⅰ" are inconsistent, and pole I is not a search keyword. The rule can be modified to delete the keyword pole I, that is, [path:{low end}&{Y / Y}&{8121B}&{commutator}&{Phase A}], or further modify the rule to [path:{8121B}&{Phase A}], and then match. After all matches are successful, modify the device information in the telemetry properties as shown in Table 3.

[0050] Table 3 Telemetry attribute table after successful matching of equipment and measurement data

[0051]

[0052]

[0053] Step 3: Match the telemetry data of the A-phase device of the low-end Y / Y8121B converter transformer of pole I by the measurement type and other attributes. Take "Pole I low-end Y / Y converter transformer 8121B A-phase transformer operating condition. Bottom layer oil temperature" as an example to illustrate. Use "Pole I low-end Y / Y converter transformer 8121B A-phase transformer operating condition. Bottom layer oil temperature" to describe all measurement rules under the converter transformer equipment type for matching. As a result, only the matching rule "[{% bottom layer oil temperature}]" meets the rule. Therefore, the measurement "Pole I low-end Y / Y converter transformer 8121B A-phase transformer operating condition. Bottom layer oil temperature" under the A-phase of the low-end Y / Y8121B converter transformer of pole I is assigned the BotTmp measurement type, unit ℃ and other attributes.

[0054] The same method was used to match other measurements and the final results are shown in Table 4:

[0055] Table 4 Measurement type matching results

[0056]

[0057]

[0058] The present invention has the following characteristics:

[0059] The present invention relies on the basic principle of associating telesignaling, telemetry with equipment and equipment measurement types by writing or automatically generating equipment keyword strings and measurement type keywords. The program can be used to automatically match and associate, and finally establish modeling of the equipment and types to which all station measurement points belong. This method can effectively improve data classification efficiency by about 80%, facilitate the classification of measurement data within the station, and provide a model basis for data analysis of advanced applications.

[0060] The present invention uses keywords to match equipment and measurement, and measurement type, to achieve the association of telesignaling, telemetry and equipment, and equipment measurement type, and uses a program to automatically match and associate to establish a model of the equipment and type to which all station measurement points belong. This method can effectively improve the efficiency of data management by 80%, and also save labor costs. This method can be extended to areas where model management is required in systems such as centralized control stations and substations.

[0061] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments without creative work, or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for associating power station equipment measurement data, characterized in that: The method comprises: obtaining a device name and a measurement field; obtaining a device name keyword according to the device name; matching the device with the measurement data according to a pre-acquired device and measurement data matching rule and using the device name keyword: if the device is successfully matched, adding a device unique identifier in a measurement model corresponding to the measurement data; if the device is not successfully matched, modifying the device and measurement data matching rule, and re-matching the device with the measurement data; the pre-acquired device and measurement data matching rule comprises using a logical rule in a string matching rule to match the device name keyword with the measurement field.

2. The power plant equipment measurement data association method according to claim 1, characterized in that: The method also includes: obtaining a measurement type keyword; after the device and the measurement data are matched, matching the measurement data and the measurement type under the device according to a pre-acquired measurement type matching rule; if the measurement type is successfully matched, adding a unique identification of the measurement type in the measurement model of the corresponding measurement data; if the measurement type is not successfully matched, modifying the measurement type matching rule, and re-matching the measurement and the measurement type under the device; the pre-acquired measurement type matching rule includes using the logical rule in the string matching rule to perform string matching between the device name keyword and the measurement field.

3. The power station equipment measurement data association method according to claim 1, characterized in that: The device name keyword includes a typical naming feature keyword or an alias keyword.

4. The power station equipment measurement data association method according to claim 3, characterized in that: For a device with a typical naming feature, the typical naming feature is extracted as a device name keyword of the device.

5. The power station equipment measurement data association method according to claim 3, characterized in that: For a device with an alias, the alias is used as the device name keyword of the device.

6. The power station equipment measurement data association method according to claim 1, characterized in that: The device name keywords also include keywords extracted by performing syntactic analysis on the device name.

7. The power station equipment measurement data association method according to claim 6, characterized in that: After extracting keywords from the device name through syntactic analysis, the pre-acquired device and measurement matching rules are automatically generated according to the keywords.

8. The power station equipment measurement data association method according to claim 1 or 2, characterized in that: The string matching rule includes at least one of regular expression, and, or, before inclusion, after inclusion, contains, equal to and not equal to.

9. The power station equipment measurement data association method according to claim 2, characterized in that: The pre-acquired device and measurement data matching rule and / or the pre-acquired measurement type matching rule further includes a similarity matching rule.

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