Online state intelligent evaluation method and system of transformer winding
By setting multiple data acquisition points on the transformer winding, acquiring and analyzing multi-source data, and calculating the comprehensive online status evaluation factor, the problem of inaccurate winding status evaluation in the existing technology is solved, and efficient and accurate winding status monitoring is achieved.
Patent Information
- Application Number
- CN202510724855.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-30
- Publication Date
- 2025-09-12
AI Technical Summary
The existing online monitoring methods for transformer windings are difficult to fully reflect the comprehensive status of the windings, lack the deep fusion and intelligent analysis of multi-source heterogeneous data, and are prone to misjudgment or missed judgment.
Multiple data acquisition points are set on the transformer winding to obtain multi-source online status execution data. The winding status is judged by analyzing and combining the sub-online status evaluation factors and combining them with the preset comprehensive online status evaluation factors to achieve intelligent evaluation.
The accuracy and efficiency of online status evaluation of transformer windings are improved, misjudgment or missed judgment is avoided, and the safety and stability of the transformer are ensured.
Smart Images
Figure CN120632253A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of transformer windings, and in particular to an online state intelligent evaluation method and system for transformer windings. Background Art
[0002] As core equipment in power systems, the operating status of transformers directly impacts the safety and stability of the power grid. Windings, critical components of transformers, are susceptible to multiple stresses during long-term operation, including electrical, thermal, and mechanical stresses. This can lead to insulation aging, deformation, or displacement, which can cause serious problems and potentially lead to unexpected accidents. Therefore, real-time monitoring and accurate evaluation of transformer winding status are crucial.
[0003] Currently, the primary method for detecting transformer winding conditions is online monitoring. While these methods (such as oil chromatography and partial discharge detection) can acquire data in real time, they typically focus on a single parameter (such as temperature, vibration, or current) and fail to fully reflect the winding's overall condition. Furthermore, existing online monitoring technologies often rely on threshold alarms or manual judgment, lacking the deep integration and intelligent analysis of multi-source heterogeneous data, which can easily lead to misjudgments or missed detections. Summary of the Invention
[0004] The embodiment of the present invention provides a method and system for intelligent online status evaluation of transformer windings. The present invention can analyze multi-source data to ensure the accuracy and efficiency of online intelligent status evaluation of transformer windings, avoid misjudgment or missed judgment, and ensure the safety and stability of the transformer.
[0005] In order to achieve the above object, the present invention provides an online state intelligent evaluation method for transformer windings, comprising: receiving an online state intelligent evaluation command, presetting a plurality of data acquisition points on a transformer winding, and acquiring a plurality of online state execution data of the transformer winding based on the data acquisition points; Analyzing and combining the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculating the sub-online state evaluation factors of the transformer windings based on the online state execution data groups; Extracting the sub-online state evaluation factors corresponding to each online state execution data group, analyzing all the sub-online state evaluation factors, and calculating the comprehensive online state evaluation factor of the transformer winding based on the analysis results; A preset comprehensive online state evaluation factor is obtained, and whether the transformer winding meets the online state condition is determined based on the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
[0006] Furthermore, before receiving the online state intelligent evaluation command and presetting a plurality of data acquisition points on the transformer winding, the method further includes: Obtaining a previous command and determining a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.
[0007] Furthermore, when the online state execution data corresponding to each data acquisition point is analyzed and combined to obtain multiple online state execution data groups, it includes: Randomly determine a data acquisition point and extract a corresponding online status execution data; Traversing the remaining data acquisition points based on the extracted online state execution data to determine the online state execution data corresponding to the extracted online state execution data; combining the extracted online state execution data with the online state execution data corresponding to the extracted online state execution data to obtain an online state execution data group; The remaining online state execution data of the randomly determined data acquisition points are analyzed and combined to obtain a plurality of online state execution data groups.
[0008] Furthermore, when calculating the sub-online state evaluation factor of the transformer winding according to the online state execution data group, it includes: Randomly extracting one online state execution data from the online state execution data group as the reference online state execution data; Presetting a first preset data value and a second preset data value, and sorting the online state execution data group from small to large; Determine first online state execution data of the reference online state execution data based on the first preset data value; Determining second online state execution data of the reference online state execution data based on the second preset data value; Extracting minimum online state execution data from the first online state execution data, and extracting maximum online state execution data from the second online state execution data; Calculating a difference between the maximum online state execution data and the minimum online state execution data as a change difference of the benchmark online state execution data; determining an overall difference in the online state execution data set; A ratio of the variation difference to the overall difference is calculated and used as a sub-online state evaluation factor of the transformer winding.
[0009] Furthermore, when determining the overall difference of the online state execution data group, it includes: ; Where a is the overall difference of the online state execution data group, s is the number of online state execution data in the online state execution data group, g d+1 is the d+1th online state execution data in the online state execution data group, g d It is the dth online state execution data in the online state execution data group.
[0010] Furthermore, when analyzing all the sub-online status evaluation factors and calculating the comprehensive online status evaluation factor of the transformer winding based on the analysis results, it includes: Extracting the same online status evaluation factor from all the sub-online status evaluation factors and obtaining multiple online status evaluation factor sets; Counting the number of a first online status evaluation factor set of the online status evaluation factor set; Extracting one online status evaluation factor from all online status evaluation factor sets respectively, and calculating a first online status evaluation factor and value; Presetting a preset online status evaluation factor, eliminating all online status evaluation factor sets that are smaller than the preset online status evaluation factor, and counting the number of second online status evaluation factor sets in the remaining online status evaluation factor sets; Extracting one online status evaluation factor from the remaining online status evaluation factor set, and calculating a second online status evaluation factor and value; The comprehensive online status evaluation factor of the transformer winding is calculated according to the number of the first online status evaluation factor sets, the number of the second online status evaluation factor sets, the sum of the first online status evaluation factors and the sum of the second online status evaluation factors.
[0011] Furthermore, when judging whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor, the method includes: When the comprehensive online state evaluation factor is less than the preset comprehensive online state evaluation factor, it is determined that the transformer winding does not meet the online state condition; When the comprehensive online state evaluation factor is greater than or equal to the preset comprehensive online state evaluation factor, it is determined that the transformer winding meets the online state condition.
[0012] Furthermore, after determining that the transformer winding does not meet the online state condition, the method further includes: Presetting a first preset comprehensive online status evaluation factor and a second preset comprehensive online status evaluation factor; Presetting a first preset alarm level, a second preset alarm level, and a third preset alarm level; When the comprehensive online status evaluation factor is less than the first preset comprehensive online status evaluation factor, issuing an alarm based on the first preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the first preset comprehensive online status evaluation factor and less than the second preset comprehensive online status evaluation factor, an alarm is issued based on the second preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the second preset comprehensive online status evaluation factor and less than the preset comprehensive online status evaluation factor, an alarm is issued based on the third preset alarm level.
[0013] In order to achieve the above object, the present invention further provides an online intelligent evaluation system for transformer winding status, comprising: A data acquisition module is used to receive an online state intelligent evaluation command, pre-set multiple data acquisition points on the transformer winding, and acquire multiple online state execution data of the transformer winding based on the data acquisition points; A first calculation module is used to analyze and combine the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculate the sub-online state evaluation factor of the transformer winding based on the online state execution data groups; A second calculation module is used to extract the sub-online state evaluation factors corresponding to each online state execution data group, analyze all the sub-online state evaluation factors, and calculate the comprehensive online state evaluation factor of the transformer winding of the online state execution data group based on the analysis results; The state evaluation module is used to obtain a preset comprehensive online state evaluation factor, and judge whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
[0014] Furthermore, it also includes: A command processing module, configured to obtain a previous command and determine a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.
[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a method and system for intelligent online status evaluation of a transformer winding. The method comprises the following steps: pre-setting a plurality of data acquisition points on the transformer winding to obtain a plurality of online status execution data of the transformer winding; analyzing and combining the online status execution data corresponding to each data acquisition point to obtain a plurality of online status execution data groups, and calculating a sub-online status evaluation factor; analyzing all the sub-online status evaluation factors to calculate a comprehensive online status evaluation factor; obtaining a preset preset comprehensive online status evaluation factor, and judging whether the transformer winding meets the online status condition based on the relationship between the comprehensive online status evaluation factor and the preset comprehensive online status evaluation factor. The method can analyze multi-source data to ensure the accuracy and efficiency of the online status intelligent evaluation of the transformer winding, avoid misjudgment or missed judgment, and ensure the safety and stability of the transformer. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings: Figure 1 A schematic diagram showing a flow chart of an online state intelligent evaluation method for transformer windings according to an embodiment of the present invention is shown; Figure 2 A structural diagram of an online intelligent status evaluation system for transformer windings in an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0017] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following embodiments are used to illustrate the present invention but are not intended to limit the scope of the present invention.
[0018] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.
[0019] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.
[0020] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.
[0021] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.
[0022] like Figure 1 As shown, an embodiment of the present invention discloses an online state intelligent evaluation method for transformer windings, comprising: S110: receiving an online state intelligent evaluation command, presetting a plurality of data acquisition points on a transformer winding, and acquiring a plurality of online state execution data of the transformer winding based on the data acquisition points; In this embodiment, the online state intelligent evaluation command is a command for performing online state intelligent evaluation on the transformer winding.
[0023] In this embodiment, the data acquisition points can be evenly distributed on the transformer windings, and the specific number is preferably 15.
[0024] In this embodiment, the online state execution data includes voltage, current, impedance, temperature, etc., which are not shown here one by one.
[0025] In this embodiment, each data acquisition point corresponds to a plurality of online status execution data.
[0026] In some embodiments of the present application, before receiving the online state intelligent evaluation command and presetting a plurality of data acquisition points on the transformer winding, the method further includes: Obtaining a previous command and determining a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.
[0027] In this embodiment, the previous command includes a voltage detection command, a current detection command, and the like.
[0028] In this embodiment, the time node difference is preferably 30 minutes, which can be adjusted according to actual conditions.
[0029] In this embodiment, if the time node difference is less than the preset time node difference, at this time, the online status intelligent evaluation of the transformer winding is relatively close and does not need to be evaluated again. However, in practice, the staff may want to evaluate again within 30 minutes. Therefore, a log reminder is issued, which is decided by the relevant staff.
[0030] The beneficial effect of the above technical solution is: the present invention matches the online status intelligent evaluation command with the command category of the previous command, and judges the time node difference, which can avoid repeated evaluation of the transformer winding in a short period of time, and also avoids missed evaluations by sending log reminders.
[0031] S120: Analyze and combine the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculate the sub-online state evaluation factors of the transformer winding based on the online state execution data groups; In some embodiments of the present application, when analyzing and combining the online status execution data corresponding to each data acquisition point to obtain multiple online status execution data groups, the following steps are included: Randomly determine a data acquisition point and extract a corresponding online status execution data; Traversing the remaining data acquisition points based on the extracted online state execution data to determine the online state execution data corresponding to the extracted online state execution data; combining the extracted online state execution data with the online state execution data corresponding to the extracted online state execution data to obtain an online state execution data group; The remaining online state execution data of the randomly determined data acquisition points are analyzed and combined to obtain a plurality of online state execution data groups.
[0032] In this embodiment, determining the online status execution data corresponding to the extracted online status execution data means, if the extracted online status execution data is voltage, extracting the voltage corresponding to each remaining data acquisition point, combining all voltages to obtain an online status execution data group, and also obtaining an online status execution data group based on the current corresponding to each data acquisition point.
[0033] The beneficial effect of the above technical solution is: the present invention combines the extracted online status execution data with the online status execution data corresponding to the extracted online status execution data to obtain an online status execution data group, thereby realizing a refined combination of the online status execution data and dividing the online status execution data of the same dimension, thereby providing reliable data support for the intelligent online status evaluation of the transformer winding.
[0034] In some embodiments of the present application, when calculating the sub-online state evaluation factor of the transformer winding according to the online state execution data group, the method includes: Randomly extracting one online state execution data from the online state execution data group as the reference online state execution data; Presetting a first preset data value and a second preset data value, and sorting the online state execution data group from small to large; Determine first online state execution data of the reference online state execution data based on the first preset data value; Determining second online state execution data of the reference online state execution data based on the second preset data value; Extracting minimum online state execution data from the first online state execution data, and extracting maximum online state execution data from the second online state execution data; Calculating a difference between the maximum online state execution data and the minimum online state execution data as a change difference of the benchmark online state execution data; determining an overall difference in the online state execution data set; A ratio of the variation difference to the overall difference is calculated and used as a sub-online state evaluation factor of the transformer winding.
[0035] In this embodiment, the first preset data value is preferably 3, and the second preset data value is preferably 6, which can be adjusted according to actual conditions.
[0036] In this embodiment, the first online state execution data refers to the left side data of the reference online state execution data, and the second online state execution data refers to the right side data of the reference online state execution data.
[0037] The beneficial effect of the above technical solution is: the present invention calculates the ratio of the change difference and the overall difference, and uses it as the sub-online state evaluation factor of the transformer winding, thereby ensuring the calculation accuracy of the sub-online state evaluation factor. The sub-online state evaluation factor can be used to feedback the online state of the transformer winding, thereby ensuring the accuracy of the intelligent online state evaluation of the transformer winding.
[0038] In some embodiments of the present application, determining the overall difference of the online state execution data group includes: ; Where a is the overall difference of the online state execution data group, s is the number of online state execution data in the online state execution data group, g d+1 is the d+1th online state execution data in the online state execution data group, g d It is the dth online state execution data in the online state execution data group.
[0039] S130: extracting the sub-online state evaluation factors corresponding to each online state execution data group, analyzing all the sub-online state evaluation factors, and calculating the comprehensive online state evaluation factor of the transformer winding based on the analysis results; In this embodiment, the above steps are repeated to calculate the sub-online status evaluation factor corresponding to each online status execution data group.
[0040] In some embodiments of the present application, when analyzing all sub-online status evaluation factors and calculating the comprehensive online status evaluation factor of the transformer winding based on the analysis results, the following steps are included: Extracting the same online status evaluation factor from all the sub-online status evaluation factors and obtaining multiple online status evaluation factor sets; Counting the number of a first online status evaluation factor set of the online status evaluation factor set; Extracting one online status evaluation factor from all online status evaluation factor sets respectively, and calculating a first online status evaluation factor and value; Presetting a preset online status evaluation factor, eliminating all online status evaluation factor sets that are smaller than the preset online status evaluation factor, and counting the number of second online status evaluation factor sets in the remaining online status evaluation factor sets; Extracting one online status evaluation factor from the remaining online status evaluation factor set, and calculating a second online status evaluation factor and value; The comprehensive online status evaluation factor of the transformer winding is calculated according to the number of the first online status evaluation factor sets, the number of the second online status evaluation factor sets, the sum of the first online status evaluation factors and the sum of the second online status evaluation factors.
[0041] In this embodiment, the preset online status evaluation factor refers to the variance of all online status evaluation factors.
[0042] In this embodiment, the comprehensive online status evaluation factor of the transformer winding is calculated according to the following formula: ; Wherein, k is the comprehensive online status evaluation factor of the transformer winding, c1 is the number of the first online status evaluation factor set, c2 is the number of the second online status evaluation factor set, v1 is the sum value of the first online status evaluation factor, and v2 is the sum value of the second online status evaluation factor.
[0043] The beneficial effect of the above technical solution is: the present invention calculates the comprehensive online status evaluation factor of the transformer winding based on the number of the first online status evaluation factor set, the number of the second online status evaluation factor set, the sum of the first online status evaluation factor and the sum of the second online status evaluation factor, and realizes the intelligent online status evaluation of the transformer winding through the comprehensive online status evaluation factor, thereby ensuring the evaluation accuracy and efficiency, eliminating the need for manual participation in the evaluation, and eliminating evaluation errors.
[0044] S140: Obtain a preset comprehensive online state evaluation factor, and determine whether the transformer winding meets the online state condition based on the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
[0045] In some embodiments of the present application, when judging whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor, the method includes: When the comprehensive online state evaluation factor is less than the preset comprehensive online state evaluation factor, it is determined that the transformer winding does not meet the online state condition; When the comprehensive online state evaluation factor is greater than or equal to the preset comprehensive online state evaluation factor, it is determined that the transformer winding meets the online state condition.
[0046] In this embodiment, the preset comprehensive online status evaluation factor is preferably 5, and can be adjusted according to actual conditions.
[0047] The beneficial effect of the above technical solution is that the present invention determines whether the transformer winding meets the online status conditions based on the relationship between the comprehensive online status evaluation factor and the preset comprehensive online status evaluation factor, thereby providing technical support for the safe maintenance and management of the transformer winding.
[0048] In some embodiments of the present application, after determining that the transformer winding does not meet the online state condition, the method further includes: Presetting a first preset comprehensive online status evaluation factor and a second preset comprehensive online status evaluation factor; Presetting a first preset alarm level, a second preset alarm level, and a third preset alarm level; When the comprehensive online status evaluation factor is less than the first preset comprehensive online status evaluation factor, issuing an alarm based on the first preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the first preset comprehensive online status evaluation factor and less than the second preset comprehensive online status evaluation factor, an alarm is issued based on the second preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the second preset comprehensive online status evaluation factor and less than the preset comprehensive online status evaluation factor, an alarm is issued based on the third preset alarm level.
[0049] In this embodiment, the first preset comprehensive online status evaluation factor is preferably 2, and the second preset comprehensive online status evaluation factor is preferably 4, which can be adjusted according to actual conditions.
[0050] In this embodiment, the first preset alarm level is greater than the second preset alarm level, which is greater than the third preset alarm level.
[0051] The beneficial effect of the above technical solution is: the present invention selects the corresponding preset alarm level according to the comprehensive online status evaluation factor, the first preset comprehensive online status evaluation factor and the second preset comprehensive online status evaluation factor, thereby achieving accurate alarm and ensuring the rationality of the online status maintenance of the transformer winding, which can not only ensure the efficient maintenance of the transformer winding, but also avoid the waste of manpower and material resources.
[0052] In order to further illustrate the technical idea of the present invention, the technical solution of the present invention is now described in combination with specific application scenarios.
[0053] Correspondingly, such as Figure 2 As shown, the present application also provides an online intelligent evaluation system for transformer winding status, comprising: A data acquisition module is used to receive an online state intelligent evaluation command, pre-set multiple data acquisition points on the transformer winding, and acquire multiple online state execution data of the transformer winding based on the data acquisition points; A first calculation module is used to analyze and combine the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculate the sub-online state evaluation factor of the transformer winding based on the online state execution data groups; A second calculation module is used to extract the sub-online state evaluation factors corresponding to each online state execution data group, analyze all the sub-online state evaluation factors, and calculate the comprehensive online state evaluation factor of the transformer winding of the online state execution data group based on the analysis results; The state evaluation module is used to obtain a preset comprehensive online state evaluation factor, and judge whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
[0054] In some embodiments of the present application, further comprising: A command processing module, configured to obtain a previous command and determine a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.
[0055] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.
[0056] While the present invention has been described above with reference to exemplary embodiments, various modifications may be made and equivalent components may be substituted without departing from the scope of the present invention. In particular, the various features of the disclosed embodiments may be combined with one another in any manner, provided no structural conflicts exist. These combinations are not fully described in this specification for reasons of space and resource conservation.
[0057] Those skilled in the art will understand that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will still be able to modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.
Claims
1. A method for intelligent online status evaluation of transformer windings, characterized in that: include: receiving an online state intelligent evaluation command, presetting a plurality of data acquisition points on a transformer winding, and acquiring a plurality of online state execution data of the transformer winding based on the data acquisition points; Analyzing and combining the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculating the sub-online state evaluation factors of the transformer windings based on the online state execution data groups; Extracting the sub-online state evaluation factors corresponding to each online state execution data group, analyzing all the sub-online state evaluation factors, and calculating the comprehensive online state evaluation factor of the transformer winding based on the analysis results; A preset comprehensive online state evaluation factor is obtained, and whether the transformer winding meets the online state condition is determined based on the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
2. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: Before receiving the online state intelligent evaluation command and presetting multiple data acquisition points on the transformer winding, the process also includes: Obtaining a previous command and determining a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.
3. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: When analyzing and combining the online status execution data corresponding to each data acquisition point to obtain multiple online status execution data groups, it includes: Randomly determine a data acquisition point and extract a corresponding online status execution data; Traversing the remaining data acquisition points based on the extracted online state execution data to determine the online state execution data corresponding to the extracted online state execution data; combining the extracted online state execution data with the online state execution data corresponding to the extracted online state execution data to obtain an online state execution data group; The remaining online state execution data of the randomly determined data acquisition points are analyzed and combined to obtain a plurality of online state execution data groups.
4. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: When calculating the sub-online state evaluation factor of the transformer winding according to the online state execution data group, it includes: Randomly extracting one online state execution data from the online state execution data group as the reference online state execution data; Presetting a first preset data value and a second preset data value, and sorting the online state execution data group from small to large; Determine first online state execution data of the reference online state execution data based on the first preset data value; Determining second online state execution data of the reference online state execution data based on the second preset data value; Extracting minimum online state execution data from the first online state execution data, and extracting maximum online state execution data from the second online state execution data; Calculating a difference between the maximum online state execution data and the minimum online state execution data as a change difference of the benchmark online state execution data; determining an overall difference in the online state execution data set; A ratio of the variation difference to the overall difference is calculated and used as a sub-online state evaluation factor of the transformer winding.
5. The method for online intelligent evaluation of transformer winding status according to claim 4, characterized in that: When determining the overall difference of the online state execution data group, it includes: ； Where a is the overall difference of the online state execution data group, s is the number of online state execution data in the online state execution data group, g d+1 is the d+1th online state execution data in the online state execution data group, g d It is the dth online state execution data in the online state execution data group.
6. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: When analyzing all sub-online status evaluation factors and calculating the comprehensive online status evaluation factor of the transformer winding based on the analysis results, the following steps are included: Extracting the same online status evaluation factor from all the sub-online status evaluation factors and obtaining multiple online status evaluation factor sets; Counting the number of a first online status evaluation factor set of the online status evaluation factor set; Extracting one online status evaluation factor from all online status evaluation factor sets respectively, and calculating a first online status evaluation factor and value; Presetting a preset online status evaluation factor, eliminating all online status evaluation factor sets that are smaller than the preset online status evaluation factor, and counting the number of second online status evaluation factor sets in the remaining online status evaluation factor sets; Extracting one online status evaluation factor from the remaining online status evaluation factor set, and calculating a second online status evaluation factor and value; The comprehensive online status evaluation factor of the transformer winding is calculated according to the number of the first online status evaluation factor sets, the number of the second online status evaluation factor sets, the sum of the first online status evaluation factors and the sum of the second online status evaluation factors.
7. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: When judging whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor, the method includes: When the comprehensive online state evaluation factor is less than the preset comprehensive online state evaluation factor, it is determined that the transformer winding does not meet the online state condition; When the comprehensive online state evaluation factor is greater than or equal to the preset comprehensive online state evaluation factor, it is determined that the transformer winding meets the online state condition.
8. The method for online intelligent evaluation of transformer winding status according to claim 1, characterized in that: After determining that the transformer winding does not meet the online state condition, the method further includes: Presetting a first preset comprehensive online status evaluation factor and a second preset comprehensive online status evaluation factor; Presetting a first preset alarm level, a second preset alarm level, and a third preset alarm level; When the comprehensive online status evaluation factor is less than the first preset comprehensive online status evaluation factor, issuing an alarm based on the first preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the first preset comprehensive online status evaluation factor and less than the second preset comprehensive online status evaluation factor, an alarm is issued based on the second preset alarm level; When the comprehensive online status evaluation factor is greater than or equal to the second preset comprehensive online status evaluation factor and less than the preset comprehensive online status evaluation factor, an alarm is issued based on the third preset alarm level.
9. An online state intelligent evaluation system for transformer windings, applied to the online state intelligent evaluation method for transformer windings according to any one of claims 1 to 8, characterized in that: include: A data acquisition module is used to receive an online state intelligent evaluation command, pre-set multiple data acquisition points on the transformer winding, and acquire multiple online state execution data of the transformer winding based on the data acquisition points; A first calculation module is used to analyze and combine the online state execution data corresponding to each data acquisition point to obtain multiple online state execution data groups, and calculate the sub-online state evaluation factor of the transformer winding based on the online state execution data groups; A second calculation module is used to extract the sub-online state evaluation factors corresponding to each online state execution data group, analyze all the sub-online state evaluation factors, and calculate the comprehensive online state evaluation factor of the transformer winding of the online state execution data group based on the analysis results; The state evaluation module is used to obtain a preset comprehensive online state evaluation factor, and judge whether the transformer winding meets the online state condition according to the relationship between the comprehensive online state evaluation factor and the preset comprehensive online state evaluation factor.
10. The online intelligent status evaluation system for transformer windings according to claim 9, characterized in that: Also includes: A command processing module, configured to obtain a previous command and determine a command category of the previous command; Matching the online status intelligent evaluation command with the command category of the previous command, and determining whether the online status intelligent evaluation command is the same as the previous command; If the online status intelligent evaluation command matches the command category of the previous command, determining that the online status intelligent evaluation command is the same as the previous command, collecting a first time node of sending the online status intelligent evaluation command, and collecting a second time node of sending the previous command; Calculating a time node difference between the first time node and the second time node, and determining whether the online status intelligent evaluation command can be processed based on a relationship between the time node difference and a preset time node difference; If the time node difference is greater than or equal to the preset time node difference, it is determined that the online status intelligent evaluation command can be processed; If the time node difference is less than the preset time node difference, it is determined that the online status intelligent evaluation command cannot be processed, and a log reminder is generated and sent; If the online status intelligent evaluation command does not match the command category of the previous command, it is determined that the online status intelligent evaluation command is different from the previous command, and the online status intelligent evaluation command is processed.