CN116165318B - Transformer fault type identification method and device and electronic equipment - Google Patents
Transformer fault type identification method and device and electronic equipment Download PDFInfo
- Publication number
- CN116165318B CN116165318B CN202310458089.5A CN202310458089A CN116165318B CN 116165318 B CN116165318 B CN 116165318B CN 202310458089 A CN202310458089 A CN 202310458089A CN 116165318 B CN116165318 B CN 116165318B
- Authority
- CN
- China
- Prior art keywords
- characteristic gas
- value
- data
- voltage
- filling
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/86—Signal analysis
- G01N30/8696—Details of Software
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention discloses a transformer fault type identification method, a device and electronic equipment, which are used for solving the technical problems that the existing transformer fault type identification method is low in accuracy and easy to bring hidden danger to safe and stable operation of a power system. The invention comprises the following steps: acquiring characteristic gas oil chromatographic monitoring data of a transformer; determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data; filling the missing value of the characteristic gas according to the missing value type to obtain filling data; performing primary correction on the filling data to obtain primary correction data; performing secondary correction on the filling data to obtain secondary correction data; and identifying a transformer fault type of the transformer based on the padding data when the primary correction data is the same as the secondary correction data.
Description
Technical Field
The present invention relates to the field of transformers, and in particular, to a method and an apparatus for identifying a fault type of a transformer, and an electronic device.
Background
The transformer is used as a junction in the whole power system for connecting different voltages, and the running condition of the transformer determines whether the power grid is safe and stable. However, the transformer is difficult to avoid faults in operation, if the faults occur inInside the body, especially latent faults such as partial discharge, poor contact and the like can generate local overheating, and the heat reaches a certain degree to enable the transformer oil to generate chemical reaction to generate a series of characteristic gases, including: hydrogen (H) 2 ) Methane (CH) 4 ) Ethane (C) 2 H 6 ) Ethylene (C) 2 H 4 ) Acetylene (C) 2 H 2 ) Carbon monoxide (CO), carbon dioxide (CO) 2 ). Therefore, the safe and stable operation of the transformer is an essential factor for the safety and reliability of the power, and effective measures must be taken to prevent and reduce the occurrence of faults of the transformer.
In the prior art, fault type analysis of transformers can be performed by monitoring transformer equipment status oil chromatography data. However, a data loss occurs in the transformer oil chromatographic monitoring process, so that the accuracy of fault type analysis based on the transformer oil chromatographic monitoring data is low. It is therefore necessary to process the missing values of the chromatographic monitoring data of transformer oil.
Currently, in the process of processing the missing values of the transformer equipment state oil chromatograph monitoring data, most of the methods are adopted to directly ignore or delete samples containing the missing values, but the methods can cause loss of effective information and damage to time sequence continuity. Furthermore, common processing methods include mean interpolation, which replaces the missing value with the mean or mode of the complete value of the same variable. However, the mean value interpolation method does not consider the change rule of the time sequence, and the interpolation result contains more repeated values, so that the true distribution of the data is distorted, and the fault type of the transformer cannot be accurately identified according to the characteristic gas signal data, thereby bringing hidden danger to the safe and stable operation of the power system.
Disclosure of Invention
The invention provides a transformer fault type identification method, a device and electronic equipment, which are used for solving the technical problems that the existing transformer fault type identification method is low in accuracy and easy to bring hidden danger to safe and stable operation of a power system.
The invention provides a transformer fault type identification method, which comprises the following steps:
acquiring characteristic gas oil chromatographic monitoring data of a transformer;
determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data;
Filling the missing value of the characteristic gas according to the missing value type to obtain filling data;
performing primary correction on the filling data to obtain primary correction data;
performing secondary correction on the filling data to obtain secondary correction data;
and identifying a transformer fault type of the transformer based on the padding data when the primary correction data is the same as the secondary correction data.
Optionally, the step of determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data includes:
and determining a missing characteristic gas missing value and a missing value type of the characteristic gas missing value from the characteristic gas oil chromatographic monitoring data through a preset transformer oil chromatographic model.
Optionally, the step of filling the missing value of the characteristic gas according to the missing value type to obtain filling data includes:
acquiring a time sequence of the characteristic gas oil chromatography monitoring data;
when the missing value type is a single characteristic gas missing value type, acquiring the same number of first characteristic gas signal values before and after the characteristic gas missing value based on the time sequence;
Calculating an average value of the first characteristic gas signal values;
and filling the characteristic gas missing value by adopting the average value to obtain filling data.
Optionally, the step of filling the missing value of the feature gas according to the missing value type to obtain filling data further includes:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring continuous second characteristic gas signal values in preset time before and after the characteristic gas missing value based on the time sequence;
carrying out data segmentation on all the second characteristic gas signal values to obtain a plurality of segmentation results; the segmentation result corresponds to a plurality of the characteristic gas deficiency values one by one;
carrying out data standardization processing on the segmented result to obtain a standardized processing result;
and filling the characteristic gas missing value by adopting the standardized processing result as a filling value to obtain filling data.
Optionally, the step of performing primary correction on the padding data to obtain primary correction data includes:
when the missing value type is continuous to a single characteristic gas missing value type, acquiring a first voltage and a first current of the characteristic gas missing value and a second voltage and a second current in a preset time before and after the characteristic gas missing value based on the time sequence;
Calculating a first voltage average value of the first voltage and the second voltage, and calculating a first voltage ratio of the first voltage to the first voltage average value;
calculating a first current average value of the first current and the second current, and calculating a first current ratio of the first current to the first current average value;
and correcting the filling data once by adopting the first voltage ratio and the first current ratio to obtain primary correction data.
Optionally, the step of correcting the padding data once to obtain primary correction data further includes:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring a plurality of third voltages and third currents respectively corresponding to the characteristic gas missing values based on the time sequence, and fourth voltages and fourth currents in preset time before and after the characteristic gas missing values;
calculating a second voltage average value of the third voltage and the fourth voltage, and calculating a second voltage ratio of the third voltage to the second voltage average value;
calculating a second current average value of the third current and the fourth current, and calculating a second current ratio of the third current to the second current average value;
And correcting the filling data once by adopting the second voltage ratio and the second current ratio to obtain primary correction data.
Optionally, the step of performing secondary correction on the padding data to obtain secondary correction data includes:
when the missing value type is continuous to a single characteristic gas missing value type, acquiring a first transformer oil temperature of the characteristic gas missing value and a second transformer oil temperature within a preset time before and after the characteristic gas missing value based on the time sequence;
calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature, and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value;
and carrying out secondary correction on the filling data by adopting the first oil temperature ratio to obtain secondary correction data.
Optionally, the step of performing secondary correction on the padding data to obtain secondary correction data further includes:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring third transformer oil temperatures respectively corresponding to a plurality of characteristic gas missing values based on the time sequence and fourth transformer oil temperatures in preset time before and after the characteristic gas missing values;
Calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature, and calculating a second oil temperature ratio of the third transformer oil temperature to the second oil temperature average value;
and carrying out secondary correction on the filling data by adopting the second oil temperature ratio to obtain secondary correction data.
The invention provides a transformer fault type identification device, which comprises:
the characteristic gas oil chromatography monitoring data acquisition module is used for acquiring characteristic gas oil chromatography monitoring data of the transformer;
the characteristic gas deficiency value and deficiency value type determining module is used for determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data;
the filling module is used for filling the missing value of the characteristic gas according to the missing value type to obtain filling data;
the primary correction module is used for carrying out primary correction on the filling data to obtain primary correction data;
the secondary correction module is used for carrying out secondary correction on the filling data to obtain secondary correction data;
and the fault type identification module is used for identifying the transformer fault type of the transformer based on the filling data when the primary correction data is the same as the secondary correction data.
The invention provides an electronic device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the transformer fault type identification method according to any one of the above claims according to instructions in the program code.
From the above technical scheme, the invention has the following advantages: the invention provides a transformer fault type identification method, which comprises the following steps: acquiring characteristic gas oil chromatographic monitoring data of a transformer; determining a characteristic gas missing value and a missing value type of the characteristic gas missing value according to the characteristic gas oil chromatography monitoring data; filling the missing value of the characteristic gas according to the type of the missing value to obtain filling data; performing primary correction on the filling data to obtain primary correction data; performing secondary correction on the filling data to obtain secondary correction data; and when the primary correction data is the same as the secondary correction data, identifying the transformer fault type of the transformer based on the padding data. The invention complements the missing value of the characteristic gas by determining the missing value type, realizes the repair of complete data, and improves the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data; and the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data is improved by carrying out primary correction processing and secondary correction processing on the characteristic gas missing value filling.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart of steps of a method for identifying a fault type of a transformer according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for identifying a fault type of a transformer according to another embodiment of the present invention;
fig. 3 is a block diagram of a compiler fault type recognition device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a transformer fault type identification method, a device and electronic equipment, which are used for solving the technical problems that the existing transformer fault type identification method is low in accuracy and easy to bring hidden danger to safe and stable operation of a power system.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating steps of a transformer fault type identification method according to an embodiment of the present invention.
The invention provides a transformer fault type identification method, which specifically comprises the following steps:
step 101, acquiring characteristic gas oil chromatographic monitoring data of a transformer;
a transformer is a device for changing an ac voltage using the principle of electromagnetic induction, and the main components are a primary coil, a secondary coil, and an iron core (magnetic core). The main functions are as follows: voltage transformation, current transformation, impedance transformation, isolation, voltage stabilization (magnetic saturation transformers), and the like.
In the embodiment of the invention, the oil chromatographic monitoring data of the characteristic gas of the transformer can be obtained to perform fault analysis.
In one example, the feature gas may include hydrogen (H 2 ) Methane (CH) 4 ) Ethane (C) 2 H 6 ) Ethylene (C) 2 H 4 ) Acetylene (C) 2 H 2 ) Carbon monoxide (CO), carbon dioxide (CO) 2 ）。
Step 102, determining a characteristic gas missing value and a missing value type of the characteristic gas missing value according to characteristic gas oil chromatography monitoring data;
in the embodiment of the invention, after the characteristic gas oil chromatography monitoring data is obtained, the characteristic gas missing value and the missing value type of the characteristic gas missing value can be determined according to the characteristic gas oil chromatography monitoring data.
In specific implementation, the characteristic gas oil chromatographic monitoring data can be analyzed by establishing a transformer oil chromatographic model, and the characteristic gas missing value and the missing value type of the characteristic gas missing value are determined.
Step 103, filling the missing value of the characteristic gas according to the type of the missing value to obtain filling data;
after the missing value type and the characteristic gas missing value are determined, the characteristic gas missing value can be filled according to the missing value type, and filling data are obtained.
104, carrying out primary correction on the filling data to obtain primary correction data;
step 105, performing secondary correction on the filling data to obtain secondary correction data;
and 106, identifying the transformer fault type of the transformer based on the filling data when the primary correction data is the same as the secondary correction data.
After the padding data is acquired, primary correction and secondary correction may be performed on the padding data. And judging the accuracy of the filling data by comparing the primary correction data with the secondary correction data.
In one example, if the primary correction data and the secondary correction data are the same, the filling data may be used to fill in the characteristic gas oil chromatography monitoring data, and the filled characteristic gas oil chromatography monitoring data may be used to determine the fault type of the transformer.
The invention complements the missing value of the characteristic gas by determining the missing value type, realizes the repair of complete data, and improves the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data; and the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data is improved by carrying out primary correction processing and secondary correction processing on the characteristic gas missing value filling.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for identifying a fault type of a transformer according to another embodiment of the present invention. The method specifically comprises the following steps:
step 201, acquiring characteristic gas oil chromatographic monitoring data of a transformer;
step 201 is the same as step 101, and specific reference may be made to the description of step 101, which is not repeated here.
Step 202, determining a missing value type of missing characteristic gas missing values from characteristic gas oil chromatographic monitoring data through a preset transformer oil chromatographic model;
in the embodiment of the invention, the characteristic gas oil chromatographic monitoring data can be analyzed by establishing a transformer oil chromatographic model to determine the characteristic gas missing value and the missing value type of the characteristic gas missing value.
Step 203, filling the missing value of the characteristic gas according to the type of the missing value to obtain filling data;
after the missing value type and the characteristic gas missing value are determined, the characteristic gas missing value can be filled according to the missing value type, and filling data are obtained.
In one example, the step of filling the missing value of the feature gas with the missing value according to the missing value type to obtain the filling data may include the following sub-steps:
s31, acquiring a time sequence of characteristic gas oil chromatography monitoring data;
s32, when the missing value type is a single characteristic gas missing value type, acquiring first characteristic gas signal values with the same quantity before and after the characteristic gas missing value based on a time sequence;
s33, calculating an average value of the first characteristic gas signal values;
and S34, filling the missing value of the characteristic gas by adopting the average value to obtain filling data.
In the embodiment of the invention, the missing value type can be a single characteristic gas missing value type. The process of single feature gas deficiency value filling may include: acquiring the same number of first characteristic gas signal values before and after a single characteristic gas deficiency value based on a time sequence; and then calculating an average value of the acquired first characteristic gas signal values, and filling by taking the average value as a missing value to obtain filling data.
Further, the step of filling the missing value of the feature gas according to the missing value type to obtain filled data may further include the sub-steps of:
s35, when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring continuous second characteristic gas signal values in preset time before and after the characteristic gas missing value based on a time sequence;
s36, carrying out data segmentation on all second characteristic gas signal values to obtain a plurality of segmentation results; the segmentation results are in one-to-one correspondence with a plurality of characteristic gas deficiency values;
s37, carrying out data standardization processing on the segmentation result to obtain a standardization processing result;
and S38, filling the characteristic gas missing value by adopting the standardized processing result as a filling value to obtain filling data.
In a specific implementation, if the missing value type is a plurality of continuous characteristic gas missing value types, continuous second characteristic gas signal values in a preset time before and after the plurality of characteristic gas missing values can be obtained based on a time sequence, and then all the collected second characteristic gases are subjected to segmentation processing to obtain a plurality of segmentation results; and carrying out standardization processing on the segmented result to obtain a standardization processing result, and filling the characteristic gas missing value by taking the standardization processing result as the missing value to obtain filling data. The calculation formula of the normalization process is as follows:
，i=1，...，mk；j=1，...，n；
Wherein mk is the number of samples in the data segment,normalized measurement value for the ith sample,/-for the sample>For the j-th class state quantity->Is the average value of the j-th class state quantity, +.>Is the standard deviation of the j-th class state quantity.
Step 204, performing primary correction on the filling data to obtain primary correction data;
in an embodiment of the present invention, performing a correction on the padding data may include the sub-steps of:
s41, when the missing value type is continuous to a single characteristic gas missing value type, acquiring a first voltage and a first current of the characteristic gas missing value and a second voltage and a second current in a preset time before and after the characteristic gas missing value based on a time sequence;
s42, calculating a first voltage average value of the first voltage and the second voltage, and calculating a first voltage ratio of the first voltage to the first voltage average value;
s43, calculating a first current average value of the first current and the second current, and calculating a first current ratio of the first current to the first current average value;
s44, performing primary correction on the filling data by adopting the first voltage ratio and the first current ratio to obtain primary correction data.
In a specific implementation, when the filling data of a single characteristic gas missing value type is corrected once, first voltage and first current of the single characteristic gas missing value and second voltage and second current in preset time before and after the characteristic gas missing value can be obtained based on a time sequence; then calculating a first voltage average value of the first voltage and the second voltage, and calculating a first current ratio of the first voltage to the first current average value; and calculating a first current average value of the first current and the second current, and calculating a first current ratio between the first current and the first current average value. And finally, correcting the filling data once by adopting a first voltage ratio and a first current ratio to obtain primary correction data.
Further, the step of correcting the padding data once to obtain primary correction data may further include the sub-steps of:
s45, when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring a third voltage and a third current respectively corresponding to the plurality of characteristic gas missing values and a fourth voltage and a fourth current in a preset time before and after the characteristic gas missing values based on a time sequence;
s46, calculating a second voltage average value of the third voltage and the fourth voltage, and calculating a second voltage ratio of the third voltage to the second voltage average value;
s47, calculating a second current average value of the third current and the fourth current, and calculating a second current ratio of the third current to the second current average value;
s48, performing primary correction on the filling data by adopting the second voltage ratio and the second current ratio to obtain primary correction data.
In a specific implementation, performing a correction process on the feature gas deficiency values of the plurality of continuous feature gas deficiency value types may include the following processes: acquiring a third voltage and a third current respectively corresponding to a plurality of continuous characteristic gas missing values based on a time sequence, and a fourth voltage and a fourth current in a preset time before and after the characteristic gas missing values; calculating a second voltage average value of the third voltage and the fourth voltage, and calculating a second voltage ratio of the third voltage to the second voltage average value; then calculating a second current average value between the third current and the fourth current, and calculating a second current ratio between the third current and the second current average value; and then, correcting the filling data once by adopting a second voltage ratio and a second current ratio to obtain primary correction data.
Step 205, performing secondary correction on the filling data to obtain secondary correction data;
in the embodiment of the present invention, the step of performing the secondary correction on the padding data to obtain the secondary correction data may include the following sub-steps:
s51, when the type of the missing value is continuous to a single type of the missing value of the characteristic gas, acquiring a first transformer oil temperature of the missing value of the characteristic gas and a second transformer oil temperature within a preset time before and after the missing value of the characteristic gas based on a time sequence;
s52, calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature, and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value;
and S53, carrying out secondary correction on the filling data by adopting the first oil temperature ratio to obtain secondary correction data.
In a specific implementation, when the filling data of the single characteristic gas missing value is subjected to secondary correction, firstly, the first transformer oil temperature of the single characteristic gas missing value and the second transformer oil temperature within a preset time before and after the characteristic gas missing value can be obtained based on a time sequence; then calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature, and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value; and finally, carrying out secondary correction on the filling data by adopting a first oil temperature ratio to obtain secondary correction data.
Further, the step of secondarily correcting the padding data to obtain secondary correction data may further include the sub-steps of:
s54, when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring third transformer oil temperatures respectively corresponding to the plurality of characteristic gas missing values and fourth transformer oil temperatures in preset time before and after the characteristic gas missing values based on a time sequence;
s55, calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature, and calculating a second oil temperature ratio of the third transformer oil temperature to the second oil temperature average value;
s56, performing secondary correction on the filling data by adopting the second oil temperature ratio to obtain secondary correction data.
In a specific implementation, when filling up the characteristic gas deficiency values of the plurality of continuous characteristic gas deficiency value types, firstly, third transformer oil temperatures respectively corresponding to the plurality of continuous characteristic gas deficiency values and fourth transformer oil temperatures in preset time before and after the plurality of continuous characteristic gas deficiency values can be obtained based on a time sequence; then calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature, and calculating a second oil temperature ratio between the third transformer oil temperature and the second oil temperature average value; and finally, carrying out secondary correction on the filling data by adopting a second oil temperature ratio to obtain secondary correction data.
Step 206, identifying the transformer fault type of the transformer based on the padding data when the primary correction data is the same as the secondary correction data.
In one example, if the primary correction data and the secondary correction data are the same (or the deviation is within a preset range), the characteristic gas oil chromatographic monitoring data can be padded by using the padding data, and the fault type of the transformer can be judged by using the padded characteristic gas oil chromatographic monitoring data.
If the primary correction data and the secondary correction data are different (or the deviation is larger than the preset range), the fault type judgment error can be judged, at the moment, the chromatographic model of the preset transformer oil can be adjusted, and the fault type judgment can be carried out by redetermining the fault type.
The invention complements the missing value of the characteristic gas by determining the missing value type, realizes the repair of complete data, and improves the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data; and the accuracy of identifying the fault type of the transformer according to the characteristic gas signal data is improved by carrying out primary correction processing and secondary correction processing on the characteristic gas missing value filling.
Referring to fig. 3, fig. 3 is a block diagram illustrating a compiler failure type recognition device according to an embodiment of the present invention.
The embodiment of the invention provides a transformer fault type identification device, which comprises:
the characteristic gas oil chromatography monitoring data acquisition module 301 is configured to acquire characteristic gas oil chromatography monitoring data of the transformer;
the characteristic gas deficiency value and deficiency value type determining module 302 is configured to determine a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to characteristic gas oil chromatography monitoring data;
the filling module 303 is configured to fill the missing value of the feature gas according to the missing value type, so as to obtain filling data;
the primary correction module 304 is configured to perform primary correction on the padding data to obtain primary correction data;
a secondary correction module 305, configured to perform secondary correction on the padding data to obtain secondary correction data;
the fault type identifying module 306 is configured to identify a transformer fault type of the transformer based on the padding data when the primary correction data is the same as the secondary correction data.
In the embodiment of the present invention, the characteristic gas deficiency value and deficiency value type determining module 302 includes:
the characteristic gas missing value and missing value type determining submodule is used for determining missing characteristic gas missing values and missing value types of the characteristic gas missing values from characteristic gas oil chromatography monitoring data through a preset transformer oil chromatography model.
In an embodiment of the present invention, the padding module 303 includes:
the time sequence acquisition sub-module is used for acquiring the time sequence of the characteristic gas oil chromatography monitoring data;
the first characteristic gas signal value acquisition submodule is used for acquiring the same number of first characteristic gas signal values before and after the characteristic gas missing value based on a time sequence when the missing value type is a single characteristic gas missing value type;
the average value calculation sub-module is used for calculating the average value of the first characteristic gas signal value;
and the first filling sub-module is used for filling the characteristic gas missing value by adopting the average value to obtain filling data.
In the embodiment of the present invention, the padding module 303 further includes:
the second characteristic gas signal value acquisition submodule is used for acquiring continuous second characteristic gas signal values in preset time before and after the characteristic gas missing value based on a time sequence when the missing value type is a plurality of continuous characteristic gas missing value types;
the segmentation submodule is used for carrying out data segmentation on all the second characteristic gas signal values to obtain a plurality of segmentation results; the segmentation results are in one-to-one correspondence with a plurality of characteristic gas deficiency values;
the standardized sub-module is used for carrying out data standardization processing on the segmented result to obtain a standardized processing result;
And the second filling sub-module is used for filling the characteristic gas missing value by taking the standardized processing result as a filling value to obtain filling data.
In an embodiment of the present invention, the primary correction module 304 includes:
the first voltage and current acquisition sub-module is used for acquiring a first voltage and a first current of the characteristic gas deficiency value and a second voltage and a second current in a preset time before and after the characteristic gas deficiency value based on a time sequence when the deficiency value type is continuous to a single characteristic gas deficiency value type;
the first voltage ratio calculation sub-module is used for calculating a first voltage average value of the first voltage and the second voltage and calculating a first voltage ratio of the first voltage to the first voltage average value;
the first current ratio calculation sub-module is used for calculating a first current average value of the first current and the second current and calculating a first current ratio of the first current to the first current average value;
and the first primary correction sub-module is used for carrying out primary correction on the filling data by adopting the first voltage ratio and the first current ratio to obtain primary correction data.
In an embodiment of the present invention, the primary correction module 304 further includes:
the second voltage and current acquisition sub-module is used for acquiring third voltage and third current respectively corresponding to a plurality of characteristic gas missing values based on a time sequence when the missing value type is a plurality of continuous characteristic gas missing value types, and fourth voltage and fourth current in preset time before and after the characteristic gas missing values;
The second voltage ratio calculation sub-module is used for calculating a second voltage average value of the third voltage and the fourth voltage and calculating a second voltage ratio of the third voltage to the second voltage average value;
the second current ratio calculation sub-module is used for calculating a second current average value of the third current and the fourth current and calculating a second current ratio of the third current to the second current average value;
and the second primary correction sub-module is used for carrying out primary correction on the filling data by adopting a second voltage ratio and a second current ratio to obtain primary correction data.
In an embodiment of the present invention, the secondary correction module 305 includes:
the first oil temperature acquisition submodule is used for acquiring the first transformer oil temperature of the characteristic gas deficiency value and the second transformer oil temperature within preset time before and after the characteristic gas deficiency value based on a time sequence when the deficiency value type is continuous to a single characteristic gas deficiency value type;
the first oil temperature ratio calculation sub-module is used for calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value;
and the first secondary correction sub-module is used for carrying out secondary correction on the filling data by adopting the first oil temperature ratio to obtain secondary correction data.
In an embodiment of the present invention, the secondary correction module 305 further includes:
the second oil temperature acquisition submodule is used for acquiring a third transformer oil temperature and a fourth transformer oil temperature in preset time before and after the characteristic gas deletion values corresponding to the characteristic gas deletion values respectively based on a time sequence when the deletion value type is the multiple continuous characteristic gas deletion value types;
the second oil temperature ratio calculation sub-module is used for calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature and calculating a second oil temperature ratio of the third transformer oil temperature to the second oil temperature average value;
and the second secondary correction sub-module is used for carrying out secondary correction on the filling data by adopting a second oil temperature ratio to obtain secondary correction data.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a memory:
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the transformer fault type identification method according to the embodiment of the invention according to the instructions in the program code.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. A method for identifying a type of transformer fault, comprising:
acquiring characteristic gas oil chromatographic monitoring data of a transformer;
determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data;
filling the missing value of the characteristic gas according to the missing value type to obtain filling data;
performing primary correction on the filling data to obtain primary correction data;
performing secondary correction on the filling data to obtain secondary correction data;
identifying a transformer fault type of the transformer based on the padding data when the primary correction data is the same as the secondary correction data;
and filling the missing value of the characteristic gas according to the missing value type to obtain filling data, wherein the step of filling the missing value of the characteristic gas according to the missing value type comprises the following steps:
acquiring a time sequence of the characteristic gas oil chromatography monitoring data;
when the missing value type is a single characteristic gas missing value type, acquiring the same number of first characteristic gas signal values before and after the characteristic gas missing value based on the time sequence;
calculating an average value of the first characteristic gas signal values;
Filling the characteristic gas missing value by adopting the average value to obtain filling data;
and filling the missing value of the characteristic gas according to the missing value type to obtain filling data, wherein the filling data comprises the following steps:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring continuous second characteristic gas signal values in preset time before and after the characteristic gas missing value based on the time sequence;
carrying out data segmentation on all the second characteristic gas signal values to obtain a plurality of segmentation results; the segmentation result corresponds to a plurality of the characteristic gas deficiency values one by one;
carrying out data standardization processing on the segmented result to obtain a standardized processing result;
filling the characteristic gas missing value by adopting the standardized processing result as a filling value to obtain filling data;
the step of correcting the filling data for one time to obtain one-time correction data comprises the following steps:
when the missing value type is continuous to a single characteristic gas missing value type, acquiring a first voltage and a first current of the characteristic gas missing value and a second voltage and a second current in a preset time before and after the characteristic gas missing value based on the time sequence;
Calculating a first voltage average value of the first voltage and the second voltage, and calculating a first voltage ratio of the first voltage to the first voltage average value;
calculating a first current average value of the first current and the second current, and calculating a first current ratio of the first current to the first current average value;
performing primary correction on the filling data by adopting the first voltage ratio and the first current ratio to obtain primary correction data;
the step of correcting the filling data once to obtain primary correction data further comprises the following steps:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring a plurality of third voltages and third currents respectively corresponding to the characteristic gas missing values based on the time sequence, and fourth voltages and fourth currents in preset time before and after the characteristic gas missing values;
calculating a second voltage average value of the third voltage and the fourth voltage, and calculating a second voltage ratio of the third voltage to the second voltage average value;
calculating a second current average value of the third current and the fourth current, and calculating a second current ratio of the third current to the second current average value;
Performing primary correction on the filling data by adopting the second voltage ratio and the second current ratio to obtain primary correction data;
the step of performing secondary correction on the filling data to obtain secondary correction data comprises the following steps:
when the missing value type is continuous to a single characteristic gas missing value type, acquiring a first transformer oil temperature of the characteristic gas missing value and a second transformer oil temperature within a preset time before and after the characteristic gas missing value based on the time sequence;
calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature, and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value;
performing secondary correction on the filling data by adopting the first oil temperature ratio to obtain secondary correction data;
the step of performing secondary correction on the filling data to obtain secondary correction data further comprises the following steps:
when the missing value type is a plurality of continuous characteristic gas missing value types, acquiring third transformer oil temperatures respectively corresponding to a plurality of characteristic gas missing values based on the time sequence and fourth transformer oil temperatures in preset time before and after the characteristic gas missing values;
Calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature, and calculating a second oil temperature ratio of the third transformer oil temperature to the second oil temperature average value;
and carrying out secondary correction on the filling data by adopting the second oil temperature ratio to obtain secondary correction data.
2. The method of claim 1, wherein the step of determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value from the characteristic gas oil chromatography monitoring data comprises:
and determining a missing characteristic gas missing value and a missing value type of the characteristic gas missing value from the characteristic gas oil chromatographic monitoring data through a preset transformer oil chromatographic model.
3. A transformer fault type recognition device, comprising:
the characteristic gas oil chromatography monitoring data acquisition module is used for acquiring characteristic gas oil chromatography monitoring data of the transformer;
the characteristic gas deficiency value and deficiency value type determining module is used for determining a characteristic gas deficiency value and a deficiency value type of the characteristic gas deficiency value according to the characteristic gas oil chromatography monitoring data;
the filling module is used for filling the missing value of the characteristic gas according to the missing value type to obtain filling data;
The primary correction module is used for carrying out primary correction on the filling data to obtain primary correction data;
the secondary correction module is used for carrying out secondary correction on the filling data to obtain secondary correction data;
the fault type identification module is used for identifying the transformer fault type of the transformer based on the filling data when the primary correction data are the same as the secondary correction data;
wherein, fill the module, include:
the time sequence acquisition sub-module is used for acquiring the time sequence of the characteristic gas oil chromatography monitoring data;
the first characteristic gas signal value acquisition submodule is used for acquiring the same number of first characteristic gas signal values before and after the characteristic gas missing value based on a time sequence when the missing value type is a single characteristic gas missing value type;
the average value calculation sub-module is used for calculating the average value of the first characteristic gas signal value;
the first filling sub-module is used for filling the characteristic gas missing value by adopting an average value to obtain filling data;
wherein, fill the module, still include:
the second characteristic gas signal value acquisition submodule is used for acquiring continuous second characteristic gas signal values in preset time before and after the characteristic gas missing value based on a time sequence when the missing value type is a plurality of continuous characteristic gas missing value types;
The segmentation submodule is used for carrying out data segmentation on all the second characteristic gas signal values to obtain a plurality of segmentation results; the segmentation results are in one-to-one correspondence with a plurality of characteristic gas deficiency values;
the standardized sub-module is used for carrying out data standardization processing on the segmented result to obtain a standardized processing result;
the second filling sub-module is used for filling the characteristic gas missing value by taking the standardized processing result as a filling value to obtain filling data;
wherein, the primary correction module includes:
the first voltage and current acquisition sub-module is used for acquiring a first voltage and a first current of the characteristic gas deficiency value and a second voltage and a second current in a preset time before and after the characteristic gas deficiency value based on a time sequence when the deficiency value type is continuous to a single characteristic gas deficiency value type;
the first voltage ratio calculation sub-module is used for calculating a first voltage average value of the first voltage and the second voltage and calculating a first voltage ratio of the first voltage to the first voltage average value;
the first current ratio calculation sub-module is used for calculating a first current average value of the first current and the second current and calculating a first current ratio of the first current to the first current average value;
The first primary correction submodule is used for carrying out primary correction on the filling data by adopting a first voltage ratio and a first current ratio to obtain primary correction data;
wherein, once correct the module, still include:
the second voltage and current acquisition sub-module is used for acquiring third voltage and third current respectively corresponding to a plurality of characteristic gas missing values based on a time sequence when the missing value type is a plurality of continuous characteristic gas missing value types, and fourth voltage and fourth current in preset time before and after the characteristic gas missing values;
the second voltage ratio calculation sub-module is used for calculating a second voltage average value of the third voltage and the fourth voltage and calculating a second voltage ratio of the third voltage to the second voltage average value;
the second current ratio calculation sub-module is used for calculating a second current average value of the third current and the fourth current and calculating a second current ratio of the third current to the second current average value;
the second primary correction sub-module is used for carrying out primary correction on the filling data by adopting a second voltage ratio and a second current ratio to obtain primary correction data;
wherein, the secondary correction module includes:
the first oil temperature acquisition submodule is used for acquiring the first transformer oil temperature of the characteristic gas deficiency value and the second transformer oil temperature within preset time before and after the characteristic gas deficiency value based on a time sequence when the deficiency value type is continuous to a single characteristic gas deficiency value type;
The first oil temperature ratio calculation sub-module is used for calculating a first oil temperature average value of the first transformer oil temperature and the second transformer oil temperature and calculating a first oil temperature ratio of the first transformer oil temperature to the first oil temperature average value;
the first secondary correction sub-module is used for carrying out secondary correction on the filling data by adopting a first oil temperature ratio to obtain secondary correction data;
wherein, the secondary correction module still includes:
the second oil temperature acquisition submodule is used for acquiring a third transformer oil temperature and a fourth transformer oil temperature in preset time before and after the characteristic gas deletion values corresponding to the characteristic gas deletion values respectively based on a time sequence when the deletion value type is the multiple continuous characteristic gas deletion value types;
the second oil temperature ratio calculation sub-module is used for calculating a second oil temperature average value of the third transformer oil temperature and the fourth transformer oil temperature and calculating a second oil temperature ratio of the third transformer oil temperature to the second oil temperature average value;
and the second secondary correction sub-module is used for carrying out secondary correction on the filling data by adopting a second oil temperature ratio to obtain secondary correction data.
4. An electronic device, the device comprising a processor and a memory:
The memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the transformer fault type identification method of any one of claims 1-2 according to instructions in the program code.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310458089.5A CN116165318B (en) | 2023-04-26 | 2023-04-26 | Transformer fault type identification method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310458089.5A CN116165318B (en) | 2023-04-26 | 2023-04-26 | Transformer fault type identification method and device and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116165318A CN116165318A (en) | 2023-05-26 |
| CN116165318B true CN116165318B (en) | 2023-07-18 |
Family
ID=86413537
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310458089.5A Active CN116165318B (en) | 2023-04-26 | 2023-04-26 | Transformer fault type identification method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116165318B (en) |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103149476B (en) * | 2013-02-06 | 2015-08-26 | 国家电网公司 | A kind of method for diagnosing fault of power transformer based on electricity-model of vibration |
| CN104537034B (en) * | 2014-12-22 | 2017-11-10 | 国家电网公司 | The Condition Monitoring Data cleaning method of power transmission and transforming equipment based on time series analysis |
| CN109445972B (en) * | 2018-09-21 | 2022-11-04 | 深圳供电局有限公司 | Data recovery method, device, equipment and storage medium |
| CN112668164A (en) * | 2020-12-18 | 2021-04-16 | 武汉大学 | Transformer fault diagnosis method and system for inducing ordered weighted evidence reasoning |
| CN114238297A (en) * | 2021-12-15 | 2022-03-25 | 华北电力大学 | Method and device for filling missing data of fan operation, electronic equipment and medium |
| CN114414940A (en) * | 2021-12-25 | 2022-04-29 | 国家电网有限公司 | Fault judgment method based on basic data of electricity utilization information acquisition system |
| CN115078618B (en) * | 2022-07-13 | 2023-11-07 | 广东电网有限责任公司 | Transformer oil chromatographic fault identification method and related device |
| CN115689367A (en) * | 2022-11-10 | 2023-02-03 | 云南电网有限责任公司红河供电局 | Quality improvement method for processing transformer state detection multivariable time sequence data |
-
2023
- 2023-04-26 CN CN202310458089.5A patent/CN116165318B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN116165318A (en) | 2023-05-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11544426B2 (en) | Systems and methods for enhanced sequential power system model parameter estimation | |
| Ghoneim et al. | A new approach of DGA interpretation technique for transformer fault diagnosis | |
| CN103328990B (en) | Method and apparatus for transformer diagnosis | |
| CN106505557B (en) | Remote measurement error identification method and device | |
| CN110146743A (en) | A kind of area's phase recognition methods | |
| CA2922581A1 (en) | Method and system for identifying full parameters of element by fault recording and fault locating method | |
| CN110502384A (en) | Parameter verification method, apparatus, equipment and the storage medium of electronic component | |
| CN106776324A (en) | Interface test method and device | |
| CN116165318B (en) | Transformer fault type identification method and device and electronic equipment | |
| CN114019282A (en) | Transformer fault diagnosis method based on principal component analysis and random forest phase fusion | |
| WO2023004700A1 (en) | Method and apparatus for detecting anomaly of transformer, and computer-readable storage medium | |
| CN115078618B (en) | Transformer oil chromatographic fault identification method and related device | |
| Mao et al. | Accurate estimating algorithm of transfer function for transformer FRA diagnosis | |
| CN114325484B (en) | Wiring inspection method for secondary circuit of generator voltage transformer | |
| CN110058133A (en) | A kind of electrical circuit fault electric arc wrong report optimization method based on feedback mechanism | |
| CN113066540B (en) | Method for preprocessing non-equilibrium fault sample of oil-immersed transformer | |
| CN110321425B (en) | Method and device for judging defect type of power grid | |
| CN105279085A (en) | Rule self-defining based smart substation configuration file test system and method | |
| CN112946558A (en) | Special transformer user metering abnormity monitoring method and system | |
| CN112415287A (en) | Method and system for identifying transformation ratio replacement of metering current transformer | |
| CN112816240A (en) | Fault identification method, device, equipment and storage medium of heating and ventilation equipment | |
| Liu et al. | Transformer fault diagnosis model based on iterative nearest neighbor interpolation and ensemble learning | |
| CN117407567A (en) | Alternating-current telemetry point-to-point method and system for transformer substation, computer equipment and medium | |
| CN111781534B (en) | Method and device for testing short-circuit resistance of transformer | |
| CN117130844B (en) | Hard disk testing method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |