CN117269238B - Nondestructive testing device and method for dry-type distribution transformer winding material - Google Patents
Nondestructive testing device and method for dry-type distribution transformer winding material Download PDFInfo
- Publication number
- CN117269238B CN117269238B CN202311567467.XA CN202311567467A CN117269238B CN 117269238 B CN117269238 B CN 117269238B CN 202311567467 A CN202311567467 A CN 202311567467A CN 117269238 B CN117269238 B CN 117269238B
- Authority
- CN
- China
- Prior art keywords
- data
- dry
- distribution transformer
- temperature
- winding
- 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
- 238000004804 winding Methods 0.000 title claims abstract description 220
- 239000000463 material Substances 0.000 title claims abstract description 163
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000009659 non-destructive testing Methods 0.000 title claims description 40
- 238000010438 heat treatment Methods 0.000 claims abstract description 161
- 230000017525 heat dissipation Effects 0.000 claims abstract description 105
- 238000001514 detection method Methods 0.000 claims abstract description 88
- 238000001816 cooling Methods 0.000 claims abstract description 57
- 238000013145 classification model Methods 0.000 claims abstract description 37
- 238000012549 training Methods 0.000 claims abstract description 13
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 claims description 82
- 229910052802 copper Inorganic materials 0.000 claims description 82
- 239000010949 copper Substances 0.000 claims description 82
- 238000001914 filtration Methods 0.000 claims description 28
- 238000001073 sample cooling Methods 0.000 claims description 24
- 238000012360 testing method Methods 0.000 claims description 12
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical group [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 6
- 229910052782 aluminium Inorganic materials 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims 4
- 230000001066 destructive effect Effects 0.000 claims 2
- 230000000007 visual effect Effects 0.000 claims 2
- 238000012797 qualification Methods 0.000 abstract description 4
- 230000000694 effects Effects 0.000 description 6
- 238000012546 transfer Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000013016 damping Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000000418 atomic force spectrum Methods 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000009413 insulation Methods 0.000 description 2
- 229920001342 Bakelite® Polymers 0.000 description 1
- 241000255925 Diptera Species 0.000 description 1
- 239000004809 Teflon Substances 0.000 description 1
- 229920006362 Teflon® Polymers 0.000 description 1
- -1 aluminum-substituted copper Chemical class 0.000 description 1
- 239000004637 bakelite Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 239000012774 insulation material Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000005676 thermoelectric effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
- G01N25/20—Investigating or analyzing materials by the use of thermal means by investigating the development of heat, i.e. calorimetry, e.g. by measuring specific heat, by measuring thermal conductivity
Abstract
The invention relates to the technical field of detection of transformer winding materials, in particular to a nondestructive detection device and a nondestructive detection method for dry-type distribution transformer winding materials, wherein a target curve is established by utilizing heating thermal potential data and heating temperature data under heating control and cooling thermal potential data and cooling temperature data under heat dissipation control, then the target curve is fitted, data are cleaned in the fitting process, interference data are filtered, and the model size and model training quantity are effectively reduced; meanwhile, detection of the winding materials of the transformer is realized by using the winding material classification model, disassembly of the transformer is avoided, detection precision of the winding materials is improved when the winding materials are detected, quality qualification of the transformer is ensured, and one-key operation is realized, so that the operation is simple and convenient; the flexible temperature control of the transformer can be realized, and the transformer is ensured not to be damaged due to overhigh temperature.
Description
Technical Field
The invention relates to the technical field of transformer winding material detection, in particular to a nondestructive testing device and method for dry-type distribution transformer winding material.
Background
The quality of distribution transformers is related to the reliability and safety of the operation of the distribution network. Because the cost of copper is high and the cost of aluminum is high, a plurality of transformer manufacturers adopt an aluminum-substituted copper mode for the material of the transformer winding in order to make a profit, and hidden danger is brought to the safe operation of the power distribution network.
Chinese patent publication No. CN105223329a discloses a method for identifying materials of transformer windings based on thermoelectric effect, comprising: s1, respectively arranging a temperature sensor at one phase connector and a 0 phase connector of a three-phase connector; s2, heating one of the phase connectors, enabling a transformer phase winding loop to generate temperature difference distribution, and recording a voltage value between the one of the phase connectors and the 0 phase connector at the moment; s3, judging the material of the transformer winding according to the temperature of one of the phase connectors and the voltage value between the one of the phase connectors and the 0-phase connector; the application realizes the judgment of the material of the transformer winding through the mode of recording the voltage value, needs manual operation and records the data, has poor intelligent effect, has fewer consideration factors in the detection of the material of the transformer winding, cannot better reflect the real condition, and has low detection effect and poor detection efficiency on the material of the transformer winding.
Disclosure of Invention
The invention provides a nondestructive testing device and method for winding materials of a dry-type distribution transformer, which are used for solving the problems of large training amount, low detection precision effect of winding materials and complex operation caused by more model parameters.
The embodiment of the specification provides a nondestructive testing method for a dry-type distribution transformer winding material, which comprises the following steps:
collecting temperature rise thermoelectric potential data and temperature rise data of a copper terminal heating point of a target dry-type distribution transformer between winding connection points under heating control, and collecting temperature reduction thermoelectric potential data and temperature reduction data of the copper terminal heating point of the dry-type distribution transformer to be tested between winding connection points under heat dissipation control;
respectively establishing corresponding target curves according to the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data and the cooling temperature data;
fitting each target curve by adopting a Newton cooling formula to obtain a plurality of curve characteristic parameters;
filtering the curve characteristic parameters to obtain target characteristic parameters;
and inputting the target characteristic parameters into a trained winding material classification model to obtain a detection result of the winding material of the target dry-type distribution transformer.
Preferably, before collecting the temperature-rising thermoelectric potential data and the temperature-rising temperature data between the copper terminal heating point of the dry-type distribution transformer to be measured and the winding connection point under heating control, the method further comprises the following steps:
obtaining winding material sample data, wherein the winding material sample data comprises winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of a dry distribution transformer and a winding connection point under heating control, sample heating temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control, and sample cooling temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control;
respectively constructing corresponding sample curves according to the sample heating thermoelectric data, the sample heating temperature data, the sample cooling thermoelectric data and the sample cooling temperature data;
fitting each sample curve by adopting a Newton cooling formula to obtain characteristic parameters of 4 multiplied by 4 sample curves;
filtering the characteristic parameters of the 4 multiplied by 4 sample curves to obtain 12 sample target characteristic parameters;
Extracting characteristics of the winding material data to obtain winding material parameters;
establishing a 13-dimensional vector space based on the 12 sample target characteristic parameters and the winding material parameters;
and constructing a winding material classification model, and training the winding material classification model by using the 13-dimensional vector space to obtain a trained winding material classification model.
Preferably, the plurality of curve characteristic parameters includes 4×4 curve characteristic parameters;
the filtering the plurality of curve characteristic parameters to obtain target characteristic parameters comprises the following steps:
and filtering the parameters representing the delay characteristic in the 4 multiplied by 4 curve characteristic parameters to obtain 12 target characteristic parameters.
Preferably, the method further comprises:
and carrying out corresponding acousto-optic prompt based on the detection result, and generating a detection result report.
Preferably, the performing the corresponding acousto-optic prompt based on the detection result includes:
and when the detection result shows that the winding material of the target dry-type distribution transformer is aluminum, performing voice alarm and sending out red light warning.
Preferably, the performing the corresponding acousto-optic prompt based on the detection result further includes:
and when the detection result shows that the winding material of the target dry-type distribution transformer is copper, carrying out voice prompt and sending out green light prompt.
Preferably, the detection result report includes the temperature-raising thermoelectric data, the temperature-raising temperature data, the temperature-lowering thermoelectric data, the temperature-lowering temperature data, and the detection result;
the generating a detection result report includes:
and generating a detection result report based on the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, the cooling temperature data and the detection result.
Preferably, after generating the detection result report, the method further includes:
and displaying the detection result report on a display page or sending the detection result report to a client.
Preferably, the method further comprises:
and carrying out heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer based on a preset heat dissipation time judgment rule.
Preferably, the heat dissipation control is performed on the dry-type distribution transformer winding material nondestructive testing device based on a preset heat dissipation time judgment rule, including:
timing the heat dissipation time under the heat dissipation control;
and stopping heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment when the heat dissipation time exceeds the preset heat dissipation time.
Preferably, the heat dissipation control is performed on the dry-type distribution transformer winding material nondestructive testing device based on a preset heat dissipation time judgment rule, and the method further comprises:
detecting the temperature of a copper terminal heating point of a target dry-type distribution transformer and the ambient temperature;
calculating the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature;
and stopping heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer when the temperature difference between the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is smaller than or equal to a preset heat dissipation temperature difference threshold value.
The embodiment of the specification also provides a nondestructive testing device for the material of the dry-type distribution transformer winding, which comprises:
the data acquisition module is used for acquiring temperature-rising thermoelectric potential data and temperature-rising temperature data between the copper terminal heating point of the target dry-type distribution transformer and the winding connection point under heating control, and acquiring temperature-reducing thermoelectric potential data and temperature-reducing temperature data between the copper terminal heating point of the dry-type distribution transformer to be tested and the winding connection point under heat dissipation control;
the curve construction module is used for respectively constructing corresponding target curves according to the heating thermoelectric voltage data, the heating temperature data, the cooling thermoelectric voltage data and the cooling temperature data;
The curve fitting module is used for fitting each target curve by adopting a Newton cooling formula to obtain a plurality of curve characteristic parameters;
the parameter filtering module is used for filtering the curve characteristic parameters to obtain target characteristic parameters;
and the winding material detection module is used for inputting the target characteristic parameters into a trained winding material classification model to obtain a detection result of the winding material of the target dry-type distribution transformer.
The invention has the beneficial effects that: according to the invention, the target curve is established by utilizing the heating thermoelectric data and the heating temperature data under heating control and the cooling thermoelectric data and the cooling temperature data under heat dissipation control, then the target curve is fitted, data is cleaned in the fitting process, interference data is filtered, and the model size and the model training quantity are effectively reduced; meanwhile, detection of the winding materials of the transformer is realized by using the winding material classification model, disassembly of the transformer is avoided, detection precision of the winding materials is improved when the winding materials are detected, quality qualification of the transformer is ensured, and one-key operation is realized, so that the operation is simple and convenient; the flexible temperature control of the transformer can be realized, and the transformer is ensured not to be damaged due to overhigh temperature.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of a method for nondestructive testing of dry-type distribution transformer winding materials according to an embodiment of the present disclosure;
FIG. 2 is a schematic illustration of heat transfer provided in an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a nondestructive testing device for a dry-type distribution transformer winding material according to an embodiment of the present disclosure;
wherein the heating point 1, copper terminals 2, 3, winding connection point 4, winding 5.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals in the drawings denote the same or similar elements, components or portions, and thus a repetitive description thereof will be omitted.
The features, structures, characteristics or other details described in a particular embodiment do not exclude that may be combined in one or more other embodiments in a suitable manner, without departing from the technical idea of the invention.
In the description of specific embodiments, features, structures, characteristics, or other details described in the present invention are provided to enable one skilled in the art to fully understand the embodiments. However, it is not excluded that one skilled in the art may practice the present invention without one or more of the specific features, structures, characteristics, or other details.
The drawings shown in the figures are merely exemplary and do not necessarily include all of the content and operations/steps nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Referring to fig. 1, a schematic diagram of a nondestructive testing method for a dry-type distribution transformer winding material according to an embodiment of the present disclosure includes:
s101: collecting temperature rise thermoelectric potential data and temperature rise data of a copper terminal heating point of a target dry-type distribution transformer between winding connection points under heating control, and collecting temperature reduction thermoelectric potential data and temperature reduction data of the copper terminal heating point of the dry-type distribution transformer to be tested between winding connection points under heat dissipation control;
in a preferred embodiment, the target dry distribution transformer is electrically connected with the nondestructive testing equipment for the winding materials of the dry distribution transformer, and the box cover is opened; then, power is supplied to nondestructive testing equipment of the winding materials of the dry-type distribution transformer and the power is started; and finally, radiating the copper terminal through radiating control, and collecting cooling thermoelectric voltage data and cooling temperature data of the copper terminal heating point of the dry-type distribution transformer to be tested between the winding connection points under radiating control, thereby completing data acquisition and providing data support for a subsequent winding material classification model. The automatic heating and the flexible temperature control of the copper terminal are realized through the mode, so that the transformer is ensured not to be damaged due to overhigh temperature, and the transformer is safe and reliable; meanwhile, heat conduction is carried out through the red copper piece in the heating process, heat insulation materials such as Teflon/bakelite and the like and special structures are adopted for heat insulation of the heating plate and the red copper heat conduction piece, so that the heating plate and the red copper heat conduction piece can be detached by hands immediately after heating and cannot be scalded, the heat insulation effect is achieved on the heating plate and the red copper heat conduction piece, and meanwhile, the phenomenon that a large amount of heat loss occurs in the air due to direct exposure of the heating plate and the copper heat conduction piece is prevented, and the heating heat conduction efficiency is higher. Furthermore, the red copper heat conducting piece can be detached and replaced, and the transformer can be suitable for transformers with different specifications. The winding connection point is a physical contact point between the copper terminal and the target dry-type distribution transformer winding, the heating control comprises a start-stop heating power supply and a start-stop temperature control, the heat dissipation control comprises a start-stop heat dissipation part and a start-stop heat dissipation power supply, and the heat transfer process accords with a heat transfer formula.
S102: respectively establishing corresponding target curves according to the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data and the cooling temperature data;
s103: fitting each target curve by adopting a Newton cooling formula to obtain a plurality of curve characteristic parameters;
s104: filtering the curve characteristic parameters to obtain target characteristic parameters;
s105: and inputting the target characteristic parameters into a trained winding material classification model to obtain a detection result of the winding material of the target dry-type distribution transformer.
In a preferred embodiment, a heating thermoelectric force curve is established according to heating thermoelectric force data, a heating temperature curve is established according to heating temperature data, a cooling thermoelectric force curve is established according to cooling thermoelectric force data, a cooling temperature curve is established according to cooling temperature data, four curves, namely target curves, are obtained, then, a Newton cooling formula is adopted to fit each curve, 4 characteristic parameters are obtained, among the 4 characteristic parameters, parameters representing delay characteristics are discarded, namely, the characteristic parameters representing delay characteristics are filtered through a parameter filtering mode, each curve is equivalent to obtaining 3 characteristic parameters, 12 characteristic parameters are obtained in total for the four curves, and then the 12 characteristic parameters are input into a trained winding material classification model, so that a detection result of winding materials of the target dry-type distribution transformer is obtained. The winding materials of the target dry-type distribution transformer are obtained by utilizing the trained winding material classification model, so that the winding materials are prevented from being detected by disassembling the transformer, and the transformer is prevented from being damaged when the transformer is disassembled.
Further, before collecting the temperature-rising thermoelectric potential data and the temperature-rising temperature data between the copper terminal heating point of the dry-type distribution transformer to be tested and the winding connection point under heating control, the method further comprises the following steps:
obtaining winding material sample data, wherein the winding material sample data comprises winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of a dry distribution transformer and a winding connection point under heating control, sample heating temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control, and sample cooling temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control;
respectively constructing corresponding sample curves according to the sample heating thermoelectric data, the sample heating temperature data, the sample cooling thermoelectric data and the sample cooling temperature data;
fitting each sample curve by adopting a Newton cooling formula to obtain characteristic parameters of 4 multiplied by 4 sample curves;
filtering the characteristic parameters of the 4 multiplied by 4 sample curves to obtain 12 sample target characteristic parameters;
Extracting characteristics of the winding material data to obtain winding material parameters;
establishing a 13-dimensional vector space based on the 12 sample target characteristic parameters and the winding material parameters;
and constructing a winding material classification model, and training the winding material classification model by using the 13-dimensional vector space to obtain a trained winding material classification model.
Further, the plurality of curve characteristic parameters includes 4×4 curve characteristic parameters;
the filtering the plurality of curve characteristic parameters to obtain target characteristic parameters comprises the following steps:
and filtering the parameters representing the delay characteristic in the 4 multiplied by 4 curve characteristic parameters to obtain 12 target characteristic parameters.
In a preferred embodiment, in order to estimate the temperature of the winding connection point without disassembling the transformer, a winding material classification model needs to be pre-constructed, that is, an RNN (Recurrent Neural Network, cyclic neural network) classification model is pre-constructed, after the classification model is constructed, winding material sample data is obtained, and the winding material sample data includes winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heat dissipation control, and sample cooling thermoelectric voltage data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heat dissipation control; then, respectively constructing corresponding heating thermoelectric potential curves, heating temperature curves, cooling thermoelectric potential curves and cooling temperature curves according to sample heating thermoelectric potential data, sample heating temperature data, sample cooling thermoelectric potential data and sample cooling temperature data, wherein the temperature transfer process of a copper terminal heating point of the dry distribution transformer to a winding connection point under heat dissipation control or heating control accords with a Newton cooling formula, and the Newton cooling formula is shown as (1):
T(t0)=H+(T(t0)-H)×e -k（t0-t） （1）；
Wherein T (T0) is the temperature of a copper terminal heating point at the moment T0, H is the ambient temperature, k is a proportionality coefficient, and T0-T is the time difference;
if h=0, the above formula is:
T(t)= T(t0)×e -k（t0-t） （2）；
wherein T (T) is the temperature of the heating point of the copper terminal at the moment T, H is the ambient temperature, k is the proportionality coefficient, and T0-T is the time difference.
As can be seen from the formula (2), in the damping process of the newton cooling formula, k is a damping coefficient set by the user, after t time passes, the current temperature of the copper terminal heating point is determined by the product of the initial temperature and the damping rate, and according to newton's law, the object has a corresponding relationship in the temperature balance of heating or cooling, and the corresponding relationship is shown in the formula (3):
（3）；
wherein,for the winding node temperature, +.>Time, a, b, c, d is a characteristic parameter;
since the temperature and the thermoelectric voltage have a linear relationship, there is also a correspondence relationship between the thermoelectric voltage y and the time x, and the correspondence relationship is shown in the formula (4):
（4）；
wherein y is the winding node thermoelectric voltage.
Finally, fitting each curve by using formulas (3) and (4), obtaining four characteristic parameters a, b, c, d by each curve, filtering the characteristic parameters among the four characteristic parameters, discarding the characteristic parameter c representing the delay characteristic, namely obtaining three characteristic parameters a, b and d by each curve, and filtering out interference data by a filtering mode, thereby effectively reducing the size of the model and the training quantity of the model; and extracting the characteristic parameters g of the winding materials in the winding material data, establishing a 13-dimensional vector space according to the 13 characteristic parameters, and inputting the 13-dimensional vector space into a pre-constructed winding material classification model for training, so as to obtain a trained winding material classification model. The trained winding material classification model obtained through the method can rapidly identify winding materials in practical application, improves detection precision of the winding materials, ensures that the quality of the transformer is qualified, is operated by one key, is simple and convenient to operate, and does not need to dismount and examine the transformer.
Further, a test position parameter f can be added, the test position parameter is defined as 1 when the test position is positioned on the high-voltage side winding, the test position parameter is defined as 0 when the test position is positioned on the low-voltage side winding, so that a parameter vector space consisting of 14 parameters is formed, then the 14-dimensional vector space is input into a pre-constructed winding material classification model for training, a trained winding material classification model is obtained, and therefore the identification efficiency of the winding material classification model is further improved, and the determination of the test position is avoided.
Further, the method further comprises:
and carrying out corresponding acousto-optic prompt based on the detection result, and generating a detection result report.
Further, the performing the corresponding acousto-optic prompt based on the detection result includes:
when the detection result shows that the material of the target dry-type distribution transformer winding is aluminum, performing voice alarm and sending out red light warning;
further, the performing the corresponding acousto-optic prompt based on the detection result further includes:
and when the detection result shows that the winding material of the target dry-type distribution transformer is copper, carrying out voice prompt and sending out green light prompt.
In a preferred embodiment, different acousto-optic prompts can be given according to different detection results to avoid the need of people to watch all the time, when the detection results show that the winding material of the target dry-type distribution transformer is aluminum, the winding material is indicated to be adulterated, a voice alarm is carried out, a red light warning is sent out, a user is timely reminded of replacing the transformer, and other bad influences and dangers caused by the operation of the adulterated transformer are prevented; when the detection result shows that the winding material of the target dry-type distribution transformer is copper, the detection is qualified, the voice prompt is carried out, the green light prompt is sent, then the transformer can be put into use, the alarm and voice prompt modes are more in line with humanized requirements, and the user experience is improved.
Further, the detection result report comprises the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, the cooling temperature data and the detection result;
the generating a detection result report includes:
and generating a detection result report based on the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, the cooling temperature data and the detection result.
In a preferred embodiment, the test result report includes temperature-increasing thermoelectric data, temperature-increasing temperature data, temperature-decreasing thermoelectric data, temperature-decreasing temperature data, test results, temperature-increasing thermoelectric curve, temperature-increasing curve, temperature-decreasing thermoelectric curve, temperature-decreasing curve, etc., so that the user can later use these data in the test result report for other analysis.
Further, after generating the detection result report, the method further comprises:
and displaying the detection result report on a display page or sending the detection result report to a client.
In a preferred embodiment, the detection results are synchronously displayed on a display page of the nondestructive detection device for the winding materials of the dry-type distribution transformer. Because some electric rooms are bad in environment, air is not circulated, dust is contained, mosquitoes are contained, and the like, many people are not willing to stay in the electric rooms for a long time, detection data and result reports can be automatically sent to a client for checking, and meanwhile, one person can perform multitasking, such as another device can be taken to detect a circuit breaker in the detection process of a dry-type distribution transformer winding, user experience is improved, and humanization is realized.
Further, the method further comprises:
and carrying out heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer based on a preset heat dissipation time judgment rule.
Furthermore, the heat dissipation control of the dry-type distribution transformer winding material nondestructive testing device based on a preset heat dissipation time judgment rule comprises the following steps:
timing the heat dissipation time under the heat dissipation control;
and stopping heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment when the heat dissipation time exceeds the preset heat dissipation time.
In a preferred embodiment, rapid cooling is realized by performing heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment, when the heat dissipation control is performed, whether the heat dissipation control is stopped can be determined according to whether the heat dissipation time exceeds a preset heat dissipation time, the heat dissipation time under the heat dissipation control is firstly timed, and when the heat dissipation time exceeds the preset heat dissipation time, the heat dissipation control is stopped; and when the heat dissipation time does not exceed the preset heat dissipation time, continuing to perform heat dissipation control. For example, the preset heat dissipation time is 3 minutes, and when the timing result of the heat dissipation time under the heat dissipation control is less than or equal to 3 minutes, heat dissipation is continued; and stopping radiating when the timing result of the radiating time under the radiating control is more than 3 minutes. Through the mode, rapid cooling is realized, the detection efficiency of the dry-type distribution transformer winding material nondestructive detection equipment to the transformer can be improved, and time is saved.
Furthermore, the heat dissipation control is performed on the dry-type distribution transformer winding material nondestructive testing equipment based on a preset heat dissipation time judgment rule, and the method further comprises the following steps:
detecting the temperature of a copper terminal heating point of a target dry-type distribution transformer and the ambient temperature;
calculating the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature;
and stopping heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer when the temperature difference between the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is smaller than or equal to a preset heat dissipation temperature difference threshold value.
In a preferred embodiment, the heat dissipation control is performed by performing heat dissipation control on the nondestructive testing equipment for the material of the dry-type distribution transformer winding, namely detecting the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature, then calculating the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature, and stopping the heat dissipation control when the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is less than or equal to 5 ℃ assuming that the preset heat dissipation temperature difference threshold is set to be 5 ℃; when the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is greater than 5 ℃, heat dissipation control is continued, the rapid cooling is determined in the temperature detection mode, long-time heat dissipation is avoided, resource loss is reduced, and time is saved. Preferably, the heat dissipation control can be performed by combining a preset heat dissipation time and a preset heat dissipation temperature difference threshold, so that the heat dissipation control effect is further improved.
As shown in fig. 2, by heating the heating point 1 at the copper terminal 2, heat is transferred from the copper terminal 2 to the winding connection point 4 via the copper terminal 3, then, temperature rise thermoelectric potential data and temperature rise temperature data between the copper terminal 3 and the winding connection point 4 are collected, heat dissipation control is performed, temperature drop thermoelectric potential data and temperature drop temperature data between the copper terminal 3 and the winding connection point 4 are collected, the above data are processed, and then, the processed data are input into a trained winding material classification model, and specific materials of the winding 5 are output. According to the invention, the detection of the material of the winding of the transformer is realized by the mode, the disassembly of the dry type distribution transformer is avoided, meanwhile, the flexible temperature control of the dry type distribution transformer can be realized, the dry type distribution transformer is prevented from being damaged due to overhigh temperature, and as the winding material detection model and the winding node temperature estimation model both consider a plurality of influencing factors, the detection precision of the winding material is improved when the winding material is detected, the quality qualification of the dry type distribution transformer is ensured, and the operation is simple and convenient by one-key operation. Wherein the arrow direction in fig. 2 is the heat transfer direction.
According to the invention, the target curve is established by utilizing the heating thermoelectric data and the heating temperature data under heating control and the cooling thermoelectric data and the cooling temperature data under heat dissipation control, then the target curve is fitted, data is cleaned in the fitting process, interference data is filtered, and the model size and the model training quantity are effectively reduced; meanwhile, detection of the winding materials of the transformer is realized by using the winding material classification model, disassembly of the transformer is avoided, detection precision of the winding materials is improved when the winding materials are detected, quality qualification of the transformer is ensured, and one-key operation is realized, so that the operation is simple and convenient; the flexible temperature control of the transformer can be realized, and the transformer is ensured not to be damaged due to overhigh temperature.
Referring to fig. 3, a schematic structural diagram of a nondestructive testing device for a dry-type distribution transformer winding material according to an embodiment of the present disclosure includes:
the data acquisition module 201 is used for acquiring temperature-rising thermoelectric voltage data and temperature-rising temperature data between the copper terminal heating point of the target dry-type distribution transformer and the winding connection point under heating control, and acquiring temperature-lowering thermoelectric voltage data and temperature-lowering temperature data between the copper terminal heating point of the dry-type distribution transformer to be tested and the winding connection point under heat dissipation control;
the curve construction module 202 is configured to respectively establish a corresponding target curve according to the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, and the cooling temperature data;
the curve fitting module 203 is configured to fit each of the target curves by using a newton cooling formula, so as to obtain a plurality of curve characteristic parameters;
the parameter filtering module 204 is configured to filter the plurality of curve feature parameters to obtain a target feature parameter;
the winding material detection module 205 is configured to input the target feature parameter into a trained winding material classification model, so as to obtain a detection result of the winding material of the target dry-type distribution transformer.
Further, before the data acquisition module 201 acquires the temperature-raising thermoelectric voltage data and the temperature-raising temperature data of the copper terminal heating point of the dry-type distribution transformer to be measured between the winding connection points under heating control, the device further comprises:
the data acquisition module is used for acquiring winding material sample data, wherein the winding material sample data comprises winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of the dry-type distribution transformer and a winding connection point under heating control, sample heating temperature data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heat dissipation control, and sample cooling temperature data between a copper terminal heating point of the dry-type distribution transformer and the winding connection point under heat dissipation control;
the data processing module is used for respectively constructing corresponding sample curves according to the sample heating thermoelectric voltage data, the sample heating temperature data, the sample cooling thermoelectric voltage data and the sample cooling temperature data;
the fitting module is used for fitting each sample curve by adopting a Newton cooling formula to obtain 4 multiplied by 4 sample curve characteristic parameters;
The parameter processing module is used for filtering the 4 multiplied by 4 sample curve characteristic parameters to obtain 12 sample target characteristic parameters;
the characteristic extraction module is used for carrying out characteristic extraction on the winding material data to obtain winding material parameters;
the vector space establishing module is used for establishing a 13-dimensional vector space based on the 12 sample target characteristic parameters and the winding material parameters;
and the model training module is used for constructing a winding material classification model, and training the winding material classification model by utilizing the 13-dimensional vector space to obtain a trained winding material classification model.
Further, the plurality of curve characteristic parameters includes 4×4 curve characteristic parameters;
the parameter filtering module 204 includes:
and the parameter filtering unit is used for filtering the parameters which represent the delay characteristic in the 4 multiplied by 4 curve characteristic parameters to obtain 12 target characteristic parameters.
Further, the device further comprises:
and the report generating module is used for carrying out corresponding acousto-optic prompt based on the detection result and generating a detection result report.
Further, the report generating module includes:
the first warning unit is used for giving a voice alarm and giving a red light warning when the detection result shows that the winding material of the target dry-type distribution transformer is aluminum;
Further, the report generating module further includes:
and the second warning unit is used for carrying out voice prompt and sending out green light prompt when the detection result shows that the winding material of the target dry-type distribution transformer is copper.
Further, the detection result report comprises the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, the cooling temperature data and the detection result;
the report generating module further includes:
and the report generating unit is used for generating a detection result report based on the heating thermoelectric voltage data, the heating temperature data, the cooling thermoelectric voltage data, the cooling temperature data and the detection result.
Further, after the report generating unit generates the detection result report, the apparatus further includes:
and the detection result display module is used for displaying the detection result report on a display page or sending the detection result report to a client.
Further, the device further comprises:
and the heat dissipation control module is used for carrying out heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment based on a preset heat dissipation time judgment rule.
Further, the heat dissipation control module includes:
the heat dissipation time timing unit is used for timing the heat dissipation time under the heat dissipation control;
and the first judging unit is used for stopping heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment when the heat dissipation time exceeds the preset heat dissipation time.
Further, the heat dissipation control module further includes:
the temperature monitoring unit is used for detecting the temperature of a copper terminal heating point of the target dry-type distribution transformer and the ambient temperature;
a temperature difference calculation unit for calculating a temperature difference between a temperature of a copper terminal heating point of the target dry-type distribution transformer and the ambient temperature;
and the second judging unit is used for stopping heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment when the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is less than or equal to a preset heat dissipation temperature difference threshold value.
The invention may be implemented in hardware or in software modules running on one or more processors or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in accordance with embodiments of the present invention may be implemented in practice using a general purpose data processing device such as a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
The above-described specific embodiments further describe the objects, technical solutions and advantageous effects of the present invention in detail, and it should be understood that the present invention is not inherently related to any particular computer, virtual device or electronic apparatus, and various general-purpose devices may also implement the present invention. The foregoing description of the embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (10)
1. A nondestructive testing method for the material of a dry-type distribution transformer winding is characterized by comprising the following steps:
Collecting temperature rise thermoelectric potential data and temperature rise data of a copper terminal heating point of the target dry-type distribution transformer between the winding connection points under heating control, and collecting temperature reduction thermoelectric potential data and temperature reduction data of the copper terminal heating point of the target dry-type distribution transformer between the winding connection points under heat dissipation control;
respectively establishing corresponding target curves according to the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data and the cooling temperature data;
fitting each target curve by adopting a Newton cooling formula to obtain a plurality of curve characteristic parameters;
filtering the curve characteristic parameters to obtain target characteristic parameters;
inputting the target characteristic parameters into a trained winding material classification model to obtain a detection result of the winding material of the target dry-type distribution transformer;
before the temperature rise thermoelectric potential data and the temperature rise temperature data of the copper terminal heating point of the target dry distribution transformer between the winding connection points under heating control are acquired, the method further comprises the steps of:
obtaining winding material sample data, wherein the winding material sample data comprises winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of a dry distribution transformer and a winding connection point under heating control, sample heating temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control, and sample cooling temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control;
Respectively constructing corresponding sample curves according to the sample heating thermoelectric data, the sample heating temperature data, the sample cooling thermoelectric data and the sample cooling temperature data;
fitting each sample curve by adopting a Newton cooling formula to obtain characteristic parameters of 4 multiplied by 4 sample curves;
filtering the characteristic parameters of the 4 multiplied by 4 sample curves to obtain 12 sample target characteristic parameters;
extracting characteristics of the winding material data to obtain winding material parameters;
establishing a 13-dimensional vector space based on the 12 sample target characteristic parameters and the winding material parameters;
constructing a winding material classification model, and training the winding material classification model by using the 13-dimensional vector space to obtain a trained winding material classification model;
the plurality of curve characteristic parameters includes 4×4 curve characteristic parameters;
the filtering the plurality of curve characteristic parameters to obtain target characteristic parameters comprises the following steps:
and filtering the parameters representing the delay characteristic in the 4 multiplied by 4 curve characteristic parameters to obtain 12 target characteristic parameters.
2. A method for non-destructive testing of dry-type distribution transformer winding materials as recited in claim 1, further comprising:
And carrying out corresponding acousto-optic prompt based on the detection result, and generating a detection result report.
3. A method for non-destructive inspection of a dry-type distribution transformer winding material as set forth in claim 2, wherein said performing a corresponding audible and visual cue based on said inspection result comprises:
and when the detection result shows that the winding material of the target dry-type distribution transformer is aluminum, performing voice alarm and sending out red light warning.
4. A method for non-destructive inspection of a dry-type distribution transformer winding material as set forth in claim 2, wherein said performing a corresponding audible and visual cue based on said inspection result further comprises:
and when the detection result shows that the winding material of the target dry-type distribution transformer is copper, carrying out voice prompt and sending out green light prompt.
5. A method for non-destructive testing of dry-type distribution transformer winding materials as set forth in claim 3, wherein said test result report comprises said temperature-increasing thermoelectric data, said temperature-increasing temperature data, said temperature-decreasing thermoelectric data, said temperature-decreasing temperature data, said test result;
the generating a detection result report includes:
and generating a detection result report based on the heating thermoelectric data, the heating temperature data, the cooling thermoelectric data, the cooling temperature data and the detection result.
6. A method for non-destructive testing of a dry-type distribution transformer winding material as set forth in claim 2, further comprising, after generating the test result report:
and displaying the detection result report on a display page or sending the detection result report to a client.
7. A method for non-destructive testing of dry-type distribution transformer winding materials as recited in claim 1, further comprising:
and carrying out heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer based on a preset heat dissipation time judgment rule.
8. A method for non-destructive testing of a dry-type distribution transformer winding material as set forth in claim 7, wherein said performing a heat dissipation control on said dry-type distribution transformer winding material non-destructive testing apparatus based on a predetermined heat dissipation time judgment rule comprises:
timing the heat dissipation time under the heat dissipation control;
and stopping heat dissipation control on the dry-type distribution transformer winding material nondestructive testing equipment when the heat dissipation time exceeds the preset heat dissipation time.
9. The method for non-destructive testing of dry-type distribution transformer winding materials according to claim 7, wherein said performing heat dissipation control on said dry-type distribution transformer winding material non-destructive testing apparatus based on a preset heat dissipation time judgment rule further comprises:
Detecting the temperature of a copper terminal heating point of a target dry-type distribution transformer and the ambient temperature;
calculating the temperature difference between the temperature of the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature;
and stopping heat dissipation control on the nondestructive testing equipment for the winding materials of the dry-type distribution transformer when the temperature difference between the copper terminal heating point of the target dry-type distribution transformer and the ambient temperature is smaller than or equal to a preset heat dissipation temperature difference threshold value.
10. A dry-type distribution transformer winding material nondestructive testing device, characterized by comprising:
the data acquisition module is used for acquiring temperature-rising thermoelectric potential data and temperature-rising temperature data between the copper terminal heating point of the target dry-type distribution transformer and the winding connection point under heating control, and acquiring temperature-lowering thermoelectric potential data and temperature-lowering temperature data between the copper terminal heating point of the target dry-type distribution transformer and the winding connection point under heat dissipation control;
the curve construction module is used for respectively constructing corresponding target curves according to the heating thermoelectric voltage data, the heating temperature data, the cooling thermoelectric voltage data and the cooling temperature data;
the curve fitting module is used for fitting each target curve by adopting a Newton cooling formula to obtain a plurality of curve characteristic parameters;
The parameter filtering module is used for filtering the curve characteristic parameters to obtain target characteristic parameters;
the winding material detection module is used for inputting the target characteristic parameters into a trained winding material classification model to obtain a detection result of the winding material of the target dry-type distribution transformer;
before the temperature rise thermoelectric potential data and the temperature rise temperature data of the copper terminal heating point of the target dry distribution transformer between the winding connection points under heating control are acquired, the method further comprises the steps of:
obtaining winding material sample data, wherein the winding material sample data comprises winding material data, sample heating thermoelectric voltage data between a copper terminal heating point of a dry distribution transformer and a winding connection point under heating control, sample heating temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heating control, sample cooling thermoelectric voltage data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control, and sample cooling temperature data between a copper terminal heating point of the dry distribution transformer and the winding connection point under heat dissipation control;
respectively constructing corresponding sample curves according to the sample heating thermoelectric data, the sample heating temperature data, the sample cooling thermoelectric data and the sample cooling temperature data;
Fitting each sample curve by adopting a Newton cooling formula to obtain characteristic parameters of 4 multiplied by 4 sample curves;
filtering the characteristic parameters of the 4 multiplied by 4 sample curves to obtain 12 sample target characteristic parameters;
extracting characteristics of the winding material data to obtain winding material parameters;
establishing a 13-dimensional vector space based on the 12 sample target characteristic parameters and the winding material parameters;
constructing a winding material classification model, and training the winding material classification model by using the 13-dimensional vector space to obtain a trained winding material classification model;
the plurality of curve characteristic parameters includes 4×4 curve characteristic parameters;
the filtering the plurality of curve characteristic parameters to obtain target characteristic parameters comprises the following steps:
and filtering the parameters representing the delay characteristic in the 4 multiplied by 4 curve characteristic parameters to obtain 12 target characteristic parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311567467.XA CN117269238B (en) | 2023-11-23 | 2023-11-23 | Nondestructive testing device and method for dry-type distribution transformer winding material |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311567467.XA CN117269238B (en) | 2023-11-23 | 2023-11-23 | Nondestructive testing device and method for dry-type distribution transformer winding material |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117269238A CN117269238A (en) | 2023-12-22 |
| CN117269238B true CN117269238B (en) | 2024-01-26 |
Family
ID=89209169
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311567467.XA Active CN117269238B (en) | 2023-11-23 | 2023-11-23 | Nondestructive testing device and method for dry-type distribution transformer winding material |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117269238B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1766598A (en) * | 2005-10-14 | 2006-05-03 | 哈尔滨工业大学 | Method and apparatus for measuring material Seebeck coefficient |
| CN105223329A (en) * | 2015-09-18 | 2016-01-06 | 重庆大学 | Based on the Transformer Winding material discrimination method of thermoelectric effect |
| CN107655940A (en) * | 2017-09-18 | 2018-02-02 | 国网重庆市电力公司电力科学研究院 | A kind of Transformer Winding wood properly test equipment and system |
| CN107843618A (en) * | 2017-11-01 | 2018-03-27 | 重庆大学 | Consider the distribution transformer winding material discrimination device and method that conducting rod material influences |
| CN108680598A (en) * | 2018-05-18 | 2018-10-19 | 国网重庆市电力公司电力科学研究院 | A kind of both ends heating distribution transformer winding material lossless detection method |
| CN116203060A (en) * | 2022-12-23 | 2023-06-02 | 广东电网有限责任公司广州供电局 | Effectiveness test system and method for transformer winding material detection device |
-
2023
- 2023-11-23 CN CN202311567467.XA patent/CN117269238B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1766598A (en) * | 2005-10-14 | 2006-05-03 | 哈尔滨工业大学 | Method and apparatus for measuring material Seebeck coefficient |
| CN105223329A (en) * | 2015-09-18 | 2016-01-06 | 重庆大学 | Based on the Transformer Winding material discrimination method of thermoelectric effect |
| CN107655940A (en) * | 2017-09-18 | 2018-02-02 | 国网重庆市电力公司电力科学研究院 | A kind of Transformer Winding wood properly test equipment and system |
| CN107843618A (en) * | 2017-11-01 | 2018-03-27 | 重庆大学 | Consider the distribution transformer winding material discrimination device and method that conducting rod material influences |
| CN108680598A (en) * | 2018-05-18 | 2018-10-19 | 国网重庆市电力公司电力科学研究院 | A kind of both ends heating distribution transformer winding material lossless detection method |
| CN116203060A (en) * | 2022-12-23 | 2023-06-02 | 广东电网有限责任公司广州供电局 | Effectiveness test system and method for transformer winding material detection device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117269238A (en) | 2023-12-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114184229A (en) | Switch cabinet operation environment monitoring system | |
| CN108872820B (en) | Method and system for evaluating insulation aging state of oil impregnated paper in high-voltage current transformer | |
| CN111650501B (en) | Testing device for nondestructive online evaluation of aging state of relay | |
| KR102648764B1 (en) | Battery performance evaluation method and battery performance evaluation device | |
| CN117269238B (en) | Nondestructive testing device and method for dry-type distribution transformer winding material | |
| Das et al. | A PMU-based data-driven approach for enhancing situational awareness in building a resilient power systems | |
| Purkait et al. | An expert system for fault diagnosis in transformers during impulse tests | |
| CN116626542A (en) | Intelligent detection system of wire harness product | |
| CN115061039A (en) | Method for evaluating characteristics of connecting terminal in high-voltage circuit breaker and related equipment | |
| CA3141786C (en) | Secondary battery inspection method and secondary battery inspection device | |
| CN110058133A (en) | A kind of electrical circuit fault electric arc wrong report optimization method based on feedback mechanism | |
| CN115225455A (en) | Abnormal device detection method and device, electronic device and storage medium | |
| Artioli et al. | A general purpose software for distance monitoring and diagnosis of electrical machines | |
| CN113009329A (en) | Tripping detection method and device for external circuit breaker of electric energy meter | |
| CN117214235A (en) | Nondestructive detection device and method for winding materials | |
| CN104346982B (en) | Reliability test instructional device | |
| CN110896547B (en) | Positioning method and device for NB-IOT network problem | |
| CN106886800B (en) | Leakage current fault positioning device and method | |
| CN111157921A (en) | Detection method and device of wiring terminal, storage medium and processor | |
| CN114091984B (en) | Power transformer operation state evaluation method and equipment | |
| Han et al. | Electric shock fault diagnosis of low‐voltage residual current‐operated protective device | |
| CN219369939U (en) | Multi-parameter calibrator for relay | |
| JP2004030201A (en) | General purpose inspecting system | |
| CN114966272A (en) | Lightning arrester state online monitoring method, device, equipment and medium | |
| CN108132418B (en) | Power equipment networking monitoring system, method and device |
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 |