CN116338391A - Insulator state detection method and device, electronic equipment and medium - Google Patents
Insulator state detection method and device, electronic equipment and medium Download PDFInfo
- Publication number
- CN116338391A CN116338391A CN202310308623.4A CN202310308623A CN116338391A CN 116338391 A CN116338391 A CN 116338391A CN 202310308623 A CN202310308623 A CN 202310308623A CN 116338391 A CN116338391 A CN 116338391A
- Authority
- CN
- China
- Prior art keywords
- insulator
- detected
- parameter
- detection
- state
- 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.)
- Pending
Links
- 239000012212 insulator Substances 0.000 title claims abstract description 341
- 238000001514 detection method Methods 0.000 title claims abstract description 217
- 230000005684 electric field Effects 0.000 claims abstract description 66
- 238000000034 method Methods 0.000 claims abstract description 28
- 238000012545 processing Methods 0.000 claims description 19
- 238000004590 computer program Methods 0.000 claims description 16
- 238000004422 calculation algorithm Methods 0.000 claims description 14
- 238000003909 pattern recognition Methods 0.000 claims description 10
- 238000004140 cleaning Methods 0.000 claims description 8
- 238000005070 sampling Methods 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 5
- 239000004973 liquid crystal related substance Substances 0.000 claims description 5
- 230000005856 abnormality Effects 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims 1
- 238000011109 contamination Methods 0.000 description 10
- 230000002159 abnormal effect Effects 0.000 description 9
- 238000004891 communication Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000003066 decision tree Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001931 thermography Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1245—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of line insulators or spacers, e.g. ceramic overhead line cap insulators; of insulators in HV bushings
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/0092—Arrangements for measuring currents or voltages or for indicating presence or sign thereof measuring current only
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/52—Testing for short-circuits, leakage current or ground faults
Abstract
The invention discloses an insulator state detection method, an insulator state detection device, electronic equipment and a medium, wherein the method comprises the following steps: acquiring a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected through a transmitter in an insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model; determining a current detection parameter value of a preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter; determining a reference boundary value of a preset detection parameter of the insulator to be detected through a receiver; and determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value. According to the method, the reliability of insulator state detection can be improved by introducing a preset number of detection parameters for detecting the insulator state, the power failure probability of the power system is reduced, and the reliability of the whole power grid is further improved.
Description
Technical Field
The present invention relates to the field of machine learning technologies, and in particular, to a method and apparatus for detecting a state of an insulator, an electronic device, and a medium.
Background
The high-voltage insulator is a key component for ensuring the reliability of the power transmission and distribution overhead line, and environmental conditions such as pollution, humidity, ultraviolet rays and the like can influence the performance of the insulator and even lead to lightning and breakdown of the insulator in some cases, so that the reliability of the whole power grid can be improved by adopting a reliable on-line insulator state monitoring technology.
At present, on-line insulator state monitoring technologies mainly comprise insulator Leakage Current (LC) optical sampling, infrared thermal imaging, ultrasonic wave, acoustic fault diagnosis and array signal processing technologies, but the technologies only depend on one index to identify the insulator state, so that the situation that the reliability of monitoring the insulator state is not high often occurs.
Disclosure of Invention
The invention provides an insulator state detection method, an insulator state detection device, electronic equipment and a medium, and aims to solve the problem of low insulator state detection reliability.
According to an aspect of the present invention, there is provided an insulator status monitoring method, the method comprising:
acquiring a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected through a transmitter in an insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model;
determining a current detection parameter value of a preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter;
determining a reference boundary value of a preset detection parameter of the insulator to be detected through a receiver;
and determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
According to another aspect of the present invention, there is provided an insulator condition monitoring device, comprising:
the parameter acquisition module is used for acquiring the maximum electric field stress parameter and the insulator leakage current parameter of the insulator to be detected through a transmitter in the insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model;
the detection parameter value determining module is used for determining the current detection parameter value of the preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter;
the reference boundary value determining module is used for determining a reference boundary value of a preset detection parameter of the insulator to be detected through the receiver;
and the insulator state determining module is used for determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the insulator status detection method of any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the insulator state detection method according to any one of the embodiments of the present invention when executed.
According to the technical scheme, the maximum electric field stress parameter and the insulator leakage current parameter of the insulator to be detected are acquired, the maximum electric field stress parameter and the insulator leakage current parameter which are subjected to data processing are transmitted to the receiver of the insulator state detection model, the receiver determines the current detection parameter value of the preset detection parameter of the insulator to be detected according to the maximum electric field stress parameter and the leakage current parameter of the insulator to be detected, the receiver also needs to determine the reference boundary value of the preset detection parameter of the insulator to be detected, and the receiver determines the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an insulator status detection method according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of an insulator status detection device according to a second embodiment of the present invention;
FIG. 3 is a graph of electric field stress at heavy and extremely heavy contamination levels for an insulator provided in accordance with an embodiment of the present invention;
FIG. 4 is a graph showing an electric field stress distribution at 15cm of an insulator after applying 11kv to the insulator according to an embodiment of the present invention;
FIG. 5 is a graph showing the electric field stress distribution after applying 11kv to an insulator in clean and extremely heavily contaminated conditions and measuring 15cm from the insulator, according to an embodiment of the present invention;
FIG. 6a is a graph of insulator leakage current in a 64% humidity environment provided in accordance with an embodiment of the present invention;
FIG. 6b is a graph of insulator leakage current provided in an environment with 77% humidity according to an embodiment of the present invention;
FIG. 6c is a graph of abnormal insulator leakage current provided in an environment with 85% humidity according to an embodiment of the present invention;
FIG. 6d is a graph of abnormal insulator leakage current provided in an environment with 91% humidity according to an embodiment of the present invention;
FIG. 7a is a schematic diagram of reference boundary values of three detection parameters of an insulator to be detected by four pattern recognition algorithms according to an embodiment of the present invention;
FIG. 7b is a schematic diagram of an insulator state decision tree provided in accordance with an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an insulator status detection device according to a second embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device implementing a method for detecting a state of an insulator according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an insulator status detection method according to an embodiment of the present invention, where the method may be implemented by an insulator status detection device, and the insulator status detection device may be implemented in hardware and/or software, and the insulator status detection device may be configured in any electronic device having a network communication function. As shown in fig. 1, the method may include:
s110, acquiring a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected through a transmitter in an insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model.
As an optional but non-limiting implementation manner, collecting, by the transmitter in the insulator state detection model, the maximum electric field stress parameter and the insulator leakage current parameter of the insulator to be detected may include:
performing data processing operation on a maximum electric field stress parameter of an insulator to be detected and an insulator leakage current parameter, wherein the data processing operation comprises the following steps: noise removal, filtering and sampling operations.
Specifically, a transmitter of the insulator state detection model acquires a maximum electric field stress parameter and an insulator leakage current parameter for judging the insulator state, a data acquisition device of the transmitter of the insulator state detection model is an embedded sensor, the transmitter carries out filtering, denoising and sampling operations on the maximum electric field stress parameter and the insulator leakage current parameter, acquires the maximum electric field stress parameter and the insulator leakage current parameter with the predicted insulator state to be detected, and then transmits the maximum electric field stress parameter and the insulator leakage current parameter to a receiver of the insulator state detection model.
And S120, determining the current detection parameter value of the preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter.
Specifically, if the insulator leakage current parameter includes a third harmonic and a fifth harmonic, one of the detection parameters for evaluating the state of the insulator may be determined according to the ratio of the third harmonic and the fifth harmonic. The maximum electric field stress parameter is used for generating a second detection parameter for evaluating the state of the insulator, and a third detection parameter for evaluating the state of the insulator is determined according to the elementary phase angle of the insulator leakage current parameter.
S130, determining a reference boundary value of a preset detection parameter of the insulator to be detected through a receiver.
Specifically, the central processing unit capable of generating a reference boundary value of a preset detection parameter is embedded in the receiver of the insulator state detection model, the central processing unit determines the critical state of the insulator to be detected according to the insulator leakage current parameter waveform diagram, the detection parameter value of the insulator to be detected in the critical state is recorded, and then the reference boundary value of the preset detection parameter when the insulator to be detected is in a normal state and an abnormal state is determined.
And S140, determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
Specifically, according to the preset number of detection parameter values currently acquired for evaluating the state of the insulator to be detected, whether the detection parameter values are within the range of the reference boundary value of the detection parameter representing the state of the insulator to be detected in a normal state or not is sequentially determined, if the detection parameter values are within the range, the state of the insulator to be detected is indicated to be normal, and if the detection parameter values are not within the range, the state of the insulator to be detected is indicated to be abnormal.
The embodiment of the application provides an insulator state detection method, the maximum electric field stress parameter and the insulator leakage current parameter of an insulator to be detected are acquired, the maximum electric field stress parameter and the insulator leakage current parameter which are subjected to data processing are transmitted to a receiver of an insulator state detection model, the receiver determines the current detection parameter value of the preset detection parameter of the insulator to be detected according to the maximum electric field stress parameter and the leakage current parameter of the insulator to be detected, the receiver also needs to determine the reference boundary value of the preset detection parameter of the insulator to be detected, and the receiver determines the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
Example two
Fig. 2 is a flowchart of an insulator status detection method according to a second embodiment of the present invention, in which a process of forming a reference boundary value of a detection parameter is described in detail on the basis of the above embodiment. As shown in fig. 2, the method includes:
s210, acquiring a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected through a transmitter in an insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model.
Specifically, the maximum electric field stress parameter and the leakage current parameter of the insulator to be detected are collected through the sensor of the transmitter, the two parameters of the insulator to be detected are collected, the state of the insulator to be detected can be detected, the data collected by the insulator to be detected is subjected to data processing through the data sampling operation, the noise removing operation and the filtering operation, and then the maximum electric field stress parameter and the leakage current parameter of the insulator to be detected are transmitted to the receiver.
Illustratively, as shown in fig. 3, the electric field stress standard values of the heavy pollution and the extremely heavy pollution levels are almost similar, so that the best position of the electronic field sensor is fixed, the source distance for measuring the insulator to be detected is the best distance for collecting the data of the insulator to be detected, and the influence of the source distance on the measurement of the related data of the insulator to be detected can be reduced.
As an example, as shown in table 1, the thickness of the contamination layer of the insulator is also different at different contamination levels, so 4 contamination levels and three humidity levels are set, wherein the 4 contamination levels include light, medium, heavy and very heavy, the three humidity levels include 75%, 85% and 95%, experimental tests are performed on various types of insulators, a large number of maximum electric field stress parameters and leakage current parameters about the insulator are recorded, an embedded sensor is used to measure the electric field stress around the ground portion of the insulator, fig. 4 shows the change of the electric field stress of the insulator at 15cm after applying 11kv voltage to the insulator at different contamination levels, and it can be observed from the graph three that the maximum electric field stress parameters of the insulator occur in the middle of the line, so the sensor measuring the insulator data should be at 15cm from the insulator, and the electric field stress distribution of the insulator at 11kv under clean and very heavy contamination conditions can be obtained as shown in fig. 5.
Table 1: table of pollution level and pollution thickness of insulator
| Pollution level | Thickness of pollution (mm) |
| |
0 |
| Light pollution | 1 |
| Moderate contamination | 1.5 |
| |
2 |
| Severe pollution | 3 |
S220, determining the current detection parameter value of the preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter.
As an optional but non-limiting implementation manner, determining, by the receiver, a current detection parameter value of a preset detection parameter of the insulator to be detected according to the maximum electric field stress parameter and the insulator leakage current parameter, including steps A1-A3:
a1, acquiring a first detection parameter value according to a third harmonic peak value and a fifth harmonic peak value of the insulator leakage current to be detected, wherein the first detection parameter value is the ratio of the third harmonic peak value to the fifth harmonic peak value;
specifically, since there is a strong correlation between the state of the insulator to be detected and the first detection parameter value, the state of health of the insulator to be detected may be detected according to the first detection parameter value, where the first detection parameter value may be a ratio of a third harmonic peak value to a fifth harmonic peak value of the leakage current parameter of the insulator to be detected, and then the leakage current parameter of the insulator is adjusted to be a percentage form of the third harmonic peak value to the fifth harmonic peak value.
The first detection parameter value is calculated according to the ratio of the collected maximum electric field stress parameter and the leakage current parameter of the insulator to be detected, and the first detection parameter value calculation formula may be represented as follows:
the LC is a leakage current parameter of the insulator to be detected.
A2, acquiring a second detection parameter value according to the elementary phase angle of the leakage current of the insulator to be detected, wherein the second detection parameter value is a cosine value according to the elementary phase angle of the leakage current of the insulator;
specifically, a second detection parameter value of the state of the insulator to be detected can be obtained according to the primitive phase angle of the leakage current, the second detection parameter value can be used as a basis for detecting the state of the insulator to be detected, and a calculation formula of the second detection parameter value can be expressed as follows:
P.I％＝cos(θ I )*100％
wherein θ I Is the elementary phase angle of the leakage current of the insulator to be detected.
And A3, acquiring a third detection parameter value according to the maximum electric field stress parameter of the insulator to be detected and the flashover voltage stress in the cleaning state, wherein the third parameter value is the ratio of the maximum electric field stress parameter of the insulator to be detected and the flashover voltage stress of the insulator to be detected in the cleaning state.
Specifically, since there is a strong relationship between the change of the third detection parameter value and the state of the insulator to be detected, the third detection parameter may represent the health state of the insulator to be detected, and the third detection parameter value is the ratio of the maximum electric field stress parameter of the insulator to be detected to the flashover voltage stress of the insulator to be detected in the clean state, where the formula is as follows:
wherein E is max To actually measure the maximum electric field stress of the insulator to be detected, E ref The flashover voltage stress of the insulator to be detected in a clean state can be expressed as:
wherein U is c0 And L is the creepage distance of the insulator to be detected.
S230, determining a reference boundary value of a preset detection parameter of the insulator to be detected through a receiver.
As an alternative, but not limiting implementation, determining, by the receiver, a reference boundary value of a preset detection parameter of the insulator to be detected may include:
the state of the insulator to be detected is adjusted by simulating and adjusting pollution conditions and humidity information of the insulator to be detected, and when the insulator to be detected is in a critical state, a critical state value of the insulator to be detected is recorded and determined, wherein the critical state is that the insulator to be detected has a flashover phenomenon.
Specifically, the environment where the insulator to be detected is located is simulated and regulated, the pollution and humidity attribute change of the environment can lead to the change of the state of the insulator, along with the change of the related attribute of the environment and the change of the detection parameter value of the insulator to be detected, the insulator to be detected is abnormal and in a critical state, and when the insulator to be detected is in a flashover state, the insulator at the moment is in the critical state and the detection parameter value of the insulator at the moment is recorded.
Exemplary, the pollution and humidity conditions of the environment where the insulator to be detected is located are simulated, the state of the insulator to be detected is regulated under the conditions, the state of the insulator to be detected comprises abnormal state and critical state, when the insulator to be detected has flashover phenomenon, the insulator to be detected is in the critical state, as shown in fig. 6, the change of leakage current of the insulator under different temperatures and pollution levels is tested under the voltage level of 40kv, and fig. 6a and 6b show that the insulator is in the normal state; as shown in FIG. 6c, the insulator is flashover, and at this time, the first detection parameter value
Namely, the ratio of the third harmonic to the fifth harmonic of the leakage current is 128%, the second detection parameter value P.I% is the cosine value of the elementary phase angle of the leakage current is 85%, and the third detection parameter value MEFS% is the most significant of the insulator to be detectedThe ratio of the stress of the large electric field to the stress of the flashover voltage of the insulator to be detected in the cleaning state is 95%; as shown in FIG. 6d, the insulator leakage current curve of the insulator to be tested under heavy pollution condition is shown, wherein the insulator is subjected to flashover, the first test parameter value +.>
The abnormal range value of (2) is less than 100% and greater than 30%, while the value of the second detection parameter value P.I% is greater than 85%, and the third detection parameter value MEFS% is greater than 60%.
Illustratively, the three detection reference values are increased according to the contamination of the environment in which the insulator is located and the increase of the humidity level, so the reference boundary values of the preset detection parameter values of the insulator are summarized as shown in table 2.
Table 2: P.I% and R3/5% are suitable for different insulator conditions
For example, when the third detection parameter value MEFS% is less than 60%, the insulator is in a normal state, and when the third detection parameter value MEFS% is greater than 60%, the insulator is in an abnormal state, and thus a reference boundary value of the third detection parameter value of the insulator is determined.
As an alternative but not limiting implementation, determining, by the receiver, the reference boundary value of the preset detection parameter of the insulator to be detected may comprise steps B1-B3:
and step B1, predicting different operation modes and fault types of the insulator to be detected through simulation accidents, and determining state variables representing the insulator to be detected.
Specifically, the insulators in the power system are simulated to be in different operation modes and fault types, detection parameter values of the insulators under the different operation modes and fault types are calculated stably, and representative state variables capable of representing the insulators to be detected are selected.
And step B2, performing unsupervised learning on state variables of the insulator to be detected through a pattern recognition algorithm to determine a discriminant of the state of the insulator to be detected.
Specifically, according to step B1, a state variable which can represent the insulator to be detected is obtained, unsupervised learning is performed on the state variable of the insulator to be detected through a pattern recognition algorithm, and a discriminant of the state of the insulator is determined, wherein the pattern recognition algorithm comprises discriminant analysis, a classification tree, naive bayes and nearest neighbors.
Exemplary, as shown in fig. 7a, the insulator state discriminant is determined by detecting the reference boundary values of three detection parameter values of the insulator to be detected according to four pattern recognition algorithms of discriminant analysis, classification tree, naive bayes and nearest neighbor.
And step B3, determining a reference boundary value of the detection parameter based on a mode recognition algorithm and combining a discriminant of the insulator state to be detected.
Specifically, a decision tree algorithm based on a pattern recognition algorithm is combined with an insulator state discriminant to develop a decision tree for displaying the reference boundary value of the detection parameter and the corresponding insulator state, namely, the reference boundary value of the detection parameter is determined according to the discriminant of the insulator state.
For example, the decision tree of the insulator status can be seen in fig. 7b, and the reference boundary values of the detection parameters are determined according to the insulator status discriminant, and the insulator status and the reference boundary values of the corresponding detection parameters are shown in table 3.
Table 3: insulator state and reference boundary value of corresponding detection parameter
S240, judging whether the preset number of detection parameter values meet the reference boundary value of the detection parameter or not by acquiring the preset number of detection parameter values of the insulator to be detected.
For example, according to fig. 7b, for an insulator having a first detection parameter value greater than 32% and less than 100% and a second detection parameter value less than 70% in an abnormal state, in order to improve the reliability of diagnosis, it is proposed herein to determine a third detection parameter value of the state of the insulator, acquire the detection parameter value of the insulator to be detected through S220, and determine whether the detection parameter values of the three detection parameters all conform to the reference boundary values of the detection parameters according to table 3.
S250, if all the preset number of detection parameter values meet the limit of the reference boundary of the detection parameters, determining that the state of the insulator to be detected is normal.
Specifically, whether three detection parameter values for detecting the state of the insulator are in the display range of the detection parameter corresponding to the reference boundary value is sequentially judged, and if the detection parameter values of the three detection parameters are in the range of the reference boundary value of the detection parameter, the state of the insulator to be detected can be determined to be normal.
And S260, if the detection parameter value does not accord with the limit of the reference boundary value of the detection parameter, determining that the state of the insulator to be detected belongs to abnormality.
Specifically, whether three detection parameter values for detecting the state of the insulator are in a display range of the detection parameter corresponding to the reference boundary value is sequentially judged, and if the detection parameter values of the three detection parameters are not in the reference boundary range of the detection parameter, the state of the insulator to be detected can be determined to belong to an abnormality.
The embodiment of the application provides an insulator state detection method, the maximum electric field stress parameter and the insulator leakage current parameter of an insulator to be detected are acquired, the maximum electric field stress parameter and the insulator leakage current parameter which are subjected to data processing are transmitted to a receiver of an insulator state detection model, the receiver determines the current detection parameter value of the preset detection parameter of the insulator to be detected according to the maximum electric field stress parameter and the leakage current parameter of the insulator to be detected, the receiver also needs to train and determine the reference boundary value of the preset detection parameter of the insulator to be detected according to a pattern recognition algorithm, and the receiver determines the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
Example III
Fig. 8 is a schematic structural diagram of an insulator status detection device according to a second embodiment of the present invention, where the device may execute the insulator status detection method according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 8, the apparatus may include:
the parameter acquisition module 310 is configured to acquire, by using a transmitter in the insulator state detection model, a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected, and transmit the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model;
the detection parameter value determining module 320 is configured to determine, according to the maximum electric field stress parameter and the insulator leakage current parameter, a current detection parameter value of a preset detection parameter of the insulator to be detected through the receiver;
a reference boundary value determining module 330, configured to determine, by using the receiver, a reference boundary value of a preset detection parameter of the insulator to be detected;
the insulator status determining module 340 is configured to determine a status of the insulator to be detected according to the current detection parameter value and the reference boundary value.
Further, the parameter obtaining module includes:
performing data processing operation on a maximum electric field stress parameter of an insulator to be detected and an insulator leakage current parameter, wherein the data processing operation comprises the following steps: noise removal, filtering and sampling operations.
Further, the detection parameter value determining module includes:
the first detection parameter value acquisition unit is used for acquiring a first detection parameter value according to a third harmonic peak value and a fifth harmonic peak value of the insulator leakage current to be detected, wherein the first detection parameter value is the ratio of the third harmonic peak value to the fifth harmonic peak value;
the second detection parameter value acquisition unit is used for acquiring a second detection parameter value according to the elementary phase angle of the insulator leakage current to be detected, wherein the second detection parameter value is a cosine value according to the elementary phase angle of the insulator leakage current;
the third detection parameter value acquisition unit is used for acquiring a third detection parameter value according to the maximum electric field stress parameter of the insulator to be detected and the flashover voltage stress in the cleaning state, wherein the third parameter value is the ratio of the maximum electric field stress parameter of the insulator to be detected to the flashover voltage stress of the insulator to be detected in the cleaning state.
Further, the reference boundary value determining module includes:
the state of the insulator to be detected is adjusted by simulating and adjusting pollution conditions and humidity information of the insulator to be detected, and when the insulator to be detected is in a critical state, a critical state value of the insulator to be detected is recorded and determined, wherein the critical state is that the insulator to be detected has a flashover phenomenon.
Further, the reference boundary value determining module further includes:
the state variable determining unit is used for predicting different operation modes and fault types of the insulator to be detected through simulation accidents and determining state variables representing the insulator to be detected;
the discriminant determining unit is used for performing unsupervised learning on the state variable of the insulator to be detected through a pattern recognition algorithm to determine the discriminant of the state of the insulator to be detected;
and the reference boundary value determining unit is used for determining the reference boundary value of the detection parameter based on a mode recognition algorithm and a discriminant of the insulator state to be detected.
Further, the insulator status determination module includes:
judging whether the preset number of detection parameter values meet the reference boundary value of the detection parameter or not by acquiring the preset number of detection parameter values of the insulator to be detected;
if all the preset number of detection parameter values meet the limit of the reference boundary of the detection parameters, determining that the state of the insulator to be detected is normal;
if the detection parameter value does not accord with the limit of the reference boundary value of the detection parameter, determining that the insulator state to be detected belongs to abnormality.
The insulator state detection device provided by the embodiment of the invention can execute the insulator state detection method provided by any embodiment of the invention, has the corresponding functions and beneficial effects of executing the insulator state detection method, and the detailed process refers to the related operation of the insulator state detection method in the embodiment.
Example IV
Fig. 9 shows a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 9, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the respective methods and processes described above, such as the insulator state detection method.
In some embodiments, the insulator status detection method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the insulator state detection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the insulator status detection processing method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. An insulator state detection method, characterized by comprising:
acquiring a maximum electric field stress parameter and an insulator leakage current parameter of an insulator to be detected through a transmitter in an insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model;
determining a current detection parameter value of a preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter;
determining a reference boundary value of a preset detection parameter of the insulator to be detected through a receiver;
and determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
2. The method of claim 1, wherein the step of collecting, by the transmitter in the insulator status detection model, the maximum electric field stress parameter and the insulator leakage current parameter of the insulator to be detected comprises:
performing data processing operation on a maximum electric field stress parameter of an insulator to be detected and an insulator leakage current parameter, wherein the data processing operation comprises the following steps: noise removal, filtering and sampling operations.
3. The method of claim 1, wherein determining, by the receiver, a current detection parameter value for a preset detection parameter for an insulator to be detected based on the maximum electric field stress parameter and an insulator leakage current parameter, comprises:
acquiring a first detection parameter value according to a third harmonic peak value and a fifth harmonic peak value of the insulator leakage current to be detected, wherein the first detection parameter value is the ratio of the third harmonic peak value to the fifth harmonic peak value;
acquiring a second detection parameter value according to the elementary phase angle of the insulator leakage current to be detected, wherein the second detection parameter value is a cosine value according to the elementary phase angle of the insulator leakage current;
and acquiring a third detection parameter value according to the maximum electric field stress parameter of the insulator to be detected and the flashover voltage stress in the cleaning state, wherein the third parameter value is the ratio of the maximum electric field stress parameter of the insulator to be detected and the flashover voltage stress of the insulator to be detected in the cleaning state.
4. The method according to claim 1, wherein determining, by the receiver, a reference boundary value of a preset detection parameter of the insulator to be detected, comprises:
the state of the insulator to be detected is adjusted by simulating and adjusting pollution conditions and humidity information of the insulator to be detected, and when the insulator to be detected is in a critical state, a critical state value of the insulator to be detected is recorded and determined, wherein the critical state is that the insulator to be detected has a flashover phenomenon.
5. The method according to claim 1, wherein determining, by the receiver, a reference boundary value of a preset detection parameter of the insulator to be detected, comprises:
predicting different operation modes and fault types of the insulator to be detected through simulation accidents, and determining state variables representing the insulator to be detected;
performing unsupervised learning on state variables of the insulator to be detected through a pattern recognition algorithm to determine a discriminant of the state of the insulator to be detected;
and determining a reference boundary value of the detection parameter based on a pattern recognition algorithm and a discriminant of the insulator state to be detected.
6. The method of claim 1, determining a state of the insulator to be inspected based on the current inspection parameter value and the reference boundary value, comprising:
judging whether the preset number of detection parameter values meet the reference boundary value of the detection parameter or not by acquiring the preset number of detection parameter values of the insulator to be detected;
if all the preset number of detection parameter values meet the limit of the reference boundary of the detection parameters, determining that the state of the insulator to be detected is normal;
if the detection parameter value does not accord with the limit of the reference boundary value of the detection parameter, determining that the insulator state to be detected belongs to abnormality.
7. An insulator condition detection device, comprising:
the parameter acquisition module is used for acquiring the maximum electric field stress parameter and the insulator leakage current parameter of the insulator to be detected through a transmitter in the insulator state detection model, and transmitting the maximum electric field stress parameter and the insulator leakage current parameter to a receiver in the insulator state detection model;
the detection parameter value determining module is used for determining the current detection parameter value of the preset detection parameter of the insulator to be detected through the receiver according to the maximum electric field stress parameter and the insulator leakage current parameter;
the reference boundary value determining module is used for determining a reference boundary value of a preset detection parameter of the insulator to be detected through the receiver;
and the insulator state determining module is used for determining the state of the insulator to be detected according to the current detection parameter value and the reference boundary value.
8. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the insulator status detection method of any one of claims 1-6.
9. A computer readable storage medium storing computer instructions for causing a processor to perform the insulator status detection method of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310308623.4A CN116338391A (en) | 2023-03-24 | 2023-03-24 | Insulator state detection method and device, electronic equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310308623.4A CN116338391A (en) | 2023-03-24 | 2023-03-24 | Insulator state detection method and device, electronic equipment and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116338391A true CN116338391A (en) | 2023-06-27 |
Family
ID=86892612
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310308623.4A Pending CN116338391A (en) | 2023-03-24 | 2023-03-24 | Insulator state detection method and device, electronic equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116338391A (en) |
-
2023
- 2023-03-24 CN CN202310308623.4A patent/CN116338391A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Bhui et al. | Application of recurrence quantification analysis to power system dynamic studies | |
| CN115683230B (en) | Method, device, equipment, medium and system for detecting faults of oil immersed transformer | |
| CN111090024A (en) | GIS state evaluation method and device based on external thermal and acoustic characteristic information | |
| CN116679161A (en) | Power grid line fault diagnosis method, equipment and medium | |
| CN117129815B (en) | Comprehensive detection method and system for multi-degradation insulator based on Internet of things | |
| CN116758056B (en) | Electrical terminal production defect detection method | |
| CN116124903B (en) | Defect early warning method, device, system, equipment and medium for insulator | |
| CN115951185A (en) | Insulator flashover detection method and device, electronic equipment and storage medium | |
| CN116957539A (en) | Cable state evaluation method, device, electronic equipment and storage medium | |
| CN116338391A (en) | Insulator state detection method and device, electronic equipment and medium | |
| CN115343579B (en) | Power grid fault analysis method and device and electronic equipment | |
| CN114818830A (en) | Map-based discharge type identification method, device, equipment and medium | |
| CN114636883A (en) | Alternating current based power system fault determination method and device and storage medium | |
| Lasalvia et al. | Intelligent acoustic detection of defective porcelain station post insulators | |
| CN116127326B (en) | Composite insulator detection method and device, electronic equipment and storage medium | |
| CN111505420B (en) | Online monitoring and diagnosing method and system for state of line arrester | |
| CN117970029A (en) | Power cable fault diagnosis method and system based on multi-mode traveling wave transmission | |
| Zhang et al. | Angle steel tower bolt defect detection based on YOLO-V3 | |
| CN117434403A (en) | Partial discharge detection method and device for electric appliance | |
| CN117761456A (en) | Power distribution network fault diagnosis method, device, equipment and storage medium | |
| CN117630575A (en) | Line lightning stroke fault determining method, device, equipment and storage medium | |
| CN117368711A (en) | Method, device, equipment and medium for evaluating health state of high-voltage switch cabinet | |
| CN116430157A (en) | Online determination method, device and equipment for aging state of lightning arrester and storage medium | |
| CN117783849A (en) | Isolation switch fault determination method, device and system and storage medium | |
| CN116304798A (en) | Partial discharge type identification method, device, equipment and medium |
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 |