CN114076877A - High-voltage insulation state analysis method and device based on electromagnetic field big data - Google Patents
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Abstract
The invention provides a high-voltage insulation state analysis method and device based on electromagnetic field big data, wherein induced voltage data measured by a plurality of windings of a high-voltage insulation state detection sensor device form a matrix type and are marked as M; simultaneously testing the temperature, the atmospheric pressure and the humidity to form a matrix K; multiplying the two to obtain a test value matrix DC(ii) a Detecting the induction voltage generated when the good insulator normally works and multiplying the induction voltage by the temperature, humidity and atmospheric pressure matrix at the corresponding moment to establish a standard value matrix DB(ii) a Testing value matrix DCAnd the matrix D of the test values of the last time periodSComparing the similarity of the standard value matrix DB, and judging the working state of the insulator; the method for detecting the pollution accumulation of the insulator in the natural environment more accurately is provided, all factors of the environment where the insulator is located are comprehensively considered, and the pollution accumulation condition of the insulator can be accurately detected and analyzed, so that the method is favorable for detecting the pollution accumulation condition of the insulator according to the resultAnd accurate and timely response measures are taken, so that the safe and stable operation of the power grid is ensured.
Description
Technical Field
The invention relates to the technical field of sensors, in particular to a high-voltage insulation state analysis method and device based on electromagnetic field big data.
Background
The pollution degree of a high-voltage post insulator in the operation of a power transmission line is influenced by various factors, wherein the influence of atmospheric pollutants is most obvious and direct. In a natural environment, a layer of pollutants is gradually deposited on the surface of the insulator under the influence of sulfur dioxide, nitric oxide, granular dust and the like. When the accumulated dirt on the surface meets the weather with higher humidity, the soluble substances in the dirt layer are dissolved in water to form a conductive water film, so that leakage current flows along the surface of the insulator to reduce the insulating property of the insulator, and the dirt is easily caused to flash under the condition. In actual operation, due to the influence of factors such as the attribute, the shape characteristic and the climate of the high-voltage post insulator, the process of accumulating the dirt on the surface of the high-voltage post insulator is complex. The magnetic field around the high-voltage post insulator where dirt accumulates will change.
In the traditional detection method, the insulator resistance measuring method comprises the following steps: belongs to contact measurement judgment. The requirement for environment such as humidity is high during measurement, and the method is not suitable for large-area detection. Distributed voltage measurement method: and the danger is very high due to the charged contact operation. Alternating current withstand voltage method: the method is direct and reliable, but the high-voltage post insulator needs to be disassembled and replaced, and field measurement is difficult. Ultraviolet imaging: the detection can be carried out in a charged mode by utilizing electronic ultraviolet optical detection. But it needs to be performed in a high humidity environment, and as a result, is susceptible to the angle of observation, and the equipment is expensive.
Therefore, how to overcome the defects of the traditional detection method, improve the safety, accuracy and convenience of high-voltage post insulator detection, promote the development process of realizing comprehensive automation of the intelligent substation, and have important significance. And detecting the high-voltage post insulator of the power grid by using the voltage generated by the non-closed loop according to the electromagnetic induction principle. The magnetic field distribution on the surface of the high-voltage strut insulator is closely related to the leakage current and the voltage grade of the insulator, and the higher the voltage is, the higher the magnetic field intensity is. When leakage current flows on the surface of the high-voltage post insulator, a magnetic field is generated to increase the electromagnetic strength, so that induced voltage is generated, and therefore the leakage current level and the discharge condition of the high-voltage post insulator can be monitored by monitoring the trend of voltage value change.
Disclosure of Invention
In order to solve the technical problems provided by the background art, the invention provides a high-voltage insulation state analysis method and device based on electromagnetic field big data, provides a more accurate detection method for the pollution accumulation of an insulator in a natural environment, comprehensively considers all factors of the environment where the insulator is located, and can accurately detect and analyze the pollution accumulation condition of the insulator, thereby being beneficial to making accurate and timely countermeasures according to the result and further ensuring the safe and stable operation of a power grid.
In order to achieve the purpose, the invention adopts the following technical scheme:
a high-voltage insulation state analysis method based on electromagnetic field big data comprises the following steps:
step 1: designing a high-voltage insulation state detection sensor, wherein a plurality of iron cores and windings thereof are arranged in the sensor, and the measured induced voltage data of the windings form a matrix type, and the matrix is marked as M;
step 2: simultaneously testing the temperature, the atmospheric pressure and the humidity at the moment to form a matrix K;
and step 3: multiplying the corresponding induced voltage matrix M by the temperature, humidity and atmospheric pressure matrix K to obtain a matrix DC(ii) a For testing a matrix D of valuesC；
And 4, step 4: detecting the induction voltage generated when the good insulator normally works and multiplying the induction voltage by the temperature, humidity and atmospheric pressure matrix at the corresponding moment to establish a standard value matrix DB；
And 5: testing value matrix DCAnd the matrix D of the test values of the last time periodSComparing the similarity of the standard value matrix DB, and if the test value matrix D is detectedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is greater than a set value A, judging that the insulator works normally; if the value D is testedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is smaller than a set value A, judging that the insulator works abnormally; if the value D is testedCTesting value D only with standard value or one time period on itselfSAnd when one of the similarity degrees is smaller than the set value A, judging that the insulator is influenced by the ambient temperature, the atmospheric pressure or the humidity.
The high-voltage insulation state detection sensor device is used for realizing the high-voltage insulation state analysis method based on the electromagnetic field big data, the sensor comprises a plurality of C-shaped components, and the C-shaped components are stacked in a multi-layer mode from top to bottom.
Further, the C-shaped component comprises a C-shaped iron core and a winding wound on the C-shaped iron core.
Furthermore, the C-shaped iron core is formed by stacking a plurality of sheet-type silicon steel sheets, each sheet-type silicon steel sheet comprises an integral sheet and dispersible tablets, the integral sheets and the dispersible tablets are arranged in a layered mode, and air gaps are reserved among the dispersible tablets in a layer formed by the dispersible tablets.
Compared with the prior art, the invention has the beneficial effects that:
the invention relates to a non-contact insulator detection method with lower cost, which is characterized in that an induced voltage generated by an iron core in an early warning sensor for the insulation state of magnetic field type high-voltage equipment is monitored, and a matrix is established by combining environmental factors, so that a worker can reasonably monitor the insulator. The method can replace the traditional method for staff pole climbing inspection, realizes uninterrupted real-time detection, enables monitoring staff to master the pollution condition of the insulator in real time, and has important significance for safe and stable operation of a power system.
Drawings
FIG. 1 is a flow chart of a high voltage insulation status analysis method based on electromagnetic field big data according to the present invention;
FIG. 2 is a stacked structure view of 9C-shaped members according to the present invention;
FIG. 3 is a top view of FIG. 2;
FIG. 4 is a structural view of a stacked structure of 9C-shaped members according to the present invention after casting;
FIG. 5 is a top view of FIG. 4;
FIG. 6 is a structural diagram of the present invention hanging on the lower end of a high voltage insulator chain;
fig. 7 is a silicon steel sheet overlay of the C-shaped iron core of the present invention;
fig. 8 is a winding diagram of the C-shaped core of the present invention.
In the figure: 1-middle C-shaped component 2-left C-shaped component 3-right C-shaped component 4-9C-shaped components stacked integrally 5-poured device 6-high voltage insulator string 7-integral piece 8-dispersible piece 9-winding 10-C-shaped iron core 11-high voltage equipment or high voltage transmission line.
Detailed Description
The following detailed description of the present invention will be made with reference to the accompanying drawings.
As shown in fig. 1, a method for analyzing a high-voltage insulation state based on electromagnetic field big data includes the following steps:
step 1: designing a high-voltage insulation state detection sensor, wherein a plurality of iron cores and windings thereof are arranged in the sensor, and the measured induced voltage data of the windings form a matrix type, and the matrix is marked as M;
step 2: simultaneously testing the temperature, the atmospheric pressure and the humidity at the moment to form a matrix K;
and step 3: multiplying the corresponding induced voltage matrix M by the temperature, humidity and atmospheric pressure matrix K to obtain a matrix DC(ii) a For testing a matrix D of valuesC；
And 4, step 4: detecting the induction voltage generated when the good insulator normally works and multiplying the induction voltage by the temperature, humidity and atmospheric pressure matrix at the corresponding moment to establish a standard value matrix DB；
And 5: testing value matrix DCAnd the matrix D of the test values of the last time periodSComparing the similarity of the standard value matrix DB, and if the test value matrix D is detectedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is greater than a set value A, judging that the insulator works normally; if the value D is testedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is smaller than a set value A, judging that the insulator works abnormally; if the value D is testedCTesting value D only with standard value or one time period on itselfSAnd when one of the similarity degrees is smaller than the set value A, judging that the insulator is influenced by the ambient temperature, the atmospheric pressure or the humidity.
As shown in fig. 2-3, the sensor device for detecting the high-voltage insulation state for implementing the method for analyzing the high-voltage insulation state based on the electromagnetic field big data comprises 9C-shaped members, wherein the 9C-shaped members are stacked by dividing into 3 layers from top to bottom, and the first layer and the third layer have the same structure: 3C-shaped components are arranged from left to right, the middle C-shaped component 1 is downward opened, two C-shaped components at two sides (including a left C-shaped component 2 and a right C-shaped component 3) are upward opened, and the middle C-shaped component 1 is placed above the two C-shaped components at two sides; the structure of the second layer is vertically symmetrical with the structure of the first layer and the third layer: 3C-shaped components are arranged from left to right, the opening of the middle C-shaped component 1 faces upwards, the openings of the two C-shaped components on the two sides face downwards, and the middle C-shaped component 1 is placed below the two C-shaped components on the two sides; the 9C-shaped components have the same structure and are devices of an iron core structure, and the structure can reduce the volume of the iron core and simultaneously enhance the magnetic field to the maximum extent and improve the detection accuracy.
As shown in fig. 4 to 6, the stacked whole 4 of 9C-shaped members is subjected to insulation casting, and the cast device 5 has an X-shaped external shape in front view and a circular top view, and is hung on the lower end of the high-voltage insulator string 6. The overall shape after casting is close to that of the high-voltage insulator string 6, and as shown in fig. 6, when the cast device 5 is hung at the lower end of the high-voltage insulator string 6, the insulation state can be detected and the insulation height can be increased.
As shown in fig. 7-8, the C-shaped member includes a C-shaped core 10 and a winding 9 wound around the C-shaped core.
As shown in fig. 7, the C-shaped iron core 10 is formed by stacking a plurality of sheet-type silicon steel sheets, each sheet has a thickness of 0.3mm, each sheet-type silicon steel sheet includes an entire sheet 7 and dispersible tablets 8, the entire sheet 7 and the dispersible tablets 8 are arranged in a layered manner, an air gap is left between the dispersible tablets 8 in a layer composed of the dispersible tablets 8, and since the iron core silicon steel sheets have two different sectional areas, a part with a small area is saturated by a magnetic field under the action of a high magnetic field, and at this time, a redundant magnetic field passes through the air gap, so that an induced voltage value is increased, and detection accuracy can be improved.
The embodiment of the specific implementation process of the high-voltage insulation state analysis method based on the electromagnetic field big data comprises the following steps:
in practical application scenarios, the insulator generates a creepage phenomenon due to long-term dust accumulation, and when leakage current flows, a magnetic field is generated between the insulator and the insulating rod. The high-voltage insulation state detection sensor device is arranged at the bottom of the insulator, and induced voltage is generated due to magnetic field saturation. Obtaining a test value matrix D after establishing a matrix by measuring the induction voltage value through a high-voltage insulation state detection sensor deviceCAnd measuring the induced voltage generated under the condition of normal working of the good insulator and obtaining a standard value matrix DBFurther obtain the induced voltage matrix D of the last time periodS。
Each iron core in the high-voltage insulation state detection sensor device can generate induced voltage due to the electromagnetic effect principle, the induced voltage values of 9 iron cores are measured through the high-voltage insulation state detection sensor device, and the 9 data form a matrix M.
The meaning of each element in matrix M is as follows:
m1indicating the magnitude of the induced voltage generated by the left 1 iron core of the first layer;
m2indicating the magnitude of the induced voltage generated by the left 2 iron core of the first layer;
m3representing the magnitude of induced voltage generated by the left 3 iron cores of the first layer;
m4indicating the magnitude of the induced voltage generated by the left 1 iron core of the second layer;
m5indicating the magnitude of the induced voltage generated by the left 2 iron core of the second layer;
m6indicating the magnitude of the induced voltage generated by the left 3 iron core of the second layer;
m7indicating the magnitude of induced voltage generated by the left 1 iron core of the third layer;
m8the induction voltage generated by the left 2 iron core of the third layer is shown;
m9the induced voltage generated by the left 3 iron core of the third layer is shown.
Temperature, atmospheric pressure and humidity during testing form a matrix K1
Matrix K1The meaning of each element in (A) is as follows:
k1represents a temperature value;
k2represents a humidity value;
k3indicating the atmospheric pressure value.
Multiplying the corresponding induced voltage matrix by the temperature, humidity and atmospheric pressure matrix to obtain a matrix DC。
Measuring for 50 times to obtain 100 matrixes, matrix M and matrix K150 of the test value matrixes D are obtainedC(ii) a Taking n test value matrixes DCAverage value of (a).
Testing value matrix DCAnd the matrix D of the test values of the last time periodSA standard value matrix DBA comparison is made.
Standard value matrix DBThe following were used:
firstly, detecting the induced voltage generated by a working magnetic field in a good insulator normal state, and establishing a matrix N:
the meaning of each element in the matrix N is as follows:
n1indicating the magnitude of induction voltage generated by the first layer of left 1 iron core when the good insulator works normally under a standard state;
n2indicating the magnitude of the induced voltage generated by the first layer of left 2 iron cores when the good insulator works normally under a standard state;
n3indicating the magnitude of the induced voltage generated by the first layer of left 3 iron core when the good insulator works normally under the standard state;
n4indicating the magnitude of the induction voltage generated by the left 1 iron core on the second layer when the good insulator works normally under the standard state;
n5indicating the magnitude of the induction voltage generated by the left 2 iron core on the second layer when the good insulator works normally under the standard state;
n6indicating the magnitude of the induction voltage generated by the left 3 iron core of the second layer when the good insulator works normally under the standard state;
n7indicating the magnitude of the induced voltage generated by the left 1 iron core on the third layer when the good insulator works normally under the standard state;
n8indicating the magnitude of the induced voltage generated by the left 2 iron core on the third layer when the good insulator works normally under the standard state;
n9and the induction voltage generated by the left 3 iron core on the third layer when the good insulator works normally in a standard state is represented.
Further, the temperature, atmospheric pressure and humidity during the test form a matrix K2：
The meaning of the elements in matrix K is as follows:
k4the temperature value of the good insulator in the standard state during normal working is represented;
k5the humidity value of the good insulator in the normal working state is represented;
k6and the atmospheric pressure value of the good insulator in the standard state during normal operation is shown.
Further, a standard value matrix D is obtainedB。
The induced voltage value matrix P in the previous time period is as follows:
the meaning of each element in the matrix P is as follows:
p1the induction voltage generated by the first layer of left 1 iron core in the previous time period is represented;
p2the induction voltage generated by the first layer of left 2 iron core in the last time period is represented;
p3the induction voltage generated by the first layer of left 3 iron core in the last time period is represented;
p4the induction voltage generated by the left 1 iron core on the second layer in a period of time on the self is represented;
p5indicating the generation of the second layer left 2 core at a time period on itselfThe magnitude of the induced voltage;
p6the induction voltage generated by the left 3 iron core on the second layer in a period of time is represented;
p7the induction voltage generated by the left 1 iron core on the third layer in a previous time period is represented;
p8the induction voltage generated by the left 2 iron core on the third layer in a previous time period is represented;
p9the induction voltage generated by the left 1 iron core on the third layer in a previous time period is represented;
further, a matrix K is formed by the temperature, the atmospheric pressure and the humidity during the test in the previous time period3。
Matrix K3The meaning of each element in (A) is as follows:
k7representing the temperature value of the time slot on the temperature sensor;
k8representing the humidity value of the last time period of the self;
k9indicating the atmospheric pressure value over a period of time on its own.
Further, the matrix D of the last time period is obtainedS：
And solving the matrix similarity beta. Beta is more than or equal to 0 and less than or equal to 2, the smaller beta indicates the similarity of the two matrixes, and the closer beta is to 2 indicates the similarity of the two matrixes is larger.
If the value D is testedCAnd a matrix D of induced voltage values in a previous time periodsA standard value matrix DBWhen the similarity is greater than 1.65, the insulator works normally; if the test value matrix DCNumerical matrix D with the previous statesA standard value matrix DBWhen the similarity is less than 1.65, the insulator is indicated to work abnormally; if the test value matrix DCOnly with the standard value matrix DBOr the numerical matrix D of the previous statesWhen one of the similarity degrees is less than 1.65, the insulator is influenced by the ambient temperature, the atmospheric pressure or the humidity.
In conclusion, the invention provides a method for detecting an insulator on line in a non-contact manner, which has lower cost. The invention provides a high-voltage insulation state analysis method based on electromagnetic field big data, which is characterized in that an induction voltage generated by an iron core in an insulation sensor of magnetic field type high-voltage equipment is monitored, and a matrix is established by combining environmental factors, so that a worker can reasonably monitor an insulator. The invention can replace the traditional method for staff rod climbing inspection, realize uninterrupted real-time detection and enable monitoring staff to master the pollution condition of the insulator in real time. The method has important significance for safe and stable operation of the power system.
The above embodiments are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of the present invention is not limited to the above embodiments. The methods used in the above examples are conventional methods unless otherwise specified.
Claims (4)
1. A high-voltage insulation state analysis method based on electromagnetic field big data is characterized by comprising the following steps:
step 1: designing a high-voltage insulation state detection sensor, wherein a plurality of iron cores and windings thereof are arranged in the sensor, and the measured induced voltage data of the windings form a matrix type, and the matrix is marked as M;
step 2: simultaneously testing the temperature, the atmospheric pressure and the humidity at the moment to form a matrix K;
and step 3: multiplying the corresponding induced voltage matrix M by the temperature, humidity and atmospheric pressure matrix K to obtain a matrix DC(ii) a For testing a matrix D of valuesC；
And 4, step 4: detecting the induction voltage generated when the good insulator normally works and multiplying the induction voltage by the temperature, humidity and atmospheric pressure matrix at the corresponding moment to establish a standard value matrix DB；
And 5: will testValue matrix DCAnd the matrix D of the test values of the last time periodSComparing the similarity of the standard value matrix DB, and if the test value matrix D is detectedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is greater than a set value A, judging that the insulator works normally; if the value D is testedCWith the previous time period of itself to test the value DSAnd a standard value DBWhen the similarity is smaller than a set value A, judging that the insulator works abnormally; if the value D is testedCTesting value D only with standard value or one time period on itselfSAnd when one of the similarity degrees is smaller than the set value A, judging that the insulator is influenced by the ambient temperature, the atmospheric pressure or the humidity.
2. The high-voltage insulation state detection sensor device for implementing the high-voltage insulation state analysis method based on electromagnetic field big data as claimed in claim 1, wherein the sensor comprises a plurality of C-shaped members, and the plurality of C-shaped members are stacked in a plurality of layers from top to bottom.
3. The apparatus according to claim 2, wherein the C-shaped member comprises a C-shaped core and a winding wound around the C-shaped core.
4. The high-voltage insulation state detection sensor device of the high-voltage insulation state analysis method based on the electromagnetic field big data as claimed in claim 3, wherein the C-shaped iron core is formed by stacking a plurality of sheet-type silicon steel sheets, the sheet-type silicon steel sheets comprise whole sheets and dispersible tablets, the whole sheets and the dispersible tablets are arranged in layers, and air gaps are left among the dispersible tablets in the layer consisting of the dispersible tablets.
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001124816A (en) * | 1999-10-25 | 2001-05-11 | Nissin Electric Co Ltd | Insulator contamination detecting device |
| CN101661076A (en) * | 2009-09-04 | 2010-03-03 | 重庆大学 | Method for detecting pollution grade of insulator |
| CN102508036A (en) * | 2011-11-02 | 2012-06-20 | 浙江大学城市学院 | On-line remote monitoring method and device for pollution state of disk insulator |
| CN102645618A (en) * | 2012-04-16 | 2012-08-22 | 浙江清科电力科技有限公司 | Intelligent detection method and detection system device for contaminated insulator |
| US20170059643A1 (en) * | 2015-09-02 | 2017-03-02 | Aktiebolaget Skf | Partial discharge signal detection using resistive attenuation |
| CN106771806A (en) * | 2016-12-13 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | A kind of Voltage for Insulators on HV Lines surface filth state remote viewing method of telemetering and system |
| CN108680604A (en) * | 2018-05-18 | 2018-10-19 | 云南电网有限责任公司电力科学研究院 | A kind of suspension insulator pollution degree monitoring system and method |
| CN109387690A (en) * | 2018-12-06 | 2019-02-26 | 国网辽宁省电力有限公司鞍山供电公司 | A kind of portable high-pressure based on arc laminated core is wireless current detection means |
| CN210487953U (en) * | 2019-07-29 | 2020-05-08 | 海南金盘电气研究院有限公司 | Transformer core magnetic field distribution detection system |
| CN112362987A (en) * | 2020-10-28 | 2021-02-12 | 广东电网有限责任公司佛山供电局 | Lightning arrester fault diagnosis method based on robust estimation |
| CN112698164A (en) * | 2020-12-12 | 2021-04-23 | 国网辽宁省电力有限公司鞍山供电公司 | Analysis method for detecting insulation state of closed space based on C-frequency band ultraviolet rays |
| CN112731082A (en) * | 2020-12-26 | 2021-04-30 | 国网吉林省电力有限公司白城供电公司 | Insulator insulation state trend prediction method based on live-line detection technology |
| CN112881879A (en) * | 2021-04-16 | 2021-06-01 | 国网黑龙江省电力有限公司大庆供电公司 | High-voltage cable terminal partial discharge mode identification method, device and equipment |
| CN113642714A (en) * | 2021-08-27 | 2021-11-12 | 国网湖南省电力有限公司 | Insulator pollution discharge state identification method and system based on small sample learning |
-
2021
- 2021-11-19 CN CN202111389270.2A patent/CN114076877B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001124816A (en) * | 1999-10-25 | 2001-05-11 | Nissin Electric Co Ltd | Insulator contamination detecting device |
| CN101661076A (en) * | 2009-09-04 | 2010-03-03 | 重庆大学 | Method for detecting pollution grade of insulator |
| CN102508036A (en) * | 2011-11-02 | 2012-06-20 | 浙江大学城市学院 | On-line remote monitoring method and device for pollution state of disk insulator |
| CN102645618A (en) * | 2012-04-16 | 2012-08-22 | 浙江清科电力科技有限公司 | Intelligent detection method and detection system device for contaminated insulator |
| US20170059643A1 (en) * | 2015-09-02 | 2017-03-02 | Aktiebolaget Skf | Partial discharge signal detection using resistive attenuation |
| CN106771806A (en) * | 2016-12-13 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | A kind of Voltage for Insulators on HV Lines surface filth state remote viewing method of telemetering and system |
| CN108680604A (en) * | 2018-05-18 | 2018-10-19 | 云南电网有限责任公司电力科学研究院 | A kind of suspension insulator pollution degree monitoring system and method |
| CN109387690A (en) * | 2018-12-06 | 2019-02-26 | 国网辽宁省电力有限公司鞍山供电公司 | A kind of portable high-pressure based on arc laminated core is wireless current detection means |
| CN210487953U (en) * | 2019-07-29 | 2020-05-08 | 海南金盘电气研究院有限公司 | Transformer core magnetic field distribution detection system |
| CN112362987A (en) * | 2020-10-28 | 2021-02-12 | 广东电网有限责任公司佛山供电局 | Lightning arrester fault diagnosis method based on robust estimation |
| CN112698164A (en) * | 2020-12-12 | 2021-04-23 | 国网辽宁省电力有限公司鞍山供电公司 | Analysis method for detecting insulation state of closed space based on C-frequency band ultraviolet rays |
| CN112731082A (en) * | 2020-12-26 | 2021-04-30 | 国网吉林省电力有限公司白城供电公司 | Insulator insulation state trend prediction method based on live-line detection technology |
| CN112881879A (en) * | 2021-04-16 | 2021-06-01 | 国网黑龙江省电力有限公司大庆供电公司 | High-voltage cable terminal partial discharge mode identification method, device and equipment |
| CN113642714A (en) * | 2021-08-27 | 2021-11-12 | 国网湖南省电力有限公司 | Insulator pollution discharge state identification method and system based on small sample learning |
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