CN102288884B - External insulation discharging detecting method based on ultraviolet light spots - Google Patents
External insulation discharging detecting method based on ultraviolet light spots Download PDFInfo
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- CN102288884B CN102288884B CN201110269518.1A CN201110269518A CN102288884B CN 102288884 B CN102288884 B CN 102288884B CN 201110269518 A CN201110269518 A CN 201110269518A CN 102288884 B CN102288884 B CN 102288884B
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Abstract
The invention provides an external insulation discharging detecting method based on ultraviolet light spots, and belongs to the technical field of detection. The external insulation discharging detecting method is used for increasing the accuracy and efficiency of external insulation discharging detection. The technical scheme of the invention is that: the external insulation discharging detecting method comprises the following steps of: firstly acquiring an ultraviolet discharging image of external insulation of electric transmission and transformation equipment by using an ultraviolet imager, obtaining edge contours of respective light spots of the ultraviolet discharging image through an active contour modeling method, calculating areas of the respective light spots according to the edge contours of the light spots, solving ratios of the areas of the respective light spots to the area of the largest light spot, and judging discharging degree and whether external insulation discharging exists. The external insulation discharging detecting method has the advantages of high calculation accuracy, high interference resistance, high automation degree and the like, and the accuracy and efficiency of the external insulation discharging detecting are greatly increased.
Description
Technical field
The present invention relates to a kind ofly for detection of power transmission and transformation equipment outer insulation discharge fault and judge the method for degree of discharge, belong to detection technique field.
Background technology
Power transmission and transforming equipment moves under atmospheric environment, easily because the reasons such as wet dirt, icing cause the electric field distortion of its external insulation, and then produces electric discharge.And electric discharge is the prerequisite that flashover occurs, be also the root of macromolecule material aging, be therefore necessary that External Insulation electric discharge detects and studies.The generation of the phenomenons such as that external insulation electric discharge is followed is sound, light, heat, electric current, the methods such as corresponding available sound, ultraviolet, infrared, leakage current detect, and wherein, the detection method based on ultraviolet is with a wide range of applications because having the advantages such as noncontact.Obtain by ultraviolet imagery how discharge severity to be processed and to be characterized after external insulation ultraviolet electric discharge image be a key point of the method, the main stream approach that current people adopt and levy discharge severity according to electric discharge hot spot area table, in ultraviolet electric discharge research due to external insulation, the image of extractible electric discharge facula area is a lot.Therefore, accurately, to take out needed ultraviolet electric discharge hot spot be the basis of carrying out ultraviolet discharge process to Quick.
The extraction of electric discharge hot spot is actually from ultraviolet electric discharge image and proposes the more shallow electric discharge facula area of color, conventional boundary operator processing can detected image edge, and there is the advantages such as computing velocity is fast, but this variation based on gradient carrys out Edge detected, easily be interfered, and the edge obtaining is discrete point, be difficult to directly calculate facula area.Mathematics morphology is closed and is closed the main spot interference removal around of ultraviolet being discharged by form, in the bianry image obtaining, 1 belongs to hot spot and 0 belongs to background, obtain facula area according to the quantity of statistics 1, the method has obtained good effect in actual applications.The further research but the method is still needed aspect following two: 1) the method is mainly for bianry image, the image that ultraviolet need to be discharged is transformed into bianry image, because field condition is changeable, in transfer process, make unavoidably facula area change, there is unavoidably the situation that background gray scale is close with discharge portion area grayscale, thereby cause the generation of error simultaneously; 2) under different situations, disturb the size of hot spot to change, in order to make morphological approach have good effect, the size of structural element should change, but is subject to changing tactful restriction.For multiple hot spot situations, the method needs follow-up profile identifying processing could obtain multiple facula areas simultaneously.In sum, the existing external insulation discharge detection method based on ultraviolet hot spot can't extract ultraviolet facula area accurately and rapidly, cannot guarantee accuracy and the detection efficiency of external insulation discharge examination, the further research of still needing.
Summary of the invention
The object of the present invention is to provide a kind of external insulation discharge detection method based on ultraviolet hot spot, to improve accuracy and the detection efficiency of external insulation discharge examination.
The alleged problem of the present invention realizes with following technical proposals:
A kind of external insulation discharge detection method based on ultraviolet hot spot, first it use ultraviolet imager to take pictures, obtain the ultraviolet electric discharge image of power transmission and transformation equipment outer insulation, then obtain the edge contour of each hot spot of ultraviolet electric discharge image and calculate each facula area according to the edge contour of hot spot by movable contour model method, finally try to achieve the ratio of each facula area and maximum facula area, and judge whether with this degree that has external insulation electric discharge and discharge
Concrete steps are as follows:
A. use ultraviolet imager to take pictures, obtain the ultraviolet electric discharge image of power transmission and transformation equipment outer insulation;
After input light enters ultraviolet imager, be first separated into visible light signal and ultraviolet signal by spectroscope, two kinds of signal imagings respectively, then stack up two kinds of images, generate the composograph that shows power transmission and transforming equipment and surface-discharge thereof;
B. obtain the edge contour of each hot spot of ultraviolet electric discharge image by movable contour model method;
C. calculate each facula area according to the edge contour of hot spot, concrete steps are as follows:
1. the maximal value and the minimum value that obtain X-axis on single light spot profile marginal point, be designated as respectively
x minwith
x max;
2. the maximal value and the minimum value that obtain Y-axis corresponding to certain X value, be designated as respectively
y xmin
with
y xmax
, to all
x min≤
x≤
x maxtraversal;
3.
l x =
y xmax
-
y xmin
, single facula area
;
4. all hot spots are calculated one by one, obtain the area of all hot spots;
D. choose maximum facula area, and try to achieve the ratio of each facula area and maximum facula area;
E. judge whether to exist the degree of external insulation electric discharge and electric discharge;
If certain facula area is greater than 0.1 with the ratio of maximum facula area, be electric discharge hot spot, otherwise for disturbing hot spot, the ratio of facula area and maximum facula area is larger, illustrates that electric discharge is more serious.
The above-mentioned external insulation discharge detection method based on ultraviolet hot spot, the method that obtains the edge contour of each hot spot of ultraviolet electric discharge image by movable contour model method is:
Adopt geometric active contour model, the citation form of model energy function is:
，
In formula
λ,
μ,
νfor weight coefficient;
Ωfor image-region; Curve (active contour)
cfor edge to be asked,
l(
c) be
clength;
u 0for initial pictures,
ufor approaching
u 0a sectionally smooth image;
Ω Cexcept image border
cimage-region in addition,
Introduce edge indicator function:
Wherein
g 0(
x,
y) be a gaussian kernel function, its energy function is:
In above formula
φfor level set function,
e intwith
e extbe defined as follows:
In above formula
h(
φ) and
δ(
φ) be defined as follows:
The gradient that obtains level set function after minimization of energy function conversion is:
Setting initial profile is the rectangle that comprises image, and above formula is order after calculating
φ=0 obtain the edge of image.
The invention has the beneficial effects as follows:
The present invention adopts movable contour model method, obtain the edge of region of discharge by solving partial differential equation, different from the algorithm of routine based on partial gradient information detected image edge, the global information of the method based on image detects hot spot edge, be difficult for being disturbed, can obtain the true edge of discharging light spot or interference hot spot, thereby can obtain accurate electric discharge facula area, so just improve the accuracy of discharge examination.
Set after initial profile, movable contour model can converge to hot spot edge and automatically without artificial participation, and for different ultraviolet electric discharge images, its initial profile is without artificial adjustment, behind acquisition hot spot edge, the selection of true electric discharge hot spot is also without artificial participation, therefore automaticity of the present invention is higher.
In sum, the present invention has that computational accuracy is high, antijamming capability is strong, automaticity advantages of higher, has greatly improved accuracy and the detection efficiency of external insulation discharge examination.
Accompanying drawing explanation
Below in conjunction with accompanying drawing, the invention will be further described.
Fig. 1 is ultraviolet discharge examination schematic diagram;
Fig. 2 is process flow diagram of the present invention;
Fig. 3 is single-spot ultraviolet electric discharge image;
Fig. 4～Fig. 8 is the edge detection results of single-spot ultraviolet electric discharge image while using respectively Sobel operator, Zerocross operator, Roberts operator, Sobel operator and Zerocross operator;
Fig. 9～Figure 12 is single-spot ultraviolet image mathematics morphology, and threshold value setting is respectively adaptive threshold, optimal threshold and size of structure element=1, the edge detection results of optimal threshold and size of structure element=2 and optimal threshold and size of structure element=5 o'clock;
Figure 13 is the edge detection results of single-spot ultraviolet image movable contour model;
Figure 14 is many hot spots ultraviolet image;
Figure 15～Figure 19 is the edge detection results of many hot spots ultraviolet electric discharge image while using respectively Sobel operator, Zerocross operator, Roberts operator, Sobel operator and Zerocross operator;
Figure 20～Figure 23 is many hot spots ultraviolet image mathematics morphology, and threshold value setting is respectively adaptive threshold, optimal threshold, size=1, optimal threshold, size=2 and optimal threshold, the edge detection results of size=5 o'clock;
Figure 24 is the edge detection results of many hot spots ultraviolet image movable contour model.
The meaning of each symbol used in literary composition:
λ,
μ,
ν, weight coefficient;
Ω, image-region;
c, edge to be asked;
l(
c),
clength;
u 0, initial pictures,
u, approach
u 0a sectionally smooth image;
Ω C, except image border
cimage-region in addition;
, edge indicator function;
g 0(
x,
y), gaussian kernel function;
φ, level set function.
Embodiment
In the shelf depreciation process of insulating surface, because compound and flyback are encouraged, electric discharge position is by the light signal of a large amount of different wave lengths of radiation, wherein comprise ultraviolet ray, ultraviolet imagery technology is to utilize special instrument to accept the UV signal of discharge generation, imaging after treatment also superposes with visible images, reaches the object of determining corona position and intensity, thereby indirectly assesses the insulation status of operational outfit the insulation defect of timely discovering device.
The acquisition principle of external insulation ultraviolet electric discharge image is as follows: signal source is irradiated by bias light (comprising visible ray, ultraviolet light and infrared light), be transferred to the ultraviolet light that has signal source self radiation of imaging lens from signal source, also have the bias light of signal source reflection.Ultraviolet imager utilizes spectroscope that the light of input is separated into two parts, and wherein a part is visible light signal, and signal is input on Visible-light CCD plate after being enhanced amplification; And another part is after ultraviolet " day is blind " optical filtering, only retain ultraviolet portion wherein, after processing, amplifier is input on ultraviolet light CCD plate.Finally, by special image processing technique, ultraviolet image and visible image are stacked up, generate the composograph of display device and surface-discharge thereof.Detect principle as shown in Figure 1, wherein UV refers to ultraviolet signal, and R refers to visible light signal.
Movable contour model
Movable contour model is proposed in 1987 by Kass at first, the basic thought of movable contour model is to think that image border is a batten that is subject to image force and external constraint power joint effect, the former makes it be tending towards significant characteristics of image, the latter retrains its shape and behavior, the size of its energy depends on shape and the position in image, it is tending towards the border of object from initial position by minimizing of energy function.Its basic derivation of energy formula is
In formula
e intfor the internal energy of activity curve, can realize continuity and the slickness of deformation process;
e extbe the external energy of activity curve, it is the continuous function of position, and for edge identification problem, it orders about active contour and shrinks the edge in image;
srepresent the arc length parameters after actual curve mapping.
Movable contour model is divided into parameter castor model and geometric active contour model.Parameter castor model is directly expressed the distortion of curve (curved surface) with the parameterized form explicitly of curve (curved surface), there is good interactivity and physical significance intuitively, but its fatal shortcoming is the curve that is difficult to process variable topological structure, geometric active contour model is converted to the evolution of low dimension curve (curved surface) implicit solution of high dimension curve (curved surface), in the method, conventional level set calculates partial differential equation, an its large feature is easy to process variable topological structure exactly, and the application in Image Edge-Detection is more and more extensive at present.Based on the theory of geometric active contour model, D.Mumford and J.Shah have proposed a kind of image partition method based on Mumford-Shah model, the method utilizes calculating energy function Minimal Realization image to cut apart, and image fuzzy or that noise is larger is still had to good effect.
The citation form of Mumford-Shah model energy function is
In formula
λ,
μ,
νfor weight coefficient;
Ωfor image-region; Curve (active contour)
cfor edge to be asked,
l(
c) be
clength;
u 0for initial pictures,
ufor approaching
u 0a sectionally smooth image;
Ω Cexcept image border
cimage-region in addition.
Level set function may be degenerated in the process of iteration, reinitialize level set function.Reinitialize processing and be a process very complicated and consuming time, unfavorable to convergence speedup.Have a kind ofly without initialized method, before model, first introduce the edge indicator function suc as formula (1) setting up.
In formula
g 0(
x,
y) be a gaussian kernel function.
Its energy function is suc as formula shown in (2).
In formula
φfor level set function.
In above formula
e intwith
e extdefinition is suc as formula shown in (3), (4).
， （4）
In above formula
h(
φ) and
δ(
φ) be defined as follows:
The gradient that obtains level set function after minimization of energy function conversion is
The initial profile of setting is the rectangle of the certain pixel of range image peripheral edge, and this model has the constraint of internal energy term, in level set movements process, without it is reinitialized, in numerical evaluation, is also greatly simplified.Formula (7) is order after calculating
φ=0 is the edge of gained image.
Facula area extracts
Movable contour model obtains multiple hot spots profile of (comprise and disturb hot spot), and the area that obtain each hot spot can be taked following operation to single profile: 1) obtain maximal value and the minimum value of the upper X-axis of contour edge point, be designated as respectively
x minwith
x max; 2) obtain maximal value and the minimum value of Y-axis corresponding to certain X value, be designated as respectively
y xmin
with
y xmax
, to all
x min≤
x≤
x maxtraversal; 3)
l x =
y xmax
-
y xmin
, area
; 4) calculate one by one and obtain all facula areas.
For single-spot problem, choose maximum area, in actual conditions, on external insulation, may there be many electric arcs, to there being multiple main spot, have more applicability in order to make to extract result, think and be greater than the effective light spot that is of certain value with the Area Ratio of maximum hot spot, this is because in electric discharge theory, is to belong to the very slight compound and flyback of the peripheral degree of main discharge to encourage when facula area is very little, useless concerning discharge characteristic extracts, can think to disturb, therefore can ignore.
Referring to accompanying drawing 2, apply step of the present invention and be:
1) adopt ultraviolet imager to obtain ultraviolet electric discharge image.
2) obtain light spot profile according to movable contour model.
3) obtain facula area according to the light spot profile obtaining.
4) when the ratio of facula area and maximum facula area is greater than 0.1 for electric discharge hot spot, otherwise for disturbing hot spot.The final ultraviolet electric discharge facula area that obtains.
Embodiment 1
Accompanying drawing 3 is for having the ultraviolet electric discharge image of single hot spot on the insulator chain obtaining with ultraviolet imager, electric discharge facula area is 345 pixels.Boundary operator result is as shown in accompanying drawing 4～Fig. 8.Obtain threshold value by adaptive threshold method, based on this threshold value, image is carried out obtaining bianry image after binary conversion treatment, this image is opened after computing and obtained image as shown in Figure 9 with mathematical morphology.When binary conversion treatment, manually constantly regulate to obtain optimal threshold, the image that the bianry image obtaining obtains after mathematical morphology is opened calculation process is as shown in accompanying drawing 10～Figure 12.Movable contour model obtains edge contour and original image as shown in Figure 13.
From accompanying drawing 4～Fig. 8, for actual ultraviolet electric discharge image, the testing result that conventional edge detection operator obtains is disturbed very large, although hot spot edge also can be identified, but the edge of the object such as shaft tower, insulator is also easy to be thought by mistake be edge to be identified by algorithm, this is because these boundary operators mainly detect based on gradient, due to, poor anti jamming capability high to image request.Therefore,, for actual ultraviolet electric discharge image, the result obtaining according to conventional edge detection operator is difficult to calculate ultraviolet facula area.From accompanying drawing 9, in the bianry image obtaining based on adaptive threshold method, the color of part background area and electric discharge hot spot solid colour, be white, obviously, obtains as being difficult in the case identification the facula area that discharges.It is because they have only utilized image local information to remove to detect profile that above two kinds of algorithms are now failed the fine electric discharge light spot profile that identifies, and can not utilize the global information of image.Therefore, their effect awaits further raising.Select, after optimal threshold, image is carried out to binary conversion treatment by artificial constantly trial, the image obtaining obtains image as shown in accompanying drawing 10～Figure 12 again after the morphology of different structure size is opened computing.Obviously, so process and can will orient hot spot, calculate to such an extent that facula area is respectively 340,328 and 324 pixels in 3 kinds of situations, error is respectively-1.45% ,-4.93% and-6.09%.There is good effect, but still need therein artificial participation, automatic capability is poor, when ultraviolet electric discharge research, relate to possibly the impact of different factors on electric discharge, in process, need to relate to the facula area identification of hundreds of even more electric discharge images, mathematics morphology needs artificial constantly trial to determine optimal threshold, and workload is too large.From accompanying drawing 13, the profile that the movable contour model method that the present invention uses obtains can better coincide with electric discharge profile, obtaining facula area is 341 pixels, error is-1.16%, obviously accuracy is also higher, the movable contour model method that what is more important the present invention adopts has been utilized image overall information preferably, and without artificial participation, automaticity is high, adaptive ability is strong.
Embodiment 2
Accompanying drawing 14 is for there being the ultraviolet electric discharge image of multiple hot spots on the insulator chain obtaining with ultraviolet imager, hot spot pixel is respectively 88,168,105 and 410 pixels from top to bottom.Conventional edge detection operator result is as shown in accompanying drawing 15～Figure 19.By adaptive threshold method, image is carried out to binary conversion treatment and obtain bianry image, then according to obtaining image as shown in Figure 20 after the image mathematical morphology unlatching computing obtaining.The artificial optimal threshold that constantly regulates when binary conversion treatment, the image that the bianry image obtaining obtains after morphology processing is as shown in accompanying drawing 21～Figure 23.Multiple edge contours that movable contour model obtains and original image are as shown in Figure 24.
Accompanying drawing 15～Figure 19 is consistent with accompanying drawing 9～Figure 12, and for many hot spots situation, conventional edge detection operator still can not correctly identify spot area, disturbs too many.Accompanying drawing 20～Figure 23 and accompanying drawing 9～Figure 12 are similar, for many hot spots situation, adaptive threshold method failure when image binaryzation, need artificial constantly trial to select to use morphological method processing after optimal threshold, result is as shown in accompanying drawing 21～Figure 23, physical dimension is selected 1 o'clock best correspondence to obtain facula area and is respectively 90,167,107 and 408 pixels, and error is respectively 2.27% ,-0.60%, 1.90% and-0.19%.Effect is pretty good, but weak point is to need artificial participation, and automaticity is poor.From accompanying drawing 24, the movable contour model method that the present invention uses is owing to having utilized preferably image overall information, obtaining light spot profile can better coincide with actual discharge light spot profile, obtain 4 facula areas and be respectively 87,166,105 and 407 pixels, error is respectively-1.14% ,-1.19%, 0% and-0.73%.Result shows that accuracy of the present invention is higher, and automaticity is high simultaneously.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (1)
1. the external insulation discharge detection method based on ultraviolet hot spot, it is characterized in that, first it use ultraviolet imager to obtain the ultraviolet electric discharge image of power transmission and transformation equipment outer insulation, then obtain the edge contour of each hot spot of ultraviolet electric discharge image and calculate each facula area according to the edge contour of hot spot by movable contour model method, finally try to achieve the ratio of each facula area and maximum facula area, and judge whether to exist the degree of external insulation electric discharge and electric discharge thereof with this:
Concrete steps are as follows:
A. use ultraviolet imager to take pictures, obtain the ultraviolet electric discharge image of power transmission and transformation equipment outer insulation;
After input light enters ultraviolet imager, be first separated into visible light signal and ultraviolet signal by spectroscope, two kinds of signal imagings respectively, then stack up two kinds of images, generate the composograph that shows power transmission and transforming equipment and surface-discharge thereof;
B. obtain the edge contour of each hot spot of ultraviolet electric discharge image by movable contour model method;
C. calculate each facula area according to the edge contour of hot spot, concrete steps are as follows:
1. the maximal value and the minimum value that obtain X-axis on single light spot profile marginal point, be designated as respectively
x minwith
x max;
2. the maximal value and the minimum value that obtain Y-axis corresponding to certain X value, be designated as respectively
y xmin
with
y xmax
, to all
x min≤
x≤
x maxtraversal;
3.
l x =
y xmax
-
y xmin
, single facula area
;
4. all hot spots are calculated one by one, obtain the area of all hot spots;
D. choose maximum facula area, and try to achieve the ratio of each facula area and maximum facula area;
E. judge whether to exist the degree of external insulation electric discharge and electric discharge:
If certain facula area is greater than 0.1 for electric discharge hot spot with the ratio of maximum facula area, otherwise for disturbing hot spot, the ratio of facula area and maximum facula area is larger, illustrates that electric discharge is more serious;
The method that obtains the edge contour of each hot spot of ultraviolet electric discharge image by movable contour model method is:
Adopt geometric active contour model, the citation form of model energy function is:
In formula
λ,
μ,
νfor weight coefficient;
Ωfor image-region; Curve active contour
cfor edge to be asked,
l(
c) be
clength;
u 0for initial pictures,
ufor approaching
u 0a sectionally smooth image;
Ω Cexcept image border
cimage-region in addition,
Introduce edge indicator function,
Wherein
g 0(
x,
y) be a gaussian kernel function, its energy function is:
，
In above formula
φfor level set function,
e intwith
e extbe defined as follows:
，
In above formula
h(
φ) and
δ(
φ) be defined as follows:
The gradient that obtains level set function after minimization of energy function conversion is:
In formula, t represents the time;
The initial profile of setting is the rectangle of the certain pixel of range image peripheral edge, and above formula is order after calculating
φ=0 obtain the edge of image.
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| CN103018640A (en) * | 2012-11-27 | 2013-04-03 | 华北电力大学（保定） | Method for testing electricity discharge intensity of corona on surface of high-voltage insulator |
| CN103149512A (en) * | 2013-02-25 | 2013-06-12 | 国网电力科学研究院武汉南瑞有限责任公司 | Insulation state assessment method of insulator based on ultraviolet imaging feature |
| CN103634565A (en) * | 2013-09-24 | 2014-03-12 | 北京环境特性研究所 | OMAP-based ultraviolet and visible light dual-channel image acquisition, processing and display system |
| CN103543394B (en) * | 2013-10-27 | 2016-02-03 | 华北电力大学（保定） | A kind of high voltage electric equipment electric discharge ultraviolet imagery quantization parameter extracting method |
| CN104035007A (en) * | 2014-06-10 | 2014-09-10 | 华北电力大学（保定） | Short-air-gap breakdown prewarning method of high-voltage electrical equipment |
| CN105004972B (en) * | 2015-06-25 | 2017-11-28 | 华北电力大学（保定） | Porcelain insulator Condition assessment of insulation method based on day blind ultraviolet imagery characteristics of image |
| CN105372562B (en) * | 2015-10-21 | 2017-07-14 | 国网新疆电力公司检修公司 | It is a kind of to utilize the method and system for setting Indexs measure EUV discharge degree |
| CN107192924A (en) * | 2017-03-21 | 2017-09-22 | 华北电力大学（保定） | A kind of non-common optical axis ultraviolet imager electric discharge point location antidote |
| CN107485840B (en) * | 2017-08-31 | 2023-10-03 | 深圳市菲普莱体育发展有限公司 | Ten thousand-frame high-speed shooting electric timer and working method thereof |
| CN107843818B (en) * | 2017-09-06 | 2020-08-14 | 同济大学 | High-voltage insulation fault diagnosis method based on heterogeneous image temperature rise and partial discharge characteristics |
| CN109345586A (en) * | 2018-11-02 | 2019-02-15 | 国网湖南省电力有限公司 | Electrical equipment discharge characteristic extracting method based on ultraviolet imagery technology |
| CN111308293A (en) * | 2020-03-27 | 2020-06-19 | 国网甘肃省电力公司电力科学研究院 | Typical defect fault identification method for electric power external insulation equipment based on ultraviolet imaging |
| CN113406448B (en) * | 2021-06-15 | 2023-05-09 | 中国铁道科学研究院集团有限公司基础设施检测研究所 | Method and device for detecting electrical state of railway insulator |
| CN114167245B (en) * | 2022-02-11 | 2022-06-17 | 国网湖北省电力有限公司超高压公司 | Intelligent detection method for partial discharge on surface of power transmission and transformation equipment and unmanned aerial vehicle fusion ultraviolet system |
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| JPH068852B2 (en) * | 1987-07-10 | 1994-02-02 | 富士電機株式会社 | Electrical insulation diagnosis method |
| CN101672885A (en) * | 2008-09-12 | 2010-03-17 | 黑龙江省电力科学研究院 | Method for on-line detecting external insulation state of electric transmission and transformation equipment |
| CN101458300B (en) * | 2008-12-26 | 2011-06-01 | 无锡市星迪仪器有限公司 | Circuit discharging detecting system |
| CN201765298U (en) * | 2010-07-23 | 2011-03-16 | 湖北省电力试验研究院 | On-site partial discharge test device for extra-high voltage converter transformer |
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