CN109856088A - A kind of on-line and non-contact inspection method of the attached husky density of insulator surface - Google Patents
A kind of on-line and non-contact inspection method of the attached husky density of insulator surface Download PDFInfo
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Abstract
The invention discloses a kind of on-line and non-contact inspection methods of the attached husky density of insulator surface, it establishes attached husky Density Detection model according to the high spectrum image of the insulating trip of different attached husky density first, then, the high spectrum image of detection insulator needed for obtaining；The attached husky density of insulator surface is obtained by attached husky Density Detection model again.The on-line checking that this method can not have a power failure goes out the surface sand density of the insulator in transmission line of electricity, the normal power transmission and distribution of electric system are not influenced, it is simple, convenient, and insulator surface local maximum can be measured, influence of the attached sand-like state to the insulation performance of insulator more accurately can be assessed and be analyzed, so as to the insulating Design to insulator and safeguards the more reliable test foundation of offer.
Description
Technical field
The present invention relates to a kind of detection methods of the attached husky density of insulator surface.
Background technique
Sandstorm is the diastrous weather for frequently appearing in arid, semiarid zone.In China, northwest sand source area often goes out
Existing strong wind sand (sandstorm) weather, sand and dust then natural subsidence after becalming only.Therebetween, tiny sandy environment can also be long through high-altitude
Distance Transmission is to multiple provinces such as southern Anhui, Jiangsu and Shanghai.Sand and dust are easily attached on electrical power trans mission/distribution system under humidified condition
In insulator surface form attached sand.Research shows that: the insulator of the attached sand in surface, under certain humidity conditions its insulation performance
(flashover voltage) declines up to 15.1%.As it can be seen that frequently occurring for sandstorm proposes the insulating Design of transmission line of electricity with maintenance
Higher requirement.Therefore, electric system need to grasp the attached husky density (quality of unit area attachment sand and dust) of insulator in time, with
Scheme is targetedly cleaned convenient for formulating to have, to ensure the safety of power supply, is used manpower and material resources sparingly simultaneously.
Existing husky Density Detection method attached to insulator surface is to remove insulator, by insulator umbrella in laboratory
Surface it is attached it is husky clean, weigh attached sandy amount under cleaning, again divided by the area of full skirt upper surface, show that insulator surface is attached
Husky density.The method the problem is that: 1, need to retract insulator, clean, weighing operation, complicated for operation, ring
Section is more, easily generates deviation in operation.2, necessary live power failure operation, seriously affects the normal power transmission and distribution of electric system,
It is difficult to carry out it.3, it can not reflect sand and dust in insulator surface local maximum, cause to be difficult to accurate evaluation and analysis is current
Influence of the attached sand-like state to its insulation performance cannot provide the maintenance of insulator reliable attached husky state verification foundation.
Summary of the invention
Goal of the invention of the invention is to provide a kind of attached husky density non-contact detection method of insulator surface, and this method can not
The on-line checking of power failure goes out the surface sand density of the insulator in transmission line of electricity, does not influence the normal power transmission and distribution of electric system,
It is simple, convenient, and insulator surface local maximum can be measured, attached sand-like state more accurately can be assessed and analyze to exhausted
The influence of the insulation performance of edge so as to the insulating Design to insulator and safeguards the more reliable test foundation of offer.
The technical scheme adopted by the invention for realizing the object of the invention is, a kind of attached husky density of insulator surface it is online non-
Contact detecting method, comprising the following steps:
A, the acquisition of the EO-1 hyperion spectral line of known attached husky density insulating trip
The insulating trip i that I sheet is produced with insulator same material, the uniform adhesion sand and dust on insulating trip i, makes to insulate
The attached husky density of piece i is Si；Insulating trip i is shot with hyperspectral imager, obtains the high spectrum image X " of attached husky density Sii, X "i
=[x "i,1,x”i,2,…,x”i,n,…,x”i,N]；Wherein, i is the serial number of insulating trip, and i=1,2,3 ... I, I are insulating trip
Number, its value are 10-500, n=1,2, and 3 ... N, N are the wave band total number of EO-1 hyperion spectral line, value 64-256；
x”i,nFor the high spectrum image X " of attached husky density SiiIn reflectivity under n-th of wave band；
To the high spectrum image X " of attached husky density SiiBlack and white correction, multiplicative scatter correction, smoothing denoising are carried out, is obtained attached
The EO-1 hyperion spectral line X of husky density Sii,Xi=[xi,1, xi,2, xi,3..., xi,n..., xi,N]；xi,nFor the EO-1 hyperion of attached husky density Si
The reflectivity under n-th of wave band in spectral line；
B, the foundation and solution of parameter model
The parameter detecting model of attached husky density is established,
S=a1x1+a2x2+a3x3+…anxn…+aNxN
Wherein, S is the attached husky density of parameter detecting model output, xnBe parameter detecting model n-th of wave band under mould
Type reflectivity, anBe parameter detecting model n-th of wave band under model scale parameter；
The attached sand density Si of each insulating trip i is assigned to the attached husky density S of parameter detecting model output, while by attached sand
Reflectivity x under n-th of wave band of the corresponding EO-1 hyperion spectral line Xi of density Sii,nIt substitutes under n-th of wave band of parameter detecting model
Model reflectivity xn；Then it is solved with partial least-squares regression method, obtains the model under n-th of wave band of parameter detecting model
Scale parameter anValue An, thus the parameter detecting model of the attached husky density solved:
S=A1x1+A2x2+A3x3+…Anxn…+ANxN
C, the on-line and non-contact inspection of the attached husky density of insulator
The running insulator to be measured in transmission and distribution line road is shot with hyperspectral imager, obtains insulator to be measured
High spectrum image, black and white correction, polynary scattering school are carried out to the high spectrum image entirety or selection area of insulator to be measured
Just, smoothing denoising obtains the entirety of insulator to be measured or the EO-1 hyperion spectral line X in region0,X0=[x0,1,x0,2,x0,3,…,
x0,n,…,x0,N]；
By the EO-1 hyperion spectral line X of insulator to be measured0In reflectivity x under n-th of wave band0, nModel as n-th of wave band
Reflectivity xnInput value, input the parameter detecting model S=A of the attached husky density solved1x1+A2x2+A3x3+…Anxn…+
ANxN, i.e. S0=A1x0,1+A2x0,2+A3x0,3+…Anx0,n…+ANx0,N；The attached husky density S of parameter detecting model output0, as to
Survey the attached husky density S of insulator entirety or selection area0。
Compared with prior art, the beneficial effects of the present invention are:
One, discontiguous shooting is carried out to the running insulator to be measured in transmission and distribution line road with hyperspectral imager, i.e.,
The detection of the attached husky density of achievable insulator to be measured；Without being retracted, being cleaned to insulator, weighed；It is operated
Simply, quick and easy, and the deviation generated during complicated manual operation is avoided, test result consistency is good.Together
When, when detection need not power failure operation, the normal power transmission and distribution of electric system will not be impacted, it is convenient to carry out.
Two, any selection, delineation can be carried out to detection (shooting) region, being averaged for insulator full skirt surface can be measured
Attached sand density, also can subregion measure the attached husky density in part of insulator surface, the attached sand of local maxima for obtaining insulator surface is close
Degree, the insulation so as to more accurately assess and analyze influence of the attached sand-like state to the insulation performance of insulator, to insulator
Design provides more reliable test foundation with maintenance.
Further, the specific practice that the present invention carries out black and white correction to the high spectrum image of attached husky density Si is: using bloom
Spectrum imager shoots standard white plate to obtain reflected image W, the W=[w of standard white plate1,w2,w3,…,wn,…,wN],
Middle wnFor the reflectivity under n-th of wave band in the reflected image of standard white plate, at the same with hyperspectral imager to standard blackboard into
Row shooting obtains reflected image D, the D=[d of standard blackboard1,d2,d3,…,dn,…,dN], dnFor the reflected image of standard blackboard
In reflectivity under n-th of wave band；In conjunction with the high spectrum image X " of attached husky density Sii, X "i=[x "i,1,x”i,2,…,x
”i,n,…,x”i,N], high spectrum image X ' after the correction of attached husky density Si is obtained by following formulai,
Wherein, x 'inFor the reflectivity under n-th of wave band in high spectrum image after the correction of attached husky density Si.
In this way, EO-1 hyperion spectral line eliminates the influence of light intensity after black and white correction, so that test is suitable for various intensity
Light condition, and further improve the accuracy and precision of detection.
Further, the specific practice of multiplicative scatter correction of the invention is:
By high spectrum image X ' after the correction of attached husky density Sii=[x 'i,1,x’i,2,x’i,3,…,x’i,n,…,x’i,N],
Calculate average high spectrum imageWherein,For average high spectrum imageIn average reflectance under n-th of wave band,Indicate tired from i=1 to i=I
Meter summation；
By high spectrum image X ' after the correction of attached husky density SiiWith average high spectrum imageOne-variable linear regression is carried out,
Obtain high spectrum image X ' after the correction of attached husky density SiiWith average high spectrum imageLinear regression relation formula,M in formulaiAnd biIt is the opposite deviation ratio and translational movement of linear regression respectively；And then obtain attached husky density
The multiplicative scatter correction spectrum of Si Wherein,
For the multiplicative scatter correction spectrum of attached husky density SiIn n-th of wave band under multiplicative scatter correction reflectivity.
Such multiplicative scatter correction eliminates the light that different size of surface mass particle generates and scatters to EO-1 hyperion
The influence of spectral line further improves the accuracy of detection.
Further, the specific method of smoothing denoising of the invention be Wavelet Denoising Method, Savitzky-Golay smothing filtering,
Differential transform or logarithmic transformation.
In this way, EO-1 hyperion spectral line is more smooth, instrument dark current and other random disturbances are eliminated, is further improved
The accuracy of detection.
The present invention is described in further detail With reference to embodiment.
Specific embodiment
Embodiment
A kind of specific embodiment of the invention is a kind of on-line and non-contact inspection side of the attached husky density of insulator surface
Method, comprising the following steps:
A, the acquisition of the EO-1 hyperion spectral line of known attached husky density insulating trip
The insulating trip i that I sheet is produced with insulator same material, the uniform adhesion sand and dust on insulating trip i, makes to insulate
The attached husky density of piece i is Si；Insulating trip i is shot with hyperspectral imager, obtains the high spectrum image X " of attached husky density Sii, X "i
=[x "i,1,x”i,2,…,x”i,n,…,x”i,N]；Wherein, i is the serial number of insulating trip, and i=1,2,3 ... I, I are insulating trip
Number, its value are 10-500, n=1,2, and 3 ... N, N are the wave band total number of EO-1 hyperion spectral line, value 64-256；
x”i,nFor the high spectrum image X " of attached husky density SiiIn reflectivity under n-th of wave band；
To the high spectrum image X " of attached husky density SiiBlack and white correction, multiplicative scatter correction, smoothing denoising are carried out, is obtained attached
The EO-1 hyperion spectral line X of husky density Sii,Xi=[xi,1, xi,2, xi,3..., xi,n..., xi,N]；xi,nFor the EO-1 hyperion of attached husky density Si
The reflectivity under n-th of wave band in spectral line；
B, the foundation and solution of parameter model
The parameter detecting model of attached husky density is established,
S=a1x1+a2x2+a3x3+…anxn…+aNxN
Wherein, S is the attached husky density of parameter detecting model output, xnBe parameter detecting model n-th of wave band under mould
Type reflectivity, anBe parameter detecting model n-th of wave band under model scale parameter；
The attached sand density Si of each insulating trip i is assigned to the attached husky density S of parameter detecting model output, while by attached sand
Reflectivity x under n-th of wave band of the corresponding EO-1 hyperion spectral line Xi of density Sii,nIt substitutes under n-th of wave band of parameter detecting model
Model reflectivity xn；Then it is solved with partial least-squares regression method, obtains the model under n-th of wave band of parameter detecting model
Scale parameter anValue An, thus the parameter detecting model of the attached husky density solved:
S=A1x1+A2x2+A3x3+…Anxn…+ANxN
C, the on-line and non-contact inspection of the attached husky density of insulator
The running insulator to be measured in transmission and distribution line road is shot with hyperspectral imager, obtains insulator to be measured
High spectrum image, black and white correction, polynary scattering school are carried out to the high spectrum image entirety or selection area of insulator to be measured
Just, smoothing denoising obtains the entirety of insulator to be measured or the EO-1 hyperion spectral line X in region0,X0=[x0,1,x0,2,x0,3,…,
x0,n,…,x0,N]；
By the EO-1 hyperion spectral line X of insulator to be measured0In reflectivity x under n-th of wave band0, nModel as n-th of wave band
Reflectivity xnInput value, input the parameter detecting model S=A of the attached husky density solved1x1+A2x2+A3x3+…Anxn…+
ANxN, i.e. S0=A1x0,1+A2x0,2+A3x0,3+…Anx0,n…+ANx0,N；The attached husky density S of parameter detecting model output0, as to
Survey the attached husky density S of insulator entirety or selection area0。
The specific practice for carrying out black and white correction to the high spectrum image of attached husky density Si of this example is: using hyperspectral imager
Standard white plate is shot to obtain reflected image W, the W=[w of standard white plate1,w2,w3,…,wn,…,wN], wherein wnFor mark
Reflectivity in the reflected image of quasi- blank under n-th of wave band, while standard blackboard shoot with hyperspectral imager
To reflected image D, the D=[d of standard blackboard1,d2,d3,…,dn,…,dN], dnFor n-th of wave in the reflected image of standard blackboard
Reflectivity under section；In conjunction with the high spectrum image X " of attached husky density Sii, X "i=[x "i,1,x”i,2,…,x”i,n,…,x”i,N],
High spectrum image X ' after the correction of attached husky density Si is obtained by following formulai,
Wherein, x 'inFor the reflectivity under n-th of wave band in high spectrum image after the correction of attached husky density Si.
The specific practice of the multiplicative scatter correction of this example is:
By high spectrum image X ' after the correction of attached husky density Sii=[x 'i,1,x’i,2,x’i,3,…,x’i,n,…,x’i,N],
Calculate average high spectrum imageWherein,For average high spectrum imageIn average reflectance under n-th of wave band,Indicate accumulative from i=1 to i=I
Summation；
By high spectrum image X ' after the correction of attached husky density SiiWith average high spectrum imageOne-variable linear regression is carried out,
Obtain high spectrum image X ' after the correction of attached husky density SiiWith average high spectrum imageLinear regression relation formula,M in formulaiAnd biIt is the opposite deviation ratio and translational movement of linear regression respectively；And then obtain attached husky density
The multiplicative scatter correction spectrum of Si Wherein,It is attached
The multiplicative scatter correction spectrum of husky density SiIn n-th of wave band under multiplicative scatter correction reflectivity.
The specific method of smoothing denoising of the invention can be Wavelet Denoising Method, Savitzky-Golay smothing filtering, differential
The existing smoothing denoising method such as transformation or logarithmic transformation.
Following table is to have carried out detection in fact to six insulators using the detection method and existing cleaning weighing technique of this example
It tests, obtained testing result (when detection, the number I=30 of insulating trip, the wave band total number of EO-1 hyperion spectral line N=256).
Contrasting detection in table the result shows that, using the method for the present invention compared with existing cleaning weighing method, error exists
Within 10%；It can be realized the on-line and non-contact inspection of the attached husky density of insulator surface, accuracy is higher；And the method for the present invention is grasped
It is greatly simplified as process, avoids to the seriously affecting of the normal power transmission and distribution of electric system, convenient to carry out, there is fabulous popularization to make
With value.
Claims (4)
1. a kind of on-line and non-contact inspection method of the attached husky density of insulator surface, comprising the following steps:
A, the acquisition of the EO-1 hyperion spectral line of known attached husky density insulating trip
The insulating trip i that I sheet is produced with insulator same material, the uniform adhesion sand and dust on insulating trip i, makes insulating trip i
Attached husky density be Si；Insulating trip i is shot with hyperspectral imager, obtains the high spectrum image X " of attached husky density Sii, X "i=
[x”i,1,x”i,2,…,x”i,n,…,x”i,N]；Wherein, i is the serial number of insulating trip, and i=1,2,3 ... I, I are of insulating trip
Number, its value are 10-500, n=1,2, and 3 ... N, N are the wave band total number of EO-1 hyperion spectral line, value 64-256；x"i,n
For the high spectrum image X " of attached husky density SiiIn reflectivity under n-th of wave band；
To the high spectrum image X " of attached husky density SiiBlack and white correction, multiplicative scatter correction, smoothing denoising are carried out, attached husky density is obtained
The EO-1 hyperion spectral line X of Sii,Xi=[xi,1, xi,2, xi,3..., xi,n..., xi,N]；xi,nIn EO-1 hyperion spectral line for attached husky density Si
N-th of wave band under reflectivity；
B, the foundation and solution of parameter model
The parameter detecting model of attached husky density is established,
S=a1x1+a2x2+a3x3+…anxn…+aNxN
Wherein, S is the attached husky density of parameter detecting model output, xnBe parameter detecting model n-th of wave band under model reflection
Rate, anBe parameter detecting model n-th of wave band under model scale parameter；
The attached sand density Si of each insulating trip i is assigned to the attached husky density S of parameter detecting model output, while by attached husky density
Reflectivity x under n-th of wave band of the corresponding EO-1 hyperion spectral line Xi of Sii,nSubstitute into the mould under n-th of wave band of parameter detecting model
Type reflectivity xn；Then it is solved with partial least-squares regression method, obtains the model scale under n-th of wave band of parameter detecting model
Parameter anValue An, thus the parameter detecting model of the attached husky density solved:
S=A1x1+A2x2+A3x3+…Anxn…+ANxN
C, the on-line and non-contact inspection of the attached husky density of insulator
The running insulator to be measured in transmission and distribution line road is shot with hyperspectral imager, obtains the height of insulator to be measured
Spectrum picture carries out black and white correction to the high spectrum image entirety or selection area of insulator to be measured, multiplicative scatter correction, puts down
Sliding denoising, obtains the entirety of insulator to be measured or the EO-1 hyperion spectral line X in region0,X0=[x0,1,x0,2,x0,3,…,x0,n,…,
x0,N]；
By the EO-1 hyperion spectral line X of insulator to be measured0In reflectivity x under n-th of wave band0, nModel reflection as n-th of wave band
Rate xnInput value, input the parameter detecting model S=A of the attached husky density solved1x1+A2x2+A3x3+…Anxn…+ANxN, i.e.,
S0=A1x0,1+A2x0,2+A3x0,3+…Anx0,n…+ANx0,N；The attached husky density S of parameter detecting model output0, insulation as to be measured
The attached husky density S of sub- entirety or selection area0。
2. a kind of on-line and non-contact inspection method of the attached husky density of insulator surface according to claim 1, feature exist
In the specific practice that the high spectrum image to attached husky density Si carries out black and white correction is: with hyperspectral imager to mark
Quasi- blank is shot to obtain reflected image W, the W=[w of standard white plate1,w2,w3,…,wn,…,wN], wherein wnFor standard white
Reflectivity in the reflected image of plate under n-th of wave band, while standard blackboard is shot with hyperspectral imager and is marked
Reflected image D, the D=[d of quasi- blackboard1,d2,d3,…,dn,…,dN], dnFor under n-th of wave band in the reflected image of standard blackboard
Reflectivity；In conjunction with the high spectrum image X " of attached husky density Sii, X "i=[x "i,1,x”i,2,…,x”i,n,…,x”i,N], under
Formula obtains high spectrum image X ' after the correction of attached husky density Sii,
Wherein, x 'inFor the reflectivity under n-th of wave band in high spectrum image after the correction of attached husky density Si.
3. a kind of on-line and non-contact inspection method of the attached husky density of insulator surface according to claim 2, feature exist
In the specific practice of the multiplicative scatter correction is:
By high spectrum image X ' after the correction of attached husky density Sii=[x 'i,1,x’i,2,x’i,3,…,x’i,n,…,x’i,N], it calculates
Average high spectrum image Wherein,It is flat
Equal high spectrum imageIn average reflectance under n-th of wave band,Indicate the accumulative summation from i=1 to i=I；
By high spectrum image X ' after the correction of attached husky density SiiWith average high spectrum imageOne-variable linear regression is carried out, is obtained
High spectrum image X ' after the correction of attached sand density SiiWith average high spectrum imageLinear regression relation formula,M in formulaiAnd biIt is the opposite deviation ratio and translational movement of linear regression respectively；And then obtain attached husky density
The multiplicative scatter correction spectrum of Si Wherein,It is attached
The multiplicative scatter correction spectrum of husky density SiIn n-th of wave band under multiplicative scatter correction reflectivity.
4. a kind of on-line and non-contact inspection method of the attached husky density of insulator surface according to claim 3, feature exist
In the specific method of the smoothing denoising is that Wavelet Denoising Method, Savitzky-Golay smothing filtering, differential transform or logarithm become
It changes.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113324922A (en) * | 2021-05-31 | 2021-08-31 | 山东深蓝智谱数字科技有限公司 | Hyperspectrum-based wheat stripe rust monitoring method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102520286A (en) * | 2011-12-15 | 2012-06-27 | 国网电力科学研究院 | Hyperspectrum-based composite insulator operation state classification method |
| CN102565577A (en) * | 2011-12-15 | 2012-07-11 | 国网电力科学研究院 | Method for detecting high optical spectrum of composite insulator |
| CN104849287A (en) * | 2015-06-10 | 2015-08-19 | 国家电网公司 | Composite insulator contamination degree non-contact detection method |
| CN108072667A (en) * | 2017-09-28 | 2018-05-25 | 江苏省电力试验研究院有限公司 | Insulator contamination level detection method and system based on EO-1 hyperion |
-
2019
- 2019-01-25 CN CN201910071478.6A patent/CN109856088B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102520286A (en) * | 2011-12-15 | 2012-06-27 | 国网电力科学研究院 | Hyperspectrum-based composite insulator operation state classification method |
| CN102565577A (en) * | 2011-12-15 | 2012-07-11 | 国网电力科学研究院 | Method for detecting high optical spectrum of composite insulator |
| CN104849287A (en) * | 2015-06-10 | 2015-08-19 | 国家电网公司 | Composite insulator contamination degree non-contact detection method |
| CN108072667A (en) * | 2017-09-28 | 2018-05-25 | 江苏省电力试验研究院有限公司 | Insulator contamination level detection method and system based on EO-1 hyperion |
Non-Patent Citations (3)
| Title |
|---|
| 吴劼 等: "基于网格曲线分析绝缘子附灰密度的变化趋势", 《电网与清洁能源》 * |
| 李恒超 等: "基于高光谱成像技术的绝缘子污秽度预测", 《西南交通大学学报》 * |
| 田治仁 等: "基于彩色可见光图像的绝缘子污秽等级判别", 《电工电能新技术》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113324922A (en) * | 2021-05-31 | 2021-08-31 | 山东深蓝智谱数字科技有限公司 | Hyperspectrum-based wheat stripe rust monitoring method |
| CN113324922B (en) * | 2021-05-31 | 2022-08-23 | 山东深蓝智谱数字科技有限公司 | Hyperspectrum-based wheat stripe rust monitoring method |
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