CN108180871A - A kind of method of quantitative assessment surface of composite insulator dusting roughness - Google Patents

A kind of method of quantitative assessment surface of composite insulator dusting roughness Download PDF

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Publication number
CN108180871A
CN108180871A CN201711364700.9A CN201711364700A CN108180871A CN 108180871 A CN108180871 A CN 108180871A CN 201711364700 A CN201711364700 A CN 201711364700A CN 108180871 A CN108180871 A CN 108180871A
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China
Prior art keywords
composite insulator
roughness
dusting
extracted
visible images
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CN201711364700.9A
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CN108180871B (en
Inventor
陈�田
周求宽
尹桂来
张宇
辛建波
李唐兵
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Jiangxi Electric Power Co Ltd
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Jiangxi Electric Power Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
    • G01B11/303—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces using photoelectric detection means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

A kind of method of quantitative assessment surface of composite insulator dusting roughness, by Visual image processing technology, using matlab software editing algorithms, image array ordered series of numbers is read, image effective characteristic parameters are extracted, transmission line composite insulator surface aging feature is carried out whereby and precisely judges.The method mainly includes：Composite insulator visible images are extracted, carry out the quantitatively characterizing of composite insulator imaging surface roughness；It shoots by unmanned plane, is detected in composite insulator to be measured electrification；By the visible images of collection in worksite composite insulator to be measured, image features are extracted, pass through the comparison with known surface roughness, exact evaluation imaging surface roughness.

Description

A kind of method of quantitative assessment surface of composite insulator dusting roughness
Technical field
The present invention relates to a kind of methods of quantitative assessment surface of composite insulator dusting roughness, belong to isolator detecting technology Field.
Background technology
For surface of composite insulator state, existing common detection method is divided into qualitative judgement, quantitative detection.Wherein, Qualitative judgement method has spraying, with reference to insulator diagnostic method etc., but the easily examined personnel's subjective factor of qualitative method influences, only can be auxiliary Helping property is not easy to the growth requirement of intelligent grid with reference to using, and need to have a power failure and carry out.Quantitative assay has equivalent salt density/ash Close, surface hydrophobicity test, surface leakage marks rising property can be tested, and all carry out in the lab, scene can not carry out.Thus, Lack to the quantitative assessment in operation surface of composite insulator state.
By fast-developing unmanned air vehicle technique and a wide range of popularization and application, it is compound can quickly and easily to obtain transmission line of electricity Insulate subgraph (visible images, infrared thermal imaging, ultraviolet imagery), but lacks effective analysis to big data image, still Artificial judgment since needing.
Invention content
The object of the present invention is to for existing insulator surface state-detection there are the problem of, a kind of quantitative assessment is compound The method of insulator surface dusting roughness.
The technical solution that the present invention realizes is as follows, and the present invention reads image array number by Visual image processing technology Row extract effective characteristic parameters, carry out surface aging feature whereby and precisely judge.
A kind of the step of method of quantitative assessment surface of composite insulator dusting roughness of the present invention, is as follows：
(1) based on image processing techniques, using matlab software programmings, composite insulator visible images is extracted, are carried out The quantitatively characterizing of composite insulator imaging surface roughness；
(2) it shoots by unmanned plane, in the form of non-contacting, is detected in composite insulator to be measured electrification；
(3) by the visible images of collection in worksite composite insulator to be measured, image features are extracted, by with it is known The comparison of surface roughness, exact evaluation imaging surface roughness.
The computational methods of described image surface roughness are as follows：
Each element u (i, j) is calculated first 2kAverage gray value A (i, j, k) in neighborhood：
The gray average A (i, j, k) in each pixel field is calculated in horizontal Eh(i, j) and vertical EvOn (i, j) direction The not difference between overlaid windows：
Eh(i, j)=| A (i+2k-1,j,k)-A(i-2k-1,j)|
Ev(i, j)=| A (i, j+2k-1,k)-A(i,j-2k-1)|；
E is made to reach the k of maximum value to the calculating of each pixel, the optimal window size of each pixel is 2kmax：
Sbert (i, j)=2^max (max (Eh(i,j)),max(Ev(i,j)))
Roughness Fcrs of the mean value of all Sbest (i, j) as picture in its entirety：
The operation principle of the present invention, surface roughness is the tool of surface of composite insulator dusting (surface texture feature) as table Sign.Contactless optical imaging measurement, progress, not damaged, quick, high certainty of measurement can be charged, be easily achieved online by having The advantages that measurement, available for accurately measuring surface of composite insulator roughness, with this quantitative assessment surface of composite insulator aging Situation.The present invention carries the visible images of camera acquisition electric transmission line isolator using unmanned plane, then by extracting image Characteristic parameter, exact evaluation imaging surface roughness.
The invention has the advantages that detection method provided by the invention can realize it is live accurate judge, evade it is artificial because Element influences；Detection method provided by the invention can live detection, without have a power failure carry out；The responsible existing equipment realization of the present invention, New equipment need not be purchased；The present invention can solve current Site Detection composite insulator and rely on naked eyes judgement, subjective judgement presence Error problem.
The present invention is suitable for the online live detection of insulator surface dusting roughness.
Description of the drawings
Fig. 1 is the flow chart of quantitative assessment surface of composite insulator dusting roughness of the present invention,；
Fig. 2 is roughness computation model in image values matrix；
Fig. 3 is that the surface roughness of different surfaces state calculates result；
Fig. 3 (a) be smooth surface, roughness F=7.49；Fig. 3 (b) be dusting surface, roughness F=15.81；Fig. 3 (c) For dusting surface indentation, roughness F=18.15；Fig. 3 (d) be checked surface, roughness F=21.99.
Specific embodiment
The specific embodiment of the present invention is as shown in Figure 1.The present embodiment quantitative assessment surface of composite insulator dusting is coarse The method of degree is as follows：
(1) unmanned aerial vehicle platform is established, for shooting transmission line composite insulator；
(2) video camera on unmanned plane obtains the visible images of transmission line composite insulator；
(3) based on image processing techniques, image values matrix is extracted using matlab software programmings；
(4) based on surface roughness algorithm, roughness features parameter is extracted；
(5) linear process is normalized, obtains surface state quantitative assessment, carries out quantitative assessment.
The present embodiment surface roughness algorithm, is the roughness measurement method based on computer vision, is referred to using camera shooting Machine captures image, and the image then is sent to processing unit, by digitized processing, according to pixel distribution and gray scale, texture, The information such as shape, color select rational algorithm to calculate the roughness parameter value of workpiece.
The present embodiment imaging surface roughness calculates, as shown in Fig. 2, each element u (i, j) is 2 in evaluation matrixk Average gray value A (i, j, k) in neighborhood：
The gray average A (i, j, k) in each pixel field is calculated in horizontal Eh(i, j) and vertical EvOn (i, j) direction The not difference between overlaid windows：
Eh(i, j)=| A (i+2k-1,j,k)-A(i-2k-1,j)|
Ev(i, j)=| A (i, j+2k-1,k)-A(i,j-2k-1)|
E is made to reach the k of maximum value to the calculating of each pixel, the optimal window size of each pixel is 2kmax：
Sbert (i, j)=2^max (max (Eh(i,j)),max(Ev(i,j)))
Roughness Fcrs of the mean value of all Sbest (i, j) as picture in its entirety
The present embodiment imaging surface roughness calculates, as shown in figure 3, the roughness result for typical surface state.Fig. 3 (a) it is smooth surface, roughness F=7.49；Fig. 3 (b) be dusting surface, roughness F=15.81；Fig. 3 (c) is dusting surface Indentation, roughness F=18.15；Fig. 3 (d) is checked surface, and roughness F=21.99 as a result, can determine imaging surface roughness Numerical quantity solves the problems, such as current qualitative evaluation surface roughness.

Claims (2)

  1. A kind of 1. method of quantitative assessment surface of composite insulator dusting roughness, which is characterized in that the step of the method such as Under：
    (1) based on image processing techniques, using matlab software editing algorithms, composite insulator visible images is extracted, are carried out The quantitatively characterizing of surface of composite insulator roughness；
    (2) it shoots by unmanned plane, in the form of non-contacting, is detected in composite insulator to be measured electrification；
    (3) by the visible images of collection in worksite composite insulator to be measured, image features are extracted, by with known surface The comparison of roughness, exact evaluation imaging surface roughness.
  2. 2. a kind of method of quantitative assessment surface of composite insulator dusting roughness according to claim 1, feature exist In calculating imaging surface roughness Fcrs according to the following steps using matlab softwares：
    Each pixel element u (i, j) is 2 first in calculating visible imageskAverage gray value A (i, j, k) in neighborhood：
    The gray average A (i, j, k) in each pixel field is calculated in horizontal Eh(i, j) and vertical EvIt is not weighed on (i, j) direction Difference between folded window：
    E is made to reach the k of maximum value to the calculating of each pixel, the optimal window size of each pixel is 2kmax：
    Sbert (i, j)=2^max (max (Eh(i,j)),max(Ev(i,j)))
    Roughness Fcrs of the mean value of all Sbest (i, j) as picture in its entirety：
CN201711364700.9A 2017-12-18 2017-12-18 method for quantitatively evaluating composite insulator surface pulverization roughness Active CN108180871B (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109374516A (en) * 2018-11-30 2019-02-22 中国电力科学研究院有限公司 A kind of route suspended compound insulator surface dusting detection method
CN109405771A (en) * 2018-12-29 2019-03-01 西南交通大学 A kind of contactless hierarchical detection method of top insulation sublist surface roughness
CN110376155A (en) * 2019-09-02 2019-10-25 云南电网有限责任公司电力科学研究院 Composite insulator degradation detecting method and system based on infrared spectroscopy

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09105618A (en) * 1995-10-11 1997-04-22 Ibaraki Pref Gov Method and apparatus for inspection of defect on smooth surface of object as well as method and apparatus for measurement of roughness on surface of object
JP2004163239A (en) * 2002-11-13 2004-06-10 Silicon Technology Co Ltd Surface evaluation device
CN101561262A (en) * 2009-05-31 2009-10-21 东南大学 Surface roughness on line measurement method under uncertain condition
CN101634551A (en) * 2009-08-18 2010-01-27 清华大学深圳研究生院 Method and system for detecting surface roughness
CN102278958A (en) * 2011-06-24 2011-12-14 上海瑞伯德智能系统科技有限公司 Visual detection system for planarity of aluminum plate
CN102506773A (en) * 2011-09-28 2012-06-20 上海宏力半导体制造有限公司 Method for detecting surface roughness of wafer
CN103776397A (en) * 2013-11-22 2014-05-07 大连世佳精工机械有限公司 Substrate flatness detection apparatus
CN104848808A (en) * 2015-06-03 2015-08-19 湖南大学 Surface roughness detection method and equipment
CN105547200A (en) * 2015-12-02 2016-05-04 北京星航机电装备有限公司 Method for measurement of finished surface roughness of C/SiC composite materials on the basis of image grey information
CN105865378A (en) * 2016-03-30 2016-08-17 苏州精创光学仪器有限公司 Flatness detection method

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09105618A (en) * 1995-10-11 1997-04-22 Ibaraki Pref Gov Method and apparatus for inspection of defect on smooth surface of object as well as method and apparatus for measurement of roughness on surface of object
JP2004163239A (en) * 2002-11-13 2004-06-10 Silicon Technology Co Ltd Surface evaluation device
CN101561262A (en) * 2009-05-31 2009-10-21 东南大学 Surface roughness on line measurement method under uncertain condition
CN101634551A (en) * 2009-08-18 2010-01-27 清华大学深圳研究生院 Method and system for detecting surface roughness
CN102278958A (en) * 2011-06-24 2011-12-14 上海瑞伯德智能系统科技有限公司 Visual detection system for planarity of aluminum plate
CN102506773A (en) * 2011-09-28 2012-06-20 上海宏力半导体制造有限公司 Method for detecting surface roughness of wafer
CN103776397A (en) * 2013-11-22 2014-05-07 大连世佳精工机械有限公司 Substrate flatness detection apparatus
CN104848808A (en) * 2015-06-03 2015-08-19 湖南大学 Surface roughness detection method and equipment
CN105547200A (en) * 2015-12-02 2016-05-04 北京星航机电装备有限公司 Method for measurement of finished surface roughness of C/SiC composite materials on the basis of image grey information
CN105865378A (en) * 2016-03-30 2016-08-17 苏州精创光学仪器有限公司 Flatness detection method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
王健全等: "《基于灰度信息的工程陶瓷磨削表面粗糙度评定》", 《装甲兵工程学院学报》 *
陈曼龙等: "《车削零件表面粗糙度图像法检测优选方法》", 《应用光学》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109374516A (en) * 2018-11-30 2019-02-22 中国电力科学研究院有限公司 A kind of route suspended compound insulator surface dusting detection method
CN109405771A (en) * 2018-12-29 2019-03-01 西南交通大学 A kind of contactless hierarchical detection method of top insulation sublist surface roughness
CN110376155A (en) * 2019-09-02 2019-10-25 云南电网有限责任公司电力科学研究院 Composite insulator degradation detecting method and system based on infrared spectroscopy

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