JPH0360313A - Image processor for inspection of overhead line - Google Patents
Image processor for inspection of overhead lineInfo
- Publication number
- JPH0360313A JPH0360313A JP1193268A JP19326889A JPH0360313A JP H0360313 A JPH0360313 A JP H0360313A JP 1193268 A JP1193268 A JP 1193268A JP 19326889 A JP19326889 A JP 19326889A JP H0360313 A JPH0360313 A JP H0360313A
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- Prior art keywords
- overhead
- overhead lines
- distribution
- image
- image processing
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- 238000007689 inspection Methods 0.000 title claims description 9
- 230000005856 abnormality Effects 0.000 claims abstract description 24
- 230000001186 cumulative effect Effects 0.000 claims description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000000034 method Methods 0.000 description 5
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000009825 accumulation Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000009182 swimming Effects 0.000 description 1
- 238000011179 visual inspection Methods 0.000 description 1
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Abstract
Description
【発明の詳細な説明】
〔産業上の利用分野〕
本発明は送電線のような架空線の目視点検を自動的に行
うため、テレビカメラでとらえた映像から架空線の異常
を自動的に検出する架空線点検用画像処理装置に関する
ものである。[Detailed Description of the Invention] [Industrial Application Field] The present invention automatically detects abnormalities in overhead lines from images captured by a television camera in order to automatically visually inspect overhead lines such as power transmission lines. The present invention relates to an image processing device for inspecting overhead wires.
従来、との掘架空線の点検は人が徒歩又はヘリコプタ−
に乗って双眼鏡によシ直接目視確認することによシ行な
われていたが、最近では%開昭59−85909公報に
示されるようにヘリコプタ−上からテレビカメラで撮影
してVTRに記録したシ、実開昭61−192614公
報に示されるように架空線上を走行する自走式点極機に
テレビカメラを搭載して走行させながらVTRに記録し
たうする方法がとられている。この場合、帰還・回収段
VTRの映像を再生して人がモニタテレビを見て異常が
無いかを確認する。Traditionally, overhead cables were inspected by people on foot or by helicopter.
This was done by directly visualizing the image using binoculars aboard a helicopter, but recently, as shown in the %85909 publication, images were taken using a TV camera from above a helicopter and recorded on a VTR. As shown in Japanese Utility Model Application Publication No. 192614/1983, a method has been adopted in which a television camera is mounted on a self-propelled pointer machine running on an overhead wire and recording is made on a VTR while the machine is running. In this case, the video on the return/recovery stage VTR is played back and a person watches the monitor TV to check if there are any abnormalities.
発見すべき異常としては第6図(a)〜(0)に示すよ
うな素線切れ、溶痕、異物付着、サビ、撚り線ムラ等で
ある。このようなものは放置してかくと次第に増大し、
素線がゆるみ、地絡や短絡などの大事故に発展する可能
性があるので、速やかに発見し、処理する必要がある。Abnormalities to be detected include wire breaks, melt marks, foreign matter adhesion, rust, uneven wire stranding, etc. as shown in FIGS. 6(a) to (0). If something like this is left untreated, it will gradually increase in size,
Loosening of the strands can lead to major accidents such as ground faults and short circuits, so it is necessary to detect and dispose of it promptly.
このなかで特に撚bsムラは正常部分と異常部分の画像
変化が少なく熟練技術者でないと発見が難しいとされて
いる。Among these, it is said that it is particularly difficult to detect twist BS unevenness because there is little image change between normal and abnormal areas.
かかる従来の架空線の目視点検では人が長時間テレビを
見て判断する必要があるため、疲労や見落しが発生する
などの問題があった。Such conventional visual inspection of overhead lines requires a person to watch television for a long time to make judgments, which poses problems such as fatigue and oversights.
また、特に撚υ線ムラのような微妙な異常を連続的に再
生される画像のなかから発見するには熱線技術を必要と
するなどの課題があった0本発明は上記のような課題を
解決するためになされたもので、従来人がモニタテレビ
を見て行っていた架空線の異、常発見作業を自動的に行
うことができる架空線点検用画像処理装置を得ることを
目的とする。In addition, there was a problem in that hot wire technology was required to detect subtle abnormalities such as unevenness in twisted wires from continuously reproduced images.The present invention solves the above problems. The object of this invention is to provide an image processing device for inspecting overhead wires that can automatically perform the work of detecting abnormalities and abnormalities in overhead wires, which conventionally had to be done by a person by watching a television monitor. .
本発明に係る架空線点検用画像処理装置は、テレビカメ
ラによシ撮影された架空線の1ili像を順次入力し、
入力画像内の架空線の位置を検出し、架空線に対し所定
の方向に濃度を累積した分布をとり、その分布の状態を
解析することによシ、架空線の異常を見つけるものであ
る。The image processing device for overhead line inspection according to the present invention sequentially inputs 1ili images of overhead lines taken by a television camera,
Anomalies in the overhead wire are detected by detecting the position of the overhead wire in the input image, obtaining a distribution of accumulated density in a predetermined direction with respect to the overhead wire, and analyzing the state of the distribution.
本発明における画像処理装置は入力画像内の架空線の位
置を検出し、架空線に対し所定の方向に濃度を累積した
分布をとり、その分布の状態を解析することによシ架空
線の異常を見つける。The image processing device of the present invention detects the position of an overhead wire in an input image, obtains a distribution in which the density is accumulated in a predetermined direction with respect to the overhead wire, and analyzes the state of the distribution to detect abnormalities in the overhead wire. Find.
以下、本発明の一実施例を図について説明する0第1図
において、(1)は点検対象たる架空線、(2)はヘリ
コプタ−1(3)は撮影システム、(4)は再生用VT
R、(5)は画像処理装置、(6)はモニタテレビ、
(7)は表示器である。Hereinafter, one embodiment of the present invention will be explained with reference to the drawings. In Fig. 1, (1) is an overhead line to be inspected, (2) is a helicopter, (3) is a photographing system, and (4) is a reproduction VT.
R, (5) is an image processing device, (6) is a monitor television,
(7) is a display.
本実施例では架空11(1,)の映像をヘリコプタ−(
2)からテレビカメラ(財)でとらえ、記録用VTR(
至)で録画し、帰還後、再生用V T R(4)で再生
して画像処理装置(5)で分析し、不良箇所が見つかれ
ば表示器(7)で表示して、そのときに人(図示せず)
がモニタテレビ(6)を見て内容を確認するものである
。In this example, the image of the fictitious 11 (1,) is transferred to a helicopter (
2) was captured by a television camera (foundation) and recorded on a recording VTR (
After returning to Japan, it is played back on the playback VTR (4) and analyzed on the image processing device (5). If any defects are found, they are displayed on the display (7), and the person (not shown)
The user checks the content by watching the monitor TV (6).
画像処理装置(5)は、ビデオ信号aを取りこんで所定
の分解能でサンプリングして2次元のディジタル画像に
変換するビデオAD変換5 (a) 、変換したディジ
タル画像を記憶するビデオメモリー(52)、ビデオメ
モリーに記憶された画像に対して後述の演算処理を行う
ALUユニツ) (&5) 、演算結果をモニタテレビ
に表示するためのビデオDA変換器(54) 、 V
T R制御信号すを発生し、順次画像を進めながら画像
入力、演算8表示等の一連の動作を制御する制御ユニッ
ト(オ)から構成される。The image processing device (5) includes a video AD conversion 5 (a) that takes in a video signal a, samples it at a predetermined resolution, and converts it into a two-dimensional digital image; a video memory (52) that stores the converted digital image; An ALU unit (&5) that performs arithmetic processing (described later) on images stored in the video memory, a video DA converter (54) for displaying the arithmetic results on a TV monitor, V
It is composed of a control unit (O) that generates a TR control signal and controls a series of operations such as image input, calculation and display while sequentially advancing images.
尚、サンプリングされたディジタル画像の最小構成単位
を画素と呼ぶ。Note that the minimum constituent unit of a sampled digital image is called a pixel.
次に、第6図(0のような異常架空線を例にとって画像
処理装置(5)の動作について説明する。第2図に処理
フローを示す。Next, the operation of the image processing device (5) will be explained by taking an abnormal overhead wire as shown in FIG. 6 (0) as an example. FIG. 2 shows the processing flow.
まず、ビデオAD変換W(51)でサンプリングされた
ディジタル画像をビデオメモリー(52)に取シ込む。First, a digital image sampled by video AD conversion W (51) is input into a video memory (52).
入力された画像の例を第3図に示す。ここでは簡単のた
め、架空線部分をゝゝ1“、背景をゝゝ0“に2値化し
た画像で説明する。An example of an input image is shown in FIG. Here, for the sake of simplicity, an image in which the overhead line portion is binarized to "1" and the background is binarized to "0" will be used.
次に入力したディジタル画像のなかの架空線位置を検出
する。これは例えば画面の左右端の上から下に向って、
及び下から上に向ってゝゝ1“の画素を探索する。第3
図の例ではA、B、A′、B′が検出された左右端の位
置である。但し、画像中の背景部分にノイズがあると正
しい架空線の左右端位置を検出できないので、その場合
はあらかじめ平滑処理等(詳細は画像処理技術書参照)
にょシノイズ成分を除いて釦〈か、又は複数箇所で架空
線の位置を検出して多数決等により決定することが望ま
しい。Next, the position of the overhead wire in the input digital image is detected. For example, from the top to the bottom of the left and right edges of the screen,
and search for the pixel "1" from the bottom to the top. 3rd
In the illustrated example, A, B, A', and B' are the detected positions of the left and right ends. However, if there is noise in the background part of the image, the correct left and right end positions of the overhead lines cannot be detected, so in that case, smoothing processing etc. should be performed in advance (for details, refer to the image processing technical manual)
It is desirable to remove noise components and detect the position of the overhead wire using a button or at multiple locations and to determine by majority vote.
次に、求めた架空線の左右端をもとに架空線と直角の方
向に架空線を含む一定長さの範囲(架空線とその両側に
突起物を見つけるために必要な長さであり1第3図(a
)の例では架空線幅小両側に2画素とした)の画素の濃
度(明るさ)の累積値を一次元分布(一般に画像処理の
分野ではこれを投影図と呼ぶ)として求める0第3図(
−)の例では同図(1))のような−次元分布が得られ
る。この例では、架空線は画面に対して水平になってい
るため、濃度の累積は画面の垂直方向に求めたが、架空
線が画面に対して傾いて撮影されている場合は、その傾
き角に応じて、累積を求める角度を変更し、架空線の幅
方向に累積をとるようにする。Next, based on the obtained left and right ends of the overhead wire, a certain length range including the overhead wire in the direction perpendicular to the overhead wire (the length required to find the overhead wire and protrusions on both sides of it, and 1 Figure 3 (a
In the example of ), the overhead line width is small and there are two pixels on each side.The cumulative value of the density (brightness) of the pixels in ) is calculated as a one-dimensional distribution (generally called a projection diagram in the field of image processing)0Figure 3 (
-), a -dimensional distribution as shown in (1)) is obtained. In this example, the overhead line is horizontal to the screen, so the density accumulation was calculated in the vertical direction of the screen, but if the overhead line is tilted to the screen, the angle of inclination The angle for calculating the accumulation is changed accordingly, and the accumulation is taken in the width direction of the overhead wire.
次に求めた一次元分布について、各位置での累積値を定
常値と比較する。第3図(b)の例では定常値は4〜5
であるのに対して、0点では2で1)架空線内側に暗い
異常部分があることがわかる。Next, regarding the obtained one-dimensional distribution, the cumulative value at each position is compared with the steady value. In the example of Figure 3(b), the steady value is 4 to 5.
On the other hand, when the score is 0, the score is 2, indicating that 1) there is a dark abnormal area inside the overhead wire.
またD点では7であり、架空線内側に明るい異常部分が
季るか又は架空線外側に突起物があることが推定される
。尚、定常値としては近傍の平均値を用いるようにすれ
ば位置による撮影条件の違いの影響を除去できる0
以上のような処理をVTRを一画面ずつ進めながら順次
行ない、異常が検出されれば表示器(7)で表示する。In addition, it is 7 at point D, and it is estimated that there is a bright abnormal part on the inside of the overhead wire or that there is a protrusion on the outside of the overhead wire. Note that by using the average value in the vicinity as the steady-state value, the influence of differences in shooting conditions depending on the position can be removed.The above processing is performed sequentially while advancing the VTR one screen at a time, and if an abnormality is detected, It is displayed on the display (7).
次に、第6図(c)のような撚り線ムラの発生している
架空線を検出する方法について第4図の処理フローによ
り説明する。Next, a method for detecting an overhead wire with uneven wire twisting as shown in FIG. 6(c) will be described with reference to the processing flow shown in FIG. 4.
この場合も画像を入力して架空線の位置を見つける処理
は前記実施例と同様であるが、ここでは特に撚り線ムラ
の画像の特徴をよシきわだたすため、架空線の撚υ線方
向に濃度を累積した分布を求める。第5図(a)に入力
画像の例、同図(b)に撚り線方向の濃度の累積値の分
布の例を示す。In this case as well, the process of inputting an image and finding the position of the overhead wire is the same as in the previous embodiment, but in this case, in order to particularly highlight the image characteristics of uneven stranded wires, Find the cumulative concentration distribution in the direction. FIG. 5(a) shows an example of an input image, and FIG. 5(b) shows an example of the distribution of cumulative density values in the twisted line direction.
次に、上記分布に対してローカルピーク(ここでは負の
ピーク)を求め、各ピークの高さ2幅。Next, find local peaks (negative peaks here) for the above distribution, and calculate the height and width of each peak.
間隔を調べる。第5図(1,、)の例ではp1〜p5の
5つのローカルピークが検出され、各ピークの高さはh
1〜h5e各ピークの幅はd1〜dSr各ピーク間の間
隔はtl−t4と求まる。ここで、正常な架空線であれ
ば、高さは一定で、幅はdiのように細く、1九間隔も
tl、t2のように一定しているが、第5図(、)のよ
うな撚υ線ムラのある架空線ではd2のように幅の広い
ものや、t3.t4のように間隔のズしたものが検出さ
れ、異常があることがわかる。尚、上記実施例では2値
化画像を例にとって説明したため各ピークの高さは一定
でちったが、多値レベルの画像で同様の処理を行えば、
各ピークの高さも変化し、この高さの変動によっても異
常を見つけることができる。Check the spacing. In the example in Figure 5 (1,,), five local peaks p1 to p5 are detected, and the height of each peak is h
The width of each peak 1 to h5e is determined as d1 to dSr, and the interval between each peak is determined as tl-t4. Here, if it is a normal overhead line, the height is constant, the width is thin like di, and the 19 interval is constant like tl and t2, but as shown in Figure 5 (,) For overhead wires with uneven twisting, wide wires like d2, t3. Shifted intervals like t4 are detected, indicating that there is an abnormality. In the above embodiment, the height of each peak was constant because the binary image was used as an example, but if similar processing is performed on a multilevel image,
The height of each peak also changes, and abnormalities can also be detected by variations in this height.
上記のように、架空線の撚り線方向に濃度を累積した分
布をとり、その分布状態を調べれば、撚り線ムラのよう
な画像変化の少ない異常についても検出することができ
る。As described above, by taking the distribution of cumulative density in the stranded direction of the overhead wire and examining the distribution state, it is possible to detect abnormalities with little image change, such as stranded wire unevenness.
上記実施例ではヘリコプタ−から撮影した画像を対象と
したが、地上から望遠鏡等で剋ったものでもよく、自走
式点検機で収録したものでもよい。In the above embodiment, images taken from a helicopter were used, but images taken from the ground with a telescope or the like or images taken by a self-propelled inspection machine may also be used.
また、上記実施例では、VTRに収録した画像を再生し
て判定するようにしたが、画像処理装置をヘリコプタ−
又は自走式点検機に搭載するか又は撮影システムと画像
処理装置を通信回線で結ぶ等によジオンラインで判定す
るようにしてもよい。Furthermore, in the above embodiment, the image recorded on the VTR is played back for determination, but the image processing device may be used in a helicopter.
Alternatively, the determination may be made on-line by mounting it on a self-propelled inspection machine or by connecting the photographing system and the image processing device through a communication line.
!た、上記実施例では異常が見つかったとき、すぐに表
示器で告知するようにしたが、異常箇所をメモリしてお
いて、まとめて確認できるようにすれば更に効率的に作
業が行える。! In addition, in the above embodiment, when an abnormality is found, it is immediately notified on the display, but if the abnormality location is memorized and checked at once, the work can be done more efficiently.
尚、上記実施例では架空線以外の画像は含まれない場合
について述べたが、実際には飛来物(小鳥など)が混入
したう、背景に建物や樹木が検出されたシする場合があ
り1これらを検出し゛C異常と誤判定する可能性がある
。このため、連続する複数のフレームについて判定処理
を行ない、画面の移動速度に合せて異物の位置が移動し
ている場合のみ異常と判定するようにすれば上記誤判定
を防止することができる。In the above embodiment, the case was described in which images other than overhead wires were not included, but in reality, flying objects (small birds, etc.) may be mixed in, or buildings or trees may be detected in the background. There is a possibility that these will be detected and erroneously determined as a C abnormality. Therefore, the above-mentioned erroneous determination can be prevented by performing determination processing on a plurality of consecutive frames and determining an abnormality only when the position of the foreign object is moving in accordance with the moving speed of the screen.
以上のように本発明によれば架空線の画像を架空線点検
用画像処理装置によって入力画像内の架空線の位置を検
出して、架空線に対し所定方向に濃度を累積した分布を
と)、その分布の状態によシ架空線の異常を見つけるよ
うに構成したので、人が長時間テレビを見て判定する必
要がなく、疲労や見落し等の問題が回避できる。またこ
の発明の他の発明においては撚す線方向に濃度を累積し
九分布をとるようにしたので、撚す線ムラのような微妙
な異常も熟練技術者を要することなく自動的に安定に検
出できるものが得られる効果がある。As described above, according to the present invention, the position of the overhead wire in the input image is detected by the image processing device for overhead wire inspection, and the distribution of density accumulated in a predetermined direction with respect to the overhead wire is obtained. Since the system is configured to detect abnormalities in overhead lines based on the state of their distribution, there is no need for people to watch TV for long periods of time to make judgments, and problems such as fatigue and oversight can be avoided. In addition, in other inventions of this invention, the concentration is accumulated in the direction of the twisted wires to form a nine-distribution distribution, so even subtle abnormalities such as unevenness in the twisted wires can be automatically stabilized without requiring a skilled technician. This has the effect of providing something that can be detected.
第1図は本発明の一実施例による架空線点検用画像入力
装置を使用したシステム構成図、第2図は画像処理装置
の処理フローチャート、第3図は第2図の処理の場合の
画像処理例を示す説明図、第4図はこの発明の他の実施
例による画像処理装置の処理フローチャー)、!5図は
第4図の処理の場合の画泳処理例を示す説明図、第6図
(a)〜(Q)は架空線の異常例をそれぞれ示す部分図
である。
図において、(1)は架空線、〈2)はヘリコプタ−(
3)は撮影システム、(4)は再生用VTR,(5)は
画像処理装置、(6〉はモニタテレビ、(7〉は表示器
である。Fig. 1 is a system configuration diagram using an image input device for overhead wire inspection according to an embodiment of the present invention, Fig. 2 is a processing flowchart of the image processing device, and Fig. 3 is image processing in the case of the processing in Fig. 2. An explanatory diagram showing an example, FIG. 4 is a processing flowchart of an image processing apparatus according to another embodiment of the present invention),! FIG. 5 is an explanatory diagram showing an example of the swimming process in the case of the process shown in FIG. 4, and FIGS. 6(a) to (Q) are partial diagrams showing examples of abnormalities in the overhead wire. In the figure, (1) is an overhead line, and (2) is a helicopter (
3) is a photographing system, (4) is a playback VTR, (5) is an image processing device, (6> is a monitor television, and (7> is a display device).
Claims (3)
演算処理して上記架空線の点検を行う架空線点検用画像
処理装置において、架空線の位置を検出し、架空線の所
定の方向に濃度を累積した分布をとり、その分布の状態
により架空線の異常を見つけることを特徴とする架空線
点検用画像処理装置。(1) An image processing device for overhead line inspection that photographs overhead lines with a television camera and performs arithmetic processing on the obtained images to inspect the above-mentioned overhead lines. 1. An image processing device for inspecting overhead wires, which obtains a distribution in which density is accumulated in a direction, and detects abnormalities in overhead wires based on the state of the distribution.
演算処理して点検を行う架空線点検用画像処理装置にお
いて、架空線の位置を検出し、架空線の撚り線方向に濃
度を累積した分布をとり、その分布の状態により架空線
の異常を見つけることを特徴とする架空線点検用画像処
理装置。(2) An image processing device for overhead wire inspection, which photographs overhead wires with a television camera and performs arithmetic processing on the resulting images, detects the position of the overhead wires and calculates the density in the stranded direction of the overhead wires. An image processing device for inspecting overhead wires, which is characterized in that it takes the cumulative distribution and detects abnormalities in the overhead wires based on the state of the distribution.
が検出されたときに異常と判定することで誤判定を防止
することを特徴とする請求項第1項ないし第2項記載の
いずれかに記載の架空線点検用画像処理装置。(3) An erroneous determination is prevented by determining an abnormality when the same type of abnormality is detected in a plurality of consecutive frames of the image. Image processing device for overhead line inspection.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP1193268A JPH0360313A (en) | 1989-07-26 | 1989-07-26 | Image processor for inspection of overhead line |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP1193268A JPH0360313A (en) | 1989-07-26 | 1989-07-26 | Image processor for inspection of overhead line |
Publications (1)
Publication Number | Publication Date |
---|---|
JPH0360313A true JPH0360313A (en) | 1991-03-15 |
Family
ID=16305115
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP1193268A Pending JPH0360313A (en) | 1989-07-26 | 1989-07-26 | Image processor for inspection of overhead line |
Country Status (1)
Country | Link |
---|---|
JP (1) | JPH0360313A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2004015833A1 (en) * | 2002-08-01 | 2004-02-19 | Unión Fenosa Distribución, S.A. | Method and device for inspecting linear infrastructures |
JP2005057956A (en) * | 2003-08-07 | 2005-03-03 | Central Res Inst Of Electric Power Ind | Method, device, and program for detecting electric wire abnormality by image processing, and method for forming image for electric wire inspection |
JP2008276805A (en) * | 2008-08-04 | 2008-11-13 | Central Res Inst Of Electric Power Ind | Method of creating image for electric wire inspection |
-
1989
- 1989-07-26 JP JP1193268A patent/JPH0360313A/en active Pending
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2004015833A1 (en) * | 2002-08-01 | 2004-02-19 | Unión Fenosa Distribución, S.A. | Method and device for inspecting linear infrastructures |
JP2005057956A (en) * | 2003-08-07 | 2005-03-03 | Central Res Inst Of Electric Power Ind | Method, device, and program for detecting electric wire abnormality by image processing, and method for forming image for electric wire inspection |
JP2008276805A (en) * | 2008-08-04 | 2008-11-13 | Central Res Inst Of Electric Power Ind | Method of creating image for electric wire inspection |
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