• E2M - 전기 전자와 첨단 소재
• /
• 제8권5호
• /
• pp.551-557
• /
• 1995

For the observation of treeing, a visual measurement with an optical microscope has been used to explain breakdown mechanism in high-voltage systems. The conventional directed visual method of tree aging observation is difficult to measure in short time processing, and it is impossible to analyze on tree degradation area, progressed direction, tree pattern, etc. By using an image processing technique, the tree features which appear immediately after the tree initiation as well as changes in the configuration of the tree can be easily measured and observed than using the conventional visual methods. In this paper, we have developed a tree observating system by using image processing for tree growth, degradation area and other treeing progress. As an experimental result, it can be concluded that the image processing method is a more effective alternative than directed visual observation method. As a matter of fact, it is possible to record the image of tree propagation immediately after its first appearance and explain the characteristics of tree growth froth the computer processing image.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2001년도 하계학술대회 논문집
• /
• pp.319-322
• /
• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2001년도 추계학술대회 논문집
• /
• pp.270-273
• /
• 2001

Electrical tree is studied widely by manufacture state of insulating material fare and blazing fire diagnosis system of use in phenomenon of part discharge that happen for main cause of dielectric breakdown of equipment for electric power. Use process that draw tree pattern here measuring above zero to study special quality of this electricity tree, real-time processing by image processing is proposed because reproduction of tree blazing fire process drops and pattern of tree is difficult correct quantification of tree growth by existent visual observation by involution. This research presents general process that need in image processing of tree blazing fire, and that remove various noises that happen in above zero by measuring electrical tree dividing background and complete view in measured above zero taking advantage of specially proposed complete view object abstraction techniques effectively and quantification of tree becomes easy naturally, can apply to dielectric breakdown estimate because can chase growth process of tree.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 1990년도 추계학술대회 논문집
• /
• pp.1-16
• /
• 1990

In this paper, a system to measure treeing degradation phenomena in organic insulating materials, using an image sensor, is discussed. Using an image processing technique, tree features immediately after tree initiation as well as changes in the configuration of the tree were measured. which up to now have been extremely difficult to observe by conventional visual methods. As a result, it was possible to record the image of tree propagation immediately after its first appearance, and to describe the specific characteristics of tree growth in terms of the length, the degraded area and the sequential images.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
• /
• pp.450-452
• /
• 1995

The Tree observation technique is being highlighted as a research area for deterioration of insulation because of high-voltage power system. For the measurement of tree, image processing is actively studied as a experimental technique of electrical tree, because the conventional directed visual method is impossible to analyze on tree degradation area and tree pattern. In this paper, we have developed the tree measuring system using image processing. By using an image processing technique, the treeing can be easily measured and effectively observed.

• 한국조명전기설비학회지:조명전기설비
• /
• 제8권1호
• /
• pp.57-62
• /
• 1994

영상처리 방식을 이용하여 유기 절연재료의 트리잉 열화를 측정하였다. 전통적으로 목측(가시측정)에 의한 트리현상 변화를 관찰해 왔으나 트리형상 특징과 변화를 이해하는데 정확한 측정에 어려움을 만들었다. 영상처리 시스템을 이용한 트리 측정장치를 이용하여 트리진전길이와 열화면적들의 고유특성을 영상처리 시스템을 이용하여 목측치와 거의 대등한 결과가 나오는 트리진전 영상처리 자동계측 시스템을 구현하였다.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2001년도 추계학술대회 논문집 Vol.14 No.1
• /
• pp.270-273
• /
• 2001

Electrical tree is studied widely by manufacture state of insulating material fare and blazing fire diagnosis system of use in phenomenon of part discharge that happen for main cause of dielectric breakdown of equipment for electric power. Use process that draw tree pattern here measuring above zero to study special quality of this electricity tree, real-time processing by image processing is proposed because reproduction of tree blazing fire process drops and pattern of tree is difficult correct quantification of tree growth by existent visual observation by involution. This research presents general process that need in image processing of tree blazing fire, and that remove various noises that happen in above zero by measuring electrical tree dividing background and complete view in measured above zero taking advantage of specially proposed complete view object abstraction techniques effectively and quantification of tree becomes easy naturally, can apply to dielectric breakdown estimate because can chase growth process of tree.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 1999년도 춘계학술대회 논문집
• /
• pp.712-715
• /
• 1999

Treeing has a profit to observe processing electrical breakdown because it gives degradation steps of insulation material by optical method. But, reappearance properly of treeing is not so good and precise quantization of tree growth is not so easy because tree Patterns are very complicate. The study on tree growth using image processing is predicted to precision of tree degradation and possible to quality measurement of tree pattern. In this paper, degradation steps are analyzed by image processing, therefore precision and realiability of tree growth are increased. Also, processing of tree degradation is quantized by fractal.

• 한국전기전자재료학회논문지
• /
• 제14권1호
• /
• pp.26-33
• /
• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pas- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this prediction system was acquired $\pm$3.2% error range.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 1994년도 추계학술대회 논문집
• /
• pp.122-128
• /
• 1994

Studies on treeing phenomena have depended on the visual measurement using optical microscope. In the visual measurement, it is difficult to analyze the treeing in real time because voltages are applied discontinuously and impossible to calculate the deterioated area by treeing. Only tree type and length are studied. In this paper, image processing is introduced and voltages are applied continuously. The tree length and area are calculated in real time from tree inception to breakdown. Growing characteristics about tree types are compared for the normalized breakdown time.