• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.271-278
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• 2020

KEPCO Research Institute developed a GIS-based autopilot drone inspection system for electric power facilities and since its pilot application in 2017, it has been successfully used to detect defects in power transmission lines. This paper presents how to operate this system in the field of power line inspection. Power transmission lines are located in a wide variety of environments such as plains, mountains, river crossings, sea crossings, and industrial areas. Among these, some transmission lines are difficult for human workers to access because of their geographies and some should be checked more often due to their severe contamination. Considering these field conditions, we classified drone operation in two categories to increase its effectiveness and efficiency - patrol surveillance and detailed inspection tasks. This paper describes the detailed procedures of the two tasks above and their field application experiences. In addition, this paper newly proposes how to construct public drone roads by using the information of KEPCO's power transmission lines.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.300_301
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• 2009

765kV Transmission line is retained and operated by KEPCO(Korea Electric Power Corporation), and KPS(Korea Power Plant Service & Engineering) has been taking charge of maintenance service. KPS is doing characteristic maintenance and inspection for 765kV lines for example preventive patrol, routine patrol(every 6-month), and close inspection(every 5-year), This paper presents the optimum maintenance methods and the related standards for 765kV line. This result will use to stabilize of 765kV lines.

• Journal of Biosystems Engineering
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• v.24 no.3
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• pp.253-258
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• 1999

This study was conducted to develop an automatic egg inspection system for detecting creaked eggs based on acoustic impulse response. This system includes a sound generator, a sound sensor with signal conditioner, and a computer. The sound generator that hit the sharp of the dull edges of an egg was constructed with a ceramic ball pendulum attached to a rotary type solenoid. The signal conditioner included a pre-amplifier and a digital signal processing (DSP) board. The parameters for distinguishing cracked and normal eggs were the area, the geometric centroid and the resonance frequency of power spectrum of the acoustic signal generated. An algorithm for on-line detection of the continuous transferring eggs was developed. The performance tests resulted with 91% success rate to separate cracked and normal eggs at the rate of 1 second per an egg.

• 연구논문집
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• s.31
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• pp.135-147
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• 2001

The wall-thickness of insulated pipelines can be easily evaluated by measuring the gamma-ray transmission intensity because this intensity is inversely proportional to the thickness of insulated pipeline. The main purpose of this study is to develop the nondestructive and filmless on-line inspection system of corrosion by measuring the wall thickness of insulated pipeline. The inspection system is constructed with radioisotope, 64 channel photo diode array detector, crawler system and data taking and operating software. The traditional off-line radiographic method carried out by exposing film cassettes can be replaced by this cost-effective on-line digital imaging method and the application will be greatly expected especially in the chemical and petrochemical industries.

• Nuclear Engineering and Technology
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• v.43 no.2
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• pp.133-140
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• 2011

In this paper, a deformation measurement technology for nuclear fuel rods is proposed. The deformation measurement system includes a high-definition CMOS image sensor, a lens, a semiconductor laser line beam marker, and optical and mechanical accessories. The basic idea of the proposed deformation measurement system is to illuminate the outer surface of a fuel rod with a collimated laser line beam at an angle of 45 degrees or higher. For this method, it is assumed that a nuclear fuel rod and the optical axis of the image sensor for observing the rod are vertically composed. The relative motion of the fuel rod in the horizontal direction causes the illuminated laser line beam to move vertically along the surface of the fuel rod. The resulting change of the laser line beam position on the surface of the fuel rod is imaged as a parabolic beam in the high-definition CMOS image sensor. An ellipse model is then extracted from the parabolic beam pattern. The center coordinates of the ellipse model are taken as the feature of the deformed fuel rod. The vertical offset of the feature point of the nuclear fuel rod is derived based on the displacement of the offset in the horizontal direction. Based on the experimental results for a nuclear fuel rod sample with a formation of surface crud, an inspection resolution of 50 ${\mu}m$ is achieved using the proposed method. In terms of the degree of precision, this inspection resolution is an improvement of more than 300% from a 150 ${\mu}m$ resolution, which is the conventional measurement criteria required for the deformation of neutron irradiated fuel rods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.773-781
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• 2018

In recent years, a study of power-line inspection using an unmanned aerial vehicle (UAV) has been actively conducted. However, relevant studies have been conducting power-line inspection with an UAV operated by manual control, and they have developed just power-line detection algorithm on aerial images. To overcome limitations of existing research, we propose a drone-based power-line tracking system in this paper. The main contributions of this paper are to operate developed system under configured environment and to develop a power-line detection algorithm in real-time. Developed system is composed of the power-line detection and the image-based tracking control. To detect a power-line in real-time, a region of interest (ROI) image is extracted. Furthermore, clustering algorithm is used in order to discriminate the power-line from background. Finally, the power-line is detected by using the Hough transform, and a center position and a tilt angle are estimated by using the Kalman filter to control a drone smoothly. We design a position controller and an attitude controller for image-based tracking control, and both controllers are designed based on the proportional-derivative (PD) control method. The interaction between the position controller and the attitude controller makes the drone track the power-line. Several experiments were carried out in environments where conditions are similar to actual environments, which demonstrates the superiority of the developed system.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.15-21
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• 2013

In this paper, sensor system and inspection algorithm in order to inspect steel balance weight for automobile is described. Steel balance weight is composed of clip and weight, which is joined by press process. The defective one has a gap between clip and weight. To detect whether there is a gap, sensor system is simply configured with laser line projector and USB camera, which make it possible to measure the height difference of clip and weight area. Laser line pattern which is made on the surface of a balance weight is captured by USB camera. In case that USB camera is used in machine vision, barrel distortion caused by wide angle lens makes the captured image distorted. Image warping function is applied to correct the distortion. Simple image processing algorithm is applied to extract the laser line information and whether it is good or not is judged through the extracted information.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.106-110
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images. 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc. A total of seven images, that is, one color image form the top of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filtered image and the other is 970 nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results with Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defect and shape were 95.3%, 86% and 88.6%, respectively. Grading time was 0.35 second per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.551-559
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images, 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc., so that a total of seven images, that is, one color image from the top side of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filter image and the other is 970nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results to the Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defective and shape were 95.3%, 86% and 91%, respectively. Grading time was 0.35 sec per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.