• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.9-14
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• 2018

The vision system is a device for acquiring images and analyzing and discriminating inspection areas. Demand for use in the automation process has increased, and the introduction of a vision-based inspection system has emerged as a very important issue. These vision systems are used for everyday life and used as inspection equipment in production processes. Image processing technology is actively being studied. However, there is little research on the area definition for extracting objects such as character recognition or semiconductor packages. In this paper, define a region of interest and perform edge extraction to prevent the user from judging noise as an edge. We propose a noise-robust alignment correction model that can extract the edge of a region to be inspected using the distribution of edges in a specific region even if noise exists in the image. Through the proposed model, it is expected that the product production efficiency will be improved if it is applied to production field such as character recognition of tire or inspection of semiconductor packages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.141-146
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• 1998

Recently, the computer vision such as part measurement, and product inspection is very popular to achieve the factory automation since the labor cost is dramatically increasing. In this paper, the diameter and the length of rope are measured by CCD camera which is orthogonally mounted on the ceiling. Two parameters which are the diameter and the length of rope are used to measure the weight of rope. If the weight of rope is reached to predetermined weight, the information is transmitted to PLC(programmable logic control) to cut the rope on the wheel. The cutting machine cuts the rope according to the information obtained from the CCD camera. To measure the diameter and length of rope on real time, the searching space for image segmentation is restricted the predetermined area according to the camera calibration position. Finally, to estimate the weight of rope, the knowledge base system which depends on the diameter, the length of rope, and weight relation between these information are constructed according to diameters of rope. This method contributes to achieve the factory automation, and reduce the production cost since the operators are unnecessary to measure the weight of rope by try-and-error method.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.372-381
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• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.12
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• pp.30-37
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• 1996

On-line process control equipment for CO$_{2}$ laser cutting is not available for industrial applications. The major part of the industrial laser cutting machines are adjusted off-line by highly educated engineers. The quality inspection of the sample is visual and referred to different quality scales. Due to the lack of automation the potential laser users hesitate to implement the cutting method. The first step toward an automation of the process is the development of a process monitoring system and the research is cincentrated on the area of on-line quality monitoring during CO$_{2}$ laser cutting. The method is based on the detection of the emitted light from the cutting front by photo diode. The developed monitoring system consists of the OP Amplifier, A/D convertor, power supply and PC. The signal from the photo diode has been undertaken from Fourier analysis and statistical analysis with real time. The photograph of striation pattern was taken by metallurgical microscope. As a result, it is possible to predict the striation pattern according to the beam traveling speed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.76-83
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• 2023

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.393-400
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• 1992

The DC(Direct-Current) servo motor has widely used for many application areas, FA(Factory Automation), OA(Office Automation) and home applications. But DC servo motor needs periodical inspection because it has brush and commutator. Recently, AC servo motor has expanded it's application areas due to for the development of the power semi-conductor and control technology. But it has large torque ripple for it's small number of commutation. And it also has cogging torque due to permanent magenet rotor. Therefore it can't run balence rotarion. Many torque ripple reduction methods are published. In this paper, phase advanced method adopted for torque ripple reduction of AC servo motor. In this research, AC servo motor torque characteristic variation surveied under the phase advance control through the computer simulation. Under the simulation, the load inertia varied from 0.0001[Kg.m$^{2}$] to 0.0314[Kg.m$^{2}$]. The result os nonlinear simulation, torque and speed ripple of AC servo motor under the phase advance control reduced approximately 50[%] and 10[%]. And maximum torque of AC servo motor under phase advance control condition increased about 5[%] as compare with fixed switching time.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.11
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• pp.163-170
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• 2019

Most of the current crack investigation work consists of visual inspection using simple measuring equipment such as crack scale. These methods involve the subjection of the inspector, which may lead to differences in the inspection results prepared by the inspector, and may lead to a large number of measurement errors. So, this study proposes an image-based crack detection method to enhance objectivity and efficiency of concrete crack investigation. In this study, YOLOv2 was used to determine the presence of cracks in the image information to ensure the speed and accuracy of detection for real-time analysis. In addition, we extracted shapes of cracks and calculated quantitatively, such as width and length using various image processing techniques. The results of this study will be used as a basis for the development of image-based facility defect diagnosis automation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.937-943
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• 2009

In this paper, the algorithm discriminating the existence and nonexistence of bolts and nuts using image processing in an automobile T-Bar influencing the vibration of a frame, is introduced. To distinct whether bolts and nuts exist or not, the features of bolts and nuts are learned, and then these feature values are matched using a statistical pattern matching algorithm. Furthermore, the minimum and maximum variation rate of pixel values are used since the matching rate is low with the large variation of pixel values of bolts and nuts in each image. The proposed method in this paper is very efficient in the automation of inspection requiring real time since the inspection time is significantly reduced compared with the conventional methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1016-1021
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• 2003

The overall size of electronic product is becoming small according to development of technology. Accordingly it is difficult to inspect these small components by human eyes. So, an automation system for inspecting them has been used. The existing system put microprocessor or Programmable Logic Controller (PLC) use. The structure of microprocessor-based controller and PLC use basically composed of memory devices such as ROM, RAM and I/O ports. Accordingly, the system is not only becomes complicated and enlarged but also higher price. In this paper, we implement FPGA-based One-chip Programmable Timing Controller for Inspecting Small components to resolve above problems and design the high performance controller by using VHDL. With fast development, the FPGA of high capacity that can have memory and PLL have been introduced. By using the high-capacity FPGA, the peripherals of the existent controller, such as memory, I/O ports can be implemented in one FPGA. By doing this, because the complicated system can be simplified, the noise and power dissipation problems can be minimized and it can have the advantage in price. Since the proposed controller is organized to have internal register, counter, and software routines for generating timing signals, users do not have to problem the details about timing signals and need to only send some values about an inspection system through an RS232C port. By selecting theses values appropriate for a given inspection system, desired timing signals can be generated.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2737-2749
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• 1998

Recently, vision system is widely used in factory automation processes. In this paper, the method which detects the badness in the position, slop, and the lead of chips is proposed for the inspection of semiconductor chips. The conventional methods mainly inspect semiconductor IC with the features which is extracted in image. But we propose the method which segments the lead part by the morphology and inspects the lead faults by the invariant moment. In the simulation. the results of the proposed method is better than those of the conventional method for the noisy and noiseless images .