• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.344-354
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• 2015

In order to study the development of partial discharge (PD) under typical protrusion defects in gas-insulated switchgear, we applied step voltages on the defect and obtained the ${\varphi}-u$ and ${\varphi}-n$ spectrograms of ultra-high frequency (UHF) PD signals in various PD stages. Furthermore, we extracted seven kinds of features to characterize the degree of deterioration of insulation and analyzed their values, variation trends, and change rates. These characteristics were inconsistent with the development of PD. Hence, the differences of these features could describe the severity of PD. In addition, these characteristics could provide integrated characteristics regarding PD development and improve the reliability of PD severity assessment because these characteristics were extracted from different angles. To explain the variation laws of these seven kinds of parameters, we analyzed the relevant physical mechanism by considering the microphysical process of PD formation and development as well as the distortion effect generated by the space charges on the initial field. The relevant physical mechanism effectively allocated PD severity among these features for assessment, and the effectiveness and reliability of using these features to assess PD severity were proved by testing a large number of PD samples.

• Journal of Electrical Engineering and Technology
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• 제11권1호
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• pp.192-199
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• 2016

With changes in insulated defects, the environment, and so on, new partial discharge (PD) data are highly different from the original samples. It leads to a decrease in on-line recognition rate. The UHF signal and pulse current signal of four kinds of typical artificial defect models in gas insulated switchgear (GIS) are obtained simultaneously by experiment. The relationship map of ultra-high frequency (UHF) cumulative energy and its corresponding apparent discharge of four kinds of typical artificial defect models are plotted. UHF cumulative energy and its corresponding apparent discharge are used as inputs. The support vector machine (SVM) incremental method is constructed. Examples show that the PD SVM incremental method based on simulated annealing (SA) effectively speeds up the data update rate and improves the adaptability of the classifier compared with the original method, in that the total sample is constituted by the old and new data. The PD SVM incremental method is a better pattern recognition technology for PD on-line monitoring.

• 한국산학기술학회논문지
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• 제20권8호
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• pp.181-189
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• 2019

항공기용 전원 분배 장치는 발전기에서 생성된 전원을 분배 및 제어하고, 과전류를 보호하는 역할을 한다. 항공기 비행 중에 교류 전원 분배 장치의 결함으로 인해 교류 전원 분배가 불가능해지는 현상이 다수 발생하였다. 이로 인해 정상적인 교류 전원 분배가 불가능하고 일부 전자장비가 구동을 상실하는 문제점이 제기되었다. 본 논문에서는 결함 발생 조건인 항공기 비행 중 진동 조건을 진동 시험 장비로 모의하여, 결함의 근본 원인을 도출한 과정을 기술하였다. 이를 통해 결함의 원인이 교류 전원 분배 장치의 접촉기가 진동에 의해 내부 배선 손상이 발생한 것임을 확인하였으며, 결함 해소를 위해 접촉기 개선 형상을 도출하였다. 또한 결함이 내재된 접촉기를 검출하기 위해, 진동 시험 장비를 활용한 결함 검출 시험을 수행하는 방식으로 시험 절차를 개선하였다. 개선활동 결과 교류 전원 분배 장치의 결함 현상이 개선되었음을 구성품 인증 시험 및 비행 시험을 통해 입증하였다.

• 한국반도체및디스플레이장비학회:학술대회논문집
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• 한국반도체및디스플레이장비학회 2004년도 춘계학술대회 발표 논문집
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• pp.129-131
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• 2004

극자외선 리소그래피(EUV lithography) 기술은 50nm 이하의 선폭을 가지는 차세대 소자 제작에 있어서 선도적인 기술 중 하나이다. EUVL 에서 필수적인 요소중의 하나가 mirror 로 사용되는 blank mask 이다. Blank mask 에 있어서 가장 중요한 요소는 반사도이다. 이 blank mask 는 Si substrate 위에 반사를 위한 Mo/Si pair 가 40pair 이상 적층되어있다. Blank mask 는 매우 청결해야한다. 만약 결함이 있다면 blank mask 에는 치명적이다 결함은 blank mask 에 있어서 반사도를 떨어뜨리는 주 요소이기 때문이다. 그 결함에는 amplitude defect 과 phase defect 이 있다. FIB 에서는 amplitude defect 을 수정하는 것이 가능하다. 우리는 FIB 를 이용하여 mage mode, spot mode, bar rotation mode 를 사용하여 amplitude defect을 수정하였다. 그리고, 그 결과 효과적으로 amplitude defect을 수정하였다.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.745-755
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• 2023

The wire rope is an indispensable production machinery in coal mines. It is the main force-bearing equipment of the underground traction system. Accurate detection of wire rope defects and positions exerts an exceedingly crucial role in safe production. The existing defect detection solutions exhibit some deficiencies pertaining to the flexibility, accuracy and real-time performance of wire rope defect detection. To solve the aforementioned problems, this study utilizes the camera to sample the wire rope before the well entry, and proposes an object based on YOLOv5. The surface small-defect detection model realizes the accurate detection of small defects outside the wire rope. The transfer learning method is also introduced to enhance the model accuracy of small sample training. Herein, the enhanced YOLOv5 algorithm effectively enhances the accuracy of target detection and solves the defect detection problem of wire rope utilized in mine, and somewhat avoids accidents occasioned by wire rope damage. After a large number of experiments, it is revealed that in the task of wire rope defect detection, the average correctness rate and the average accuracy rate of the model are significantly enhanced with those before the modification, and that the detection speed can be maintained at a real-time level.

• International Journal of Contents
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• 제13권2호
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1271-1280
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• 2020

The yield and quality of a micromanufacturing process are important management factors. In real-world situations, it is difficult to achieve a high yield from a manufacturing process because the products are produced through multiple nanoscale manufacturing processes. Therefore, it is necessary to identify the processes and equipment that lead to low yields. This paper proposes an analytical method to identify the processes and equipment that cause a defect in the plastic ball grid array (PBGA) during the manufacturing process using logistic regression and stepwise variable selection. The proposed method was tested with the lot trace records of a real work site. The records included the sequence of equipment that the lot had passed through and the number of faults of each type in the lot. We demonstrated that the test results reflect the real situation in a PBGA manufacturing process, and the major equipment parameters were then controlled to confirm the improvement in yield; the yield improved by approximately 20%.

• 한국해양공학회지
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• 제13권4호통권35호
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• pp.45-54
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• 1999

Non destructive test is applied to revise mechanical strength and assume material strength or defect of material, equipment and structure, instead of fracture test. Especially, ultrasonic test has the characteristics such as an excellent permeability high-sensitiveness to fine defect and an almost exact measurement for position, size and direction of inner defect which differ from other non destructive tests. In this study, the program is developed to evaluate optimal testing condition, to distinguish obstacle echo and defect position. This program on the basic of Ray-Tracing model shows generation and processing of ultrasonic pulse. The simulation is compared with testing in the 3 cases of an oblique angle transducer like $45^{\circ},\;60^{\circ}\;and\;70^{\circ}$. The test result for all conditions is well compared with simulation result when relative not is within $0.1{\sim}7.2%$. And the course of several echos is simply assumed through simulation.

• 소성∙가공
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• 제19권3호
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• pp.173-178
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• 2010

A die cast impeller blade has been developed in the effort on cost reduction in marine equipment industry. The purpose of this work is to optimize the die casting process using Taguchi's design of experiment for minimizing the internal defect of the die cast impeller blade. The experiments were preformed using the numerical simulation based on the L18 orthogonal array. As a results, the internal defect size of the die cast impeller blade for optimal design was controlled less than 1mm.

• 반도체디스플레이기술학회지
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• 제20권1호
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• pp.99-103
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• 2021

Warpage defect detecting of scaffold is very important in biosensor production. Because warpaged scaffold cause problem in cell culture. Currently, there is no detection equipment to warpaged scaffold. In this paper, we produced detection model for shape warpage detection using deep learning based CNN. We confirmed the shape of the scaffold that is widely used in cell culture. We produced scaffold specimens, which are widely used in biosensor fabrications. Then, the scaffold specimens were photographed to collect image data necessary for model manufacturing. We produced the detecting model of scaffold warpage defect using Densenet among CNN models. We evaluated the accuracy of the defect detection model with mAP, which evaluates the detection accuracy of deep learning. As a result of model evaluating, it was confirmed that the defect detection accuracy of the scaffold was more than 95%.