• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 전기설비전문위원
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• pp.86-88
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• 2009

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pre-treatment process of fault currents by each cause acquired from the fault recorder into a phase space in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.645-646
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• 2012

• 한국안전학회지
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• 제19권1호
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• 한국주조공학회지
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• 제42권6호
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• pp.369-376
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• 2022

다이캐스팅 공정은 다양한 산업군의 인프라 역할을 수행하는 중요한 공정이지만, 높은 불량률로 인하여 관련 기업들의 수익성 및 생산성의 한계가 있는 상황이다. 이를 타개하기 위하여, 본 연구에서는 다이캐스팅 공정의 불량 검출을 위한 산업인공지능 기반 모듈을 구성하였다. 개발된 불량 검출 모듈은 제공되는 데이터의 특징에 따라서 3단계로 동작되는 모델로 구성된다. 1단계 모델은 비지도학습 기반 이상 검출을 진행하며, 레이블이 없는 데이터셋을 대상으로 작동한다. 2단계 모델은 반지도학습 기반으로 이상 검출을 진행하며, 양품 데이터의 레이블만 존재하는 데이터셋을 대상으로 작동하며, 3단계 모델은 소수의 불량 데이터가 제공된 상황의 지도학습 모델을 기반으로 작동한다. 개발된 모델은 실제 다이캐스팅 양품 데이터를 바탕으로 96% 이상의 우수한 양품 검출 성능을 보였다.

• 한국생산제조학회지
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• 제9권4호
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• pp.108-116
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• 2000

Undesired trouble such as chatter vibration and burning on the ground surface appears frequently in the cylindrical plunge grinding process. Establishment of a credible fault diagnostic system for the grinding process is the major purpose of this study. Power signals generated during the grinding operation were sampled and analyzed to determine the relationship between grinding troubles and behavior of signal changes. In addition, a neural network was optimized with a momentum coefficient a learning rate, and a structure of the hidden layer through the iterative learning process. Based on the established system, success rates of the trouble recognition were verified.

• 한국안전학회지
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• 제18권2호
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• pp.64-72
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• 2003

A new reliability assessment methodology is presented and the new method is compared with fault tree analysis. The system is modeled by directed graph at a new methodology, which is composed of nodes and arcs. The directed graph corresponds to the layout of chemical process and is easy to construct. Therefore, the directed graph analysis is applicable to the chemical process that has complex sequence. The example of fault tree analysis and directed graph analysis is given. The directed graph analysis has proved to be a valuable and useful method for the reliability assessment of chemical process.

• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.121-125
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• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

• 한국콘텐츠학회논문지
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• 제6권11호
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• pp.266-275
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• 2006

조립체 공정은 많은 부분이 자동화 되었지만 결함 진단 부분에서는 포괄적인 의사 결정을 지원하기 위해 다양한 분야의 전문성과 지식을 필요로 하기 때문에 자동화가 이루어지지 않고 있다. 본 논문에서는 다양한 분야의 전문가가 쉽게 접근할 수 있고 직관적으로 이해할 수 있는 영상 정보를 이용한 조립체 결함 분석 지원시스템을 제안한다. 본 시스템은 영상 정보와 제품 설계 정보 그리고 결함탐지 정보를 병합함으로써 조립체에서 효과적으로 결함을 분석하도록 지원한다. 제안된 방법은 라벨링을 이용하여 조립체의 영상을 부품 단위로 분할하고 확장된 속성 관계 그래프(eARG)를 사용하여 설계 정보와 결함 분석 정보를 일관되게 표현하여 결함 정보를 영상 정보로부터 접근할 수 있도록 한다.

• Geomechanics and Engineering
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• 제24권5호
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• pp.471-478
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• 2021

Water damage is one of the five disasters that affect the safety of coal mine production. The erosion of rocks by water is a very important link in the process of water inrush induced by fault activation. Through the observation and experiment of fault filling samples, according to the existing rock classification standards, fault sediments are divided into breccia, dynamic metamorphic schist and mudstone. Similar materials are developed with the characteristics of particle size distribution, cementation strength and water rationality, and then relevant tests and analyses are carried out. The experimental results show that the water-rock interaction mainly reduces the compressive strength, mechanical strength, cohesion and friction Angle of similar materials, and cracks or deformations are easy to occur under uniaxial load, which may be an important process of water inrush induced by fault activation. Mechanical experiment of similar material specimen can not only save time and cost of large scale experiment, but also master the direction and method of the experiment. The research provides a new idea for the failure process of rock structure in fault activation water inrush.

• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.107-116
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• 2003

This paper presents a systematic design methodology for fault tolerant controller against a fault in actuators and sensors of linear stochastic systems with uncertainties. The scheme is based on fault detection and diagnosis(isolation and estimation) using a bank of robust two-stage Kalman filters, and accommodation of the actuator fault by eigenstructure assignment and immediate compensation of the sensor's faulty measurement. In order to clarify the fault feature in test statistics of residual, noise reduction method is given by multi-scale discrete wavelet transform. The effectiveness of our approach Is shown via simulations for a VTOL(vertical take-off and landing) aircraft subjected to parameter variations, external disturbances, process and sensor noises.