• Title/Summary/Keyword: 성능진단기법

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A Study on Engine Health Monitoring using Linear Gas Path Analysis for Turboprop Engine (선형 GPA 기법을 이용한 터보프롭 엔진의 성능진단에 관한 연구)

  • 공창덕;신현기;기자영
    • Journal of the Korean Society of Propulsion Engineers
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    • v.3 no.4
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    • pp.93-103
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    • 1999
  • The steady-state performance analysis program for turboprop engine which was used for a small, middle industrial aircraft and a basic trainer aircraft was developed and linear Gas Path Analysis method was applied to Engine Health Monitoring for Turboprop engine. This program was compared with TURBOMARCH program which is well known with performance and power according to flight Mach No. at the standard atmospheric condition to prove a steady-state performance analysis program. From the result, inlet, exit temperature and pressure of each component had error within 3% and especially power according to flight Mach No. had error within 2.4% so that this program could be assured. To make sure if linear Gas Path Analysis is reasonable four cases were selected. The first is the case that fouling is occurred in compressor only. The second is the case that fouling is occurred in compressor and erosion is occurred in turbine. The third is the case that erosion is occurred in both compressor and turbine and power turbine at the same time. Finally, the case that fouling and erosion are occurred in compressor, compressor turbine and power turbine was selected. Different parameters were selected impartially among the independent parameters so that the effect of measurement parameter selection was observed. From the result, the more measurement parameters the smaller RMS error and even though the number of measurement parameters was the same, the RMS error was obtained differently according to which measurement parameters were selected. The case using eight instrument parameters of case IV-4 had small error comparably and was economic and it was important to select optimal number of measurement and optimal measurement parameters.

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Instrumentation Performance Measurement Technique for Evaluating Efficiency of Binary Analysis Tools (바이너리 분석도구 효율성 평가를 위한 Instrumentation 성능 측정기법)

  • Lee, Minsu;Lee, Jehyun;Kim, Hobin;Ryu, Chanho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.6
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    • pp.1331-1345
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    • 2017
  • Binary instrumentation has been developed for monitoring and debugging executables without their source codes. Previous efforts on the binary instrumentation are mainly focused on its capability and accuracy, but not on efficiency for practical application. In particular, criteria and measurement methodologies for evaluating and comparing the efficiency of binary investigation tools and algorithms do not estimated yet. In this paper, we propose the instrumentation primitives which are a unit functionality and measurement methodology. Through the empirical experiments by adopting the proposed methodology on DynamoRIO and Pin, we show the feasibility of the proposal.

A Distributed Real-time Self-Diagnosis System for Processing Large Amounts of Log Data (대용량 로그 데이터 처리를 위한 분산 실시간 자가 진단 시스템)

  • Son, Siwoon;Kim, Dasol;Moon, Yang-Sae;Choi, Hyung-Jin
    • Database Research
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    • v.34 no.3
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    • pp.58-68
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    • 2018
  • Distributed computing helps to efficiently store and process large data on a cluster of multiple machines. The performance of distributed computing is greatly influenced depending on the state of the servers constituting the distributed system. In this paper, we propose a self-diagnosis system that collects log data in a distributed system, detects anomalies and visualizes the results in real time. First, we divide the self-diagnosis process into five stages: collecting, delivering, analyzing, storing, and visualizing stages. Next, we design a real-time self-diagnosis system that meets the goals of real-time, scalability, and high availability. The proposed system is based on Apache Flume, Apache Kafka, and Apache Storm, which are representative real-time distributed techniques. In addition, we use simple but effective moving average and 3-sigma based anomaly detection technique to minimize the delay of log data processing during the self-diagnosis process. Through the results of this paper, we can construct a distributed real-time self-diagnosis solution that can diagnose server status in real time in a complicated distributed system.

Disease Classification using Random Subspace Method based on Gene Interaction Information and mRMR Filter (유전자 상호작용 정보와 mRMR 필터 기반의 Random Subspace Method를 이용한 질병 진단)

  • Choi, Sun-Wook;Lee, Chong-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.192-197
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    • 2012
  • With the advent of DNA microarray technologies, researches for disease diagnosis has been actively in progress. In typical experiments using microarray data, problems such as the large number of genes and the relatively small number of samples, the inherent measurement noise and the heterogeneity across different samples are the cause of the performance decrease. To overcome these problems, a new method using functional modules (e.g. signaling pathways) used as markers was proposed. They use the method using an activity of pathway summarizing values of a member gene's expression values. It showed better classification performance than the existing methods based on individual genes. The activity calculation, however, used in the method has some drawbacks such as a correlation between individual genes and each phenotype is ignored and characteristics of individual genes are removed. In this paper, we propose a method based on the ensemble classifier. It makes weak classifiers based on feature vectors using subsets of genes in selected pathways, and then infers the final classification result by combining the results of each weak classifier. In this process, we improved the performance by minimize the search space through a filtering process using gene-gene interaction information and the mRMR filter. We applied the proposed method to a classifying the lung cancer, it showed competitive classification performance compared to existing methods.

Pipeline Structural Damage Detection Using Self-Sensing Technology and PNN-Based Pattern Recognition (자율 감지 및 확률론적 신경망 기반 패턴 인식을 이용한 배관 구조물 손상 진단 기법)

  • Lee, Chang-Gil;Park, Woong-Ki;Park, Seung-Hee
    • Journal of the Korean Society for Nondestructive Testing
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    • v.31 no.4
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    • pp.351-359
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    • 2011
  • In a structure, damage can occur at several scales from micro-cracking to corrosion or loose bolts. This makes the identification of damage difficult with one mode of sensing. Hence, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In the self sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this study, an experimental study on the pipeline system is carried out to verify the effectiveness and the robustness of the proposed structural health monitoring approach. Different types of structural damage are artificially inflicted on the pipeline system. To classify the multiple types of structural damage, a supervised learning-based statistical pattern recognition is implemented by composing a two-dimensional space using the damage indices extracted from the impedance and guided wave features. For more systematic damage classification, several control parameters to determine an optimal decision boundary for the supervised learning-based pattern recognition are optimized. Finally, further research issues will be discussed for real-world implementation of the proposed approach.

A Study on the Embodiment of Fuzzy Logic (퍼지 이론을 실생활 적용구현 연구)

  • 정정민;최성
    • Proceedings of the KAIS Fall Conference
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    • 2002.05a
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    • pp.243-247
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    • 2002
  • 현재 인간의 지능을 모방하는 인공지능 기법은 인간 친화적인 시스템의 자동화, 제품의 성능 향상 등 공학분야에 적용되기 시작하였고, 병의 진단 및 판정 , 경영의사 결정 등의 사회과학 분야까지 그 응용분야가 확대되고 있다. 이러한 인공지능을 컴퓨터에 의한 언어적 추론의 개념과 방법을 연구하여 추론하는데 사용되는 지식을 언어적으로 표현하는 것을 연구하였고, 인간이 서로간의 지능적이라고 인식하는 대로 행동하도록 컴퓨터가 만들어질 수 있는 가능성을 추구하는 분야 즉 인공지능을 실현하는데, 원론이 되는 퍼지의 이론을 중심으로 연구하였다.

Authentication System based on Image Synthesis (이미지 합성을 이용한 인증 시스템)

  • 박봉주;김수희;차재필
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.646-648
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    • 2003
  • 본 연구는 이미지 합성을 이용하여 서버가 사용자를 인증하기 위한 알고리즘을 개발하고 이들을 구현하여 그 성능을 평가하고 분석한다. 서버는 사용자가 소지하는 사용자카드를 랜덤하게 점을 찍어 생성하고, 각 사용자에게 배포된 사용자카드의 정보를 유지.관리한다. 한 사용자로부터 인증요청이 들어오면, 서버는 그 사용자의 사용자카드 정보를 기반으로 서버카드를 실시간에 생성하여 사용자에게 송신한다. 서버카드는 인증마다 다르게 생성되므로 원타임 패스워드 챌린지(challenge) 역할을 한다. 사용자는 본인이 소유하고 있는 사용자카드와 서버로부터 송신된 서버카드를 겹쳤을 때 생성되는 이미지를 판독하여 인증을 수행한다. 보안성을 높이면서 이미지 판독을 효율적으로 하기 위해 다양한 기법을 제시하고 구현을 통하여 실용성을 진단한다.

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Assessment and Retrofitting of Existing Bridges (기존 교량의 평가 및 보강)

  • Kang, Su Tae;Kwon, Seung Hee
    • Magazine of the Korea Institute for Structural Maintenance and Inspection
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    • v.16 no.2
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    • pp.74-86
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    • 2012
  • 이태리를 비롯한 대부분의 유럽 국가들에 건설된 많은 기존 도로 및 철도 교량들 중에는 현재의 구조설계기준이나 교통시스템, 유지관리비용 절감 등을 고려한 요구조건과 비교했을 때 구조적 안전성과 기능성을 만족시키지 못하는 경우가 종종 있다. 따라서 어떤 형식의 교량이든 특정 취약성을 평가할 수 있는 신속하고 신뢰성 있는 방법론이 필요하다. 이 논문의 앞부분은 이태리 내 도로 및 철도 구조물에 대해 그런 형태의 방법론의 적용에 대해 기술하였으며, 그 결과를 보면, 한 예로 조적조 아치 교량이 일반적으로 상당히 건전한 구조 시스템으로 나타났으며 RC 교량은 일반적으로 내구성 문제를 드러내며 지진하중에 대해서도 취약한 것으로 나타났다. 강교량은 내구성 문제 외에 피로에 특히 취약한 것으로 나타났다. 그리고 이 논문에서 고려한 전형적인 보강기법들에 대해 간략히 소개하였다. 뒷부분에서는 네 개의 기존 RC교량을 중심으로 주요 교량보강 사례연구들에 대해 좀 더 자세히 기술하였다. 이 교량들은 2차 세계대전 이후에 가장 일반적으로 채택되던 형식들 중의 한 예로 보강기법의 일반적 성질을 고찰하는데 있어 적합하다. 교량의 성능개선에 대해서는 방법론적 접근에 대해 개략적으로 나타내었으며, 여기에는 구조물의 유형적 특성, 유지관리 현황, 기능적 요구조건 및 보수 보강 시스템과 연계된 환경적인 면을 고려하고 있다.

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Non-contact Impact-Echo Based Detection of Damages in Concrete Slabs Using Low Cost Air Pressure Sensors (저비용 음압센서를 이용한 콘크리트 구조물에서의 비접촉 Impact-Echo 기반 손상 탐지)

  • Kim, Jeong-Su;Lee, Chang Joon;Shin, Sung Woo
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.15 no.3
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    • pp.171-177
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    • 2011
  • The feasibility of using low cost, unpowered, unshielded dynamic microphones is investigated for cost effective contactless sensing of impact-echo signals in concrete structures. Impact-echo tests on a delaminated concrete slab specimen were conducted and the results were used to assess the damage detection capability of the low cost system. Results showed that the dynamic microphone successfully captured impact-echo signals with a contactless manner and the delaminations in concrete structures were clearly detected as good as expensive high-end air pressure sensor based non-contact impact-echo testing.

Evaluation of Seismic Safety in School Buildings Applying Artificial Seismic Waves in Earthquake Magnitude of Korea (한국형 중진지역의 인공지진파 생성을 통한 학교건물 내진안전성 평가)

  • Kim, Seung-Hyun;Park, Young-Binuk;Kang, Jun-Suk
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.1
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    • pp.10-18
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    • 2022
  • This report describes the development and stability evaluation of a seismic retrofit method to evaluate the seismic performance of existing school buildings by analyzing the earthquake waveforms that occurred in Korea. Currently, Facilities for seismic retrofit designed for excessive reinforcement are being applied. To compensate for this, optimised the retrofit mothod suitable for domestic situation considering the characteristics of the seismic region, generated a Korean-style artificial seismic wave that meets the seismic design criteria, which is less frequent than other countries.