• Smart Structures and Systems
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• 제29권1호
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• 한국항행학회논문지
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• 제27권5호
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• pp.643-648
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• 2023

한국형 위성항법보정시스템 KASS(Korea Augmentation Satellite System)은 2023년 12월 국제민간항공기구 표준의 항공용 서비스 제공을 목표로 개발 중인 SBAS 시스템이다. KASS 서비스의 지속적인 제공을 위해서는 시스템의 상태감시가 필수적이며 이를 위해 상태감시 도구가 개발되어야 한다. 상태감시 도구 개발은 목적에 따라 실시간 상태감시, 장기간 상태감시로 구분되어 개발되었다. 도구 개발은 요구사항 정의, 설계, 개발, 검증의 일련의 절차를 통해 완료하였다. 상태감시 도구 검증을 위해 실제 KASS 시스템의 2023년 8월 데이터를 활용하여 검증하였고 그 결과를 통계적으로 분석하여 운영시간, 운영률을 도출하였다. 2023년 이후부터 시작되는 항공용 서비스에 이 도구들을 활용하여 지속적 서비스 제공을 지원할 계획이다.

• 한국식품조리과학회지
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• 제8권2호
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• pp.137-145
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• 1992

A computer-assisted microbiological quality assurance program was developed based on HACCP data obtained from a 500 bed general hospital by assessing time and temperature conditions and microbiological qualities of six categories of menu items according to the process of food product flow. The purpose of the study was to develop a computer-assisted microbiological quality assurance program in order to simplify the assessment procedures and to provide a maximum assurance to foodservice personnel and the public. A 16-Bit personnel computer compatible with IBM-PC/AT was used. The data base files and processing programs were created using dBASE III plus packages. The contents of the computerized system are summarized as knows: 1. When the input program for hazard analysis runs, a series of questions are asked to determine hazards and assess their severity and risks. Critical control points and monitoring methods for CCPs are identified and saved in Master file. 2. Output and search programs for hazard analysis are composed of 6 categories of recipe data file list, code identification list, and HACCP identification of the specific menu item. 3. When the user selects a specific category of recipe from 6 categories presented on the screen and runs data file list, a series of menu item list, CCP list, monitoring methods list are generated. When the code search program runs, menu names, ingredients, amounts and a series of codes are generated. 4. When the user types in a menu item and an identification code, critical control points and monitoring methods are generated for each menu item.

• 동력기계공학회지
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• 제2권2호
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 춘계학술대회 논문집
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• pp.97-101
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• 1993

In this work, the imaginary part of the inner modulation transfer function of the cutting dynamics is introduced for tool wear monitoring. Time-series method is utilized to construct the generalthree dimensional cutting dynamics whose imaginary part of the inner modulation transfer funcition shows the proportionality to tool wear at the natural frequency of the machine tool dynamics. This modelis reduced to single-input single- output model without altering the proporitonality characteristics to tool wear and implemented to the dual computer system in which one computer performs measurement while the other calculates the imaginary part of the inner modulation transfer function of th cutting dynamics by the batchleast square method. The values of the imaginary part at the natural frequencyof the machine tool structure in the cutting direction are compared to the one calculated during machining with a brand new tool to decide the current stants of the tool. The experiments shows the relevance of the proposed concept.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1855-1856
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• 2008

본 연구에서는 공정 중에 민감하게 반응하는 플라즈마로부터 수집되는 이온에너지 분포(IED : Ion Energy Distribution)와 시계열 신경망 모델링을 결합한 플라즈마 감시 기술을 개발하였다. NIEA(Non-invasive ion analyzer)를 이용하여 IED를 측정하였으며, 모델링에 사용된 신경망은 자기 상관 시계열 신경망(A-NTS : Auto-Correlated Neural Time-Series)이다. 모델 개발을 위한 학습과 테스트 데이터로는 Duty ratio 100%에서 수집한 IED를 이용하였으며, 개발된 모델의 감시 성능은 60%에서 수집된 IED로 평가하였다. 학습인자 k와 m의 범위는 각각 1-3 으로 총 9종류의 (k, m) 조합에 대해서 모델 성능을 평가하였다. 신경망 은닉층 뉴런수는 2-9의 범위에서 최적화하였다. 최적화된 모델은 (2, 3)과 뉴런수 2에서 구해졌으며, 0.335의 예측 에러를 보였다. 60% IED 데이터로 평가한 결과 플라즈마 고장에의 민감도는 62% 이상이었다. 이는 IED의 A-NTS 모델이 플라즈마 고장의 감시에 효과적으로 적용될 수 있음을 의미한다.

• 전기학회논문지P
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• 제59권4호
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• pp.372-376
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• 2010

Electrolytic capacitors have been widely used in power electronics system because of the features of large capacitance, small size, high-voltage, and low-cost. Electrolytic capacitors, which is most of the time affected by aging effect, plays a very important role for the power electronics system quality and reliability. Therefore it is important to estimate the parameter of an electrolytic capacitor to predict the failure. The estimation of the equivalent series resistance(ESR) is important parameter in life condition monitoring of electrolytic capacitor. This paper proposes a simple technique to measure the ESR of an electrolytic capacitor. This method uses a switching DC/DC boost converter to measure the DC Bus capacitor ESR of power converter. Main advantage of the proposed method is very simple in technique, consumes very little time and requires only simple instruments. Simulation results are shown to verify the performance of the proposed method.

• 한국전자통신학회논문지
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• 제13권2호
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• pp.369-376
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• 2018

본 논문은 안드로이드 기반으로 구현된 실시간 원격 모니터링 시스템을 제안한다. 원격 모니터링 기술은 모니터링에 필요한 비용의 절감과 비정상 상태의 빠른 발견에 이점이 있다. 제안된 모니터링 시스템은 민감한 정보를 보호하기 위해 RSA(Rivest Shamir Adleman) 알고리즘을 이용하는 보안 통신을 사용한다. 가스터빈의 이상 상황이 발생하였을 때, 원격 모니터링 시스템은 사용자의 주의를 끌기 위해 푸시 메시지를 이용한 경고를 한다. 제안된 시스템은 가상 데이터 발생기를 포함하는 실험 환경에서의 실험으로 검증되었다.

• Smart Structures and Systems
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• 제10권6호
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• pp.517-546
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• 2012

In this paper, vibration-based methods to monitor damage in foundation-structure interface of harbor caisson structure are presented. The following approaches are implemented to achieve the objective. Firstly, vibration-based damage monitoring methods utilizing a variety of vibration features are selected for harbor caisson structure. Autoregressive (AR) model for time-series analysis and power spectral density (PSD) for frequency-domain analysis are selected to detect the change in the caisson structure. Also, the changes in modal parameters such as natural frequency and mode shape are examined for damage monitoring in the structure. Secondly, the feasibility of damage monitoring methods is experimentally examined on an un-submerged lab-scaled mono-caisson. Finally, numerical analysis of un-submerged mono-caisson, submerged mono-caisson and un-submerged interlocked multiple-caissons are carried out to examine the effect of boundary-dependent parameters on the damage monitoring of harbor caisson structures.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.53-56
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• 2008

Generally, the quality of satellite images is expressed by GSD (Ground Sample Distance), MTF (Modulation Transfer Function) and SNR (Signal to Noise Ratio). However, these factors are technology-oriented and do not explain interpretability of satellite images. We need a standardized index which shows standard of interpretability. In this study, we estimated NIIRS (National Imagery Interpretability Rating Scale) through the GIQE (General Image Quality Equation) which is able to judge image interpretability with the standardized index. Traditionally, NIIRS has been determined manually by specialized image analysts. We used the GIQE in order to reduce inefficiency and high costs cause by manual interpretation and to produce accurate NIIRS. For monitoring image degradation, we estimated GIQE physical parameters from image analysis and carried out time series analysis about the quality of the KOMPSAT-1 images. On all of the tests, we were able to identify the image degradation due to the changing time. This indicates that NIIRS derived from GIQE will be used for image degradation indicator.