• 제목/요약/키워드: Status Diagnosis Algorithm

검색결과 50건 처리시간 0.025초

확장 베이지안망을 적용한 고위험성 HRCT 영상 분류 (Classification of Very High Concerns HRCT Images using Extended Bayesian Networks)

  • 임채균;정용규
    • 전자공학회논문지CI
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    • 제49권2호
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    • pp.7-12
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    • 2012
  • 최근 의료분야에서는 방대한 양의 정보를 효과적으로 처리하기 위하여 의사결정트리, 신경망, 베이지안망 등을 비롯한 각종 데이터마이닝 기법의 적용 방안을 연구하고 있다. 또한 환자의 기본적인 신상정보나 과거력, 가족력과 같은 정보 이외에도 MRI, HRCT 등의 영상정보를 추가적으로 수집하고 진단에 활용함으로써 질병진단의 정확도 향상을 도모하는 것이 일반적인 현황이다. 하지만 실제 상황에서는 결과에 영향을 미치는 다량의 변수가 존재하므로 특정 데이터마이닝 기법을 통하여 얻을 수 있는 정보가 상당히 제한적이라고 볼 수 있다. 그뿐만 아니라 촬영된 의료영상도 부수적으로 진단에 긍정적인 영향을 줄 수는 있지만, 주관적인 판단 비중이 높아 자동화된 시스템으로 처리하기가 난해한 문제이다. 이에 따라 현실의 복잡한 상황에서 상대적으로 대처가 유리하고 다변량 확률적인 모델을 기반으로 하는 베이지안망에서 K2나 TAN 등으로 탐색 알고리즘을 개선한 확장 모델이 제안되었다. 이 때, 적용되는 탐색 알고리즘의 종류에 따라 그 성능이 크게 좌우되는 확장 베이지안망의 특성상, 각 기법에 대한 성능과 적합성의 사실적인 평가가 요구된다. 따라서 본 논문에서는 확장 베이지안망에서 질병 진단에 대한 동일한 데이터를 이용하여 실험을 수행하였으며, K2, TAN과 같은 탐색 알고리즘에 변화를 주며 분류 정확도를 측정하였다. 실험에서는 10-fold 교차검증을 수행한 결과분석을 기반으로 성능을 비교평가하고, 발병 위험성이 높은 환자에 대한 HRCT 영상을 분류하여 고위험성의 데이터를 식별 가능하도록 하였다.

Fault Detection of Governor Systems Using Discrete Wavelet Transform Analysis

  • Kim, Sung-Shin;Bae, Hyeon;Lee, Jae-Hyun
    • Journal of Advanced Marine Engineering and Technology
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    • 제36권5호
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    • pp.662-673
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    • 2012
  • This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

선박 추진용 2행정 저속엔진의 고장모드 데이터 개발 및 LSTM 알고리즘을 활용한 특성인자 신뢰성 검증연구 (The Study of Failure Mode Data Development and Feature Parameter's Reliability Verification Using LSTM Algorithm for 2-Stroke Low Speed Engine for Ship's Propulsion)

  • 박재철;권혁찬;김철환;장화섭
    • 대한조선학회논문집
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    • 제60권2호
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    • pp.95-109
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    • 2023
  • In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.

Proposal of a Hypothesis Test Prediction System for Educational Social Precepts using Deep Learning Models

  • Choi, Su-Youn;Park, Dea-Woo
    • 한국컴퓨터정보학회논문지
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    • 제25권9호
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    • pp.37-44
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    • 2020
  • AI 기술은 법률, 특허, 금융, 국방의 의사결정지원 기술 형태로 발전하여 질병 진단과 법률 판정 등에 적용되고 있다. Deep Learning으로 실시간 정보를 검색하려면, Big data Analysis과 Deep Learning Algorithm이 필요하다. 본 논문에서는 Deep Learning 모델인 RNN(Recurrent Neural Network)을 이용하여 상위권 대학 진학률을 예측하고자 한다. 우선, 행정구역 사설학원 현황과 행정구역 연령별 학생 수를 분석하고 교육열이 높은 지역에 거주하는 학생이 상위권 대학 진학률이 높다는 사회 통념의 가설을 설정했다. 예측된 가설과 정부의 공공데이터를 활용하여 분석된 자료를 토대로 검증하고자 한다. 예측모델은 2015년부터 2017년까지의 데이터를 활용하여 상위권 진학률을 예상하도록 학습하고, 학습된 모델은 2018년 상위권 진학률을 예측한다. 교육특구지역의 상위권 진학률을 Deep Learning 모델인 RNN을 이용하여 예측 실험을 수행했다. 본 논문은 교육열이 높은 지역의 사설학원 현황, 연령별 학생 수에 미치는 영향에 대해서 가구소득, 사교육의 참여 비율을 분석하여 상위권 진학률의 상관관계를 정의한다.

Classification of Porcine Wasting Diseases Using Sound Analysis

  • Gutierrez, W.M.;Kim, S.;Kim, D.H.;Yeon, S.C.;Chang, H.H.
    • Asian-Australasian Journal of Animal Sciences
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    • 제23권8호
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    • pp.1096-1104
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    • 2010
  • This bio-acoustic study was aimed at classifying the different porcine wasting diseases through sound analysis with emphasis given to differences in the acoustic footprints of coughs in porcine circo virus type 2 (PCV2), porcine reproductive and respiratory syndrome (PRRS) virus and Mycoplasma hyopneumoniae (MH) - infected pigs from a normal cough. A total of 36 pigs (Yorkshire${\times}$Landrace${\times}$Duroc) with average weight ranging between 25-30 kg were studied, and blood samples of the suspected infected pigs were collected and subjected to serological analysis to determine PCV2, PRRS and MH. Sounds emitted by coughing pigs were recorded individually for 30 minutes depending on cough attacks by a digital camcorder placed within a meter distance from the animal. Recorded signals were digitalized in a PC using the Cool Edit Program, classified through labeling method, and analyzed by one-way analysis of variance and discriminant analysis. Input features after classification showed that normal cough had the highest pitch level compared to other infectious diseases (p<0.002) but not statistically different from PRRS and MH. PCV2 differed statistically (p<0.002) from the normal cough and PRRS but not from MH. MH had the highest intensity and all coughs differed statistically from each other (p<0.0001). PCV2 was statistically different from others (p<0.0001) in formants 1, 2, 3 and 4. There was no statistical difference in duration between different porcine diseases and the normal cough (p>0.6863). Mechanisms of cough sound creation in the airway could be used to explain these observed acoustic differences and these findings indicated that the existence of acoustically different cough patterns depend on causes or the animals' respiratory system conditions. Conclusively, differences in the status of lungs results in different cough sounds. Finally, this study could be useful in supporting an early detection method based on the on-line cough counter algorithm for the initial diagnosis of sick animals in breeding farms.

한국형 재활환자분류체계 버전 1.0 개발 (The Development of Korean Rehabilitation Patient Group Version 1.0)

  • 황수진;김애련;문선혜;김지희;김진휘;하영혜;양옥영
    • 보건행정학회지
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    • 제26권4호
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    • pp.289-304
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    • 2016
  • Background: Rehabilitations in subacute phase are different from acute treatments regarding the characteristics and required resource consumption of the treatments. Lack of accuracy and validity of the Korean Diagnosis Related Group and Korean Out-Patient Group for the acute patients as the case-mix and payment tool for rehabilitation inpatients have been problematic issues. The objective of the study was to develop the Korean Rehabilitation Patient Group (KRPG) reflecting the characteristics of rehabilitation inpatients. Methods: As a retrospective medical record survey regarding rehabilitation inpatients, 4,207 episodes were collected through 42 hospitals. Considering the opinions of clinical experts and the decision-tree analysis, the variables for the KRPG system demonstrating the characteristics of rehabilitation inpatients were derived, and the splitting standards of the relevant variables were also set. Using the derived variables, we have drawn the rehabilitation inpatient classification model reflecting the clinical situation of Korea. The performance evaluation was conducted on the KRPG system. Results: The KRPG was targeted at the inpatients with brain or spinal cord injury. The etiologic disease, functional status (cognitive function, activity of daily living, muscle strength, spasticity, level and grade of spinal cord injury), and the patient's age were the variables in the rehabilitation patients. The algorithm of KRPG system after applying the derived variables and total 204 rehabilitation patient groups were developed. The KRPG explained 11.8% of variance in charge for rehabilitation inpatients. It also explained 13.8% of variance in length of stay for them. Conclusion: The KRPG version 1.0 reflecting the clinical characteristics of rehabilitation inpatients was classified as 204 groups.

무인전동차의 실시간 상태 진단을 위한 유지보수 정보시스템 인터페이스에 대한 개념설계 (A Conceptual Design of Maintenance Information System Interlace for Real-Time Diagnosis of Driverless EMU)

  • 한준희;김철수
    • 한국산학기술학회논문지
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    • 제18권10호
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    • pp.63-68
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    • 2017
  • 무인 운전 도시 철도시스템은 기관사 없이 열차를 운행 할 수 있는 장점을 갖지만, 이례상황 발생 시 유인운전의 기관사처럼 즉각적인 고장상태 파악, 관제보고, 수동조치가 어렵다. 따라서, 본선 운행 동안 차량 고장 / 상태 정보를 실시간으로 검지하여 차량기지 입고 시에 효율적으로 정비할 수 있는 유지보수 정보시스템의 구축이 필요하다. 본 논문에서는 무선통신망을 활용한 열차제어시스템, 관제 - 열차제어 정보시스템 콘솔 및 차량기지 유지보수 정보시스템간의 인터페이스를 실시간으로 구현하는 개념설계 방안을 제안하였다. 우선적으로 운행 중 발생되는 800,000 건/일의 많은 열차 상태 정보를 전송하기 위하여 본 연구에서 제안한 데이터 처리 알고리즘을 이용하여 56byte의 데이터 테이블로 수집한다. 이러한 상태 정보를 4자리의 헥사 코드화하여 분류하고, 본선 운행 동안 실시간으로 전동차 상태와 고장정보를 맵핑함으로서, 차량기지 내에 차량 유지보수 정보시스템에 전송한다. 또한 열차제어 정보시스템과 차량기지 유지보수 정보시스템 간에 실시간으로 송 / 수신 데이터의 전송을 각각 확인하고, 이로부터 현장에서 사용하도록 고장정보 화면구현을 구현하였다.

Research on rapid source term estimation in nuclear accident emergency decision for pressurized water reactor based on Bayesian network

  • Wu, Guohua;Tong, Jiejuan;Zhang, Liguo;Yuan, Diping;Xiao, Yiqing
    • Nuclear Engineering and Technology
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    • 제53권8호
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    • pp.2534-2546
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    • 2021
  • Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

유·가스정 최적 운영을 위한 ESP의 장기 성능 진단 및 고장 예측 실험 연구 (Experimental Study on the Diagnosis and Failure Prediction for Long-term Performance of ESP to Optimize Operation in Oil and Gas Wells)

  • 이승재;최준호;이정환
    • 한국가스학회지
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    • 제27권2호
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    • pp.71-78
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    • 2023
  • 일반적으로 평균 수명이 1.0~1.5년인 전기식 액중형 펌프(electrical submersible pump, ESP)는 유·가스 및 저류층 특성, 운영 조건에 따라 성능 저하 및 수명 감소가 발생하며, 이에 따른 ESP의 고장은 회수 및 설치에 따른 높은 유정 개·보수(workover) 비용과 생산 중단에 따른 추가 비용이 발생한다. 이에 본 연구에서는 유·가스정에서 ESP 장기 운영에 따른 수명을 예측하고자 환형 유동 시스템(flow loop system)을 설계 및 구축하고, ESP 설치 초기 시점부터 고장 시점까지의 ESP 수명에 대한 전 주기 데이터를 취득 및 분석하였다. 구축한 시스템에서 산출되는 데이터 중 ESP의 유체유량, 흡입구 및 토출구의 온도, 압력 그리고 외측부에 설치된 진동 측정기의 데이터 분석을 통하여 ESP 장기 운영에 따른 성능 상태를 정상(normal), 권고 I (advise I), 권고 II (advise II), 유지관리(maintenance), 고장(failed)의 총 5단계로 분류하였다. 실험 결과를 통해 ESP 장기 운영시 단계별 데이터의 경향 차이를 확인하였으며, 이를 통해 운영 기간에 따른 ESP의 상태를 진단하고 펌프의 고장을 예측하였다. 본 연구를 통해 도출된 결과는 유·가스정에서 운영되는 ESP의 상태 모니터링(monitoring) 을 위한 고장 예측 프로그램 및 데이터 분석 알고리즘 개발에 활용될 수 있을 것으로 판단된다.

설비공학 분야의 최근 연구 동향: 2014년 학회지 논문에 대한 종합적 고찰 (Recent Progress in Air-Conditioning and Refrigeration Research: A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2014)

  • 이대영;김사량;김현정;김동선;박준석;임병찬
    • 설비공학논문집
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    • 제27권7호
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    • pp.380-394
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    • 2015
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2014. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of heat and mass transfer, cooling and heating, and air-conditioning, the flow inside building rooms, and smoke control on fire. Research issues dealing with duct and pipe were reduced, but flows inside building rooms, and smoke controls were newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for thermal contact resistance measurement of metal interface, a fan coil with an oval-type heat exchanger, fouling characteristics of plate heat exchangers, effect of rib pitch in a two wall divergent channel, semi-empirical analysis in vertical mesoscale tubes, an integrated drying machine, microscale surface wrinkles, brazed plate heat exchangers, numerical analysis in printed circuit heat exchanger. In the area of pool boiling and condensing, non-uniform air flow, PCM applied thermal storage wall system, a new wavy cylindrical shape capsule, and HFC32/HFC152a mixtures on enhanced tubes, were actively studied. In the area of industrial heat exchangers, researches on solar water storage tank, effective design on the inserting part of refrigerator door gasket, impact of different boundary conditions in generating g-function, various construction of SCW type ground heat exchanger and a heat pump for closed cooling water heat recovery were performed. (3) In the field of refrigeration, various studies were carried out in the categories of refrigeration cycle, alternative refrigeration and modelling and controls including energy recoveries from industrial boilers and vehicles, improvement of dehumidification systems, novel defrost systems, fault diagnosis and optimum controls for heat pump systems. It is particularly notable that a substantial number of studies were dedicated for the development of air-conditioning and power recovery systems for electric vehicles in this year. (4) In building mechanical system research fields, seventeen studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, and renewable energies, piping in the buildings. Proposed designs, performance performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the evaluation of work noise in tunnel construction and the simulation and development of a light-shelf system. The subjects of building energy were worked on the energy saving of office building applied with window blind and phase change material(PCM), a method of existing building energy simulation using energy audit data, the estimation of thermal consumption unit of apartment building and its case studies, dynamic window performance, a writing method of energy consumption report and energy estimation of apartment building using district heating system. The remained studies were related to the improvement of architectural engineering education system for plant engineering industry, estimating cooling and heating degree days for variable base temperature, a prediction method of underground temperature, the comfort control algorithm of car air conditioner, the smoke control performance evaluation of high-rise building, evaluation of thermal energy systems of bio safety laboratory and a development of measuring device of solar heat gain coefficient of fenestration system.