• Title/Summary/Keyword: 엔진 진단

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A Data Fault Detection System for Diesel Engines Using Neural Networks (신경회로망을 이용한 디젤기관의 데이터 이상감지 시스템에 관한 연구)

  • 천행춘;유영호
    • Journal of Advanced Marine Engineering and Technology
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    • v.26 no.4
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    • pp.493-500
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    • 2002
  • The operational data of diesel generator engine is two kinds of data. One is interactive the other is non interactive. We can find the fault information from interactive data measured for every sampling time when the changing rate, direction and status of data are investigated in comparition with those of normal status to diagnose the fault of combustion system. The various data values of combustion system for diesel engine are not proportional to load condition. The criterion to decide the level of data value is not absolute but relative to relational data. This study proposes to compose malfunction diagnosis engine using neural networks to decide that level of data value is out of normal status with the data collected from generator engine of the ship using the commercial data mining tool. This paper investigates the real ship's operational data of diesel generator engine and confirms usefulness of fault detecting through simulations for fault detecting.

Fault Signal Analysis of the Automotive Components using Experimental Method, Part 2 - Consideration of the Component Signals (실험적 방법을 이용한 자동차 부품의 고장신호 분석, Part 2. 부품별 이상 신호 분석)

  • Lee, Hae-Jin;Park, Won-Sik;Lee, You-Yub;Oh, Jae-Eung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.05a
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    • pp.243-246
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    • 2007
  • 자동차의 고장은 그 종류나 특징 면에서 다양하게 나타나게 되므로 자동차의 진단과 점검에는 많은 노력과 비용, 시간이 소요되며 운전자에 의한 정보를 기대하기 힘든 경우에는 진단이나 정비과정에 많은 어려움을 겪게 된다. 따라서 본 연구에서는 운전자에 의한 일반적인 정보와 진동 소음 센서에 의한 정보의 신호처리기술을 종합하여 자동차 부품의 이상 신호 분석을 하였다. 그리고 정상 상태 대비 이상 신호에 따른 진동 소음 데이터 변화율을 계산하여 작동 모드 별 실내 음압에 영향을 미치는 신호 및 해당 주파수 특성을 분석하였다. 이에 따라 자동차 정비 전문가 시스템 구축을 위한 기초 연구로 엔진부의 이상 신호와 각 부품 별 이상 신호로 나누어 분석하여 데이터 처리 과정 및 이상 증상 별 경향 파악에 본 연구의 목적을 둔다.

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A study on the data fault detection system for diesel engine using neural network. (뉴럴네트웍을 이용한 디젤기관의 데이터 이상감지 시스템에 관한 연구)

  • 천행춘;김영일;김경엽;안순영;오현경;유영호
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2002.05a
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    • pp.245-250
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    • 2002
  • The operational data of diesel generator engine is two kind of discrete signal and analog signal. We can find the fault information from analog data measured for every sampling time if it is invested the changing rate or direction of data. This paper propose the Malfunction Diagnosis Engine(MDE) using the commercial data mining tool and show the data Process and fault finding method with the data collected from generator engine of the ship.

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Development of Oriental Medical Ontology using Bossam Inference Engine (Bossam 추론 엔진을 이용한 한의학 온톨로지 개발)

  • Moon, Kyung-Sil;Park, Su-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.43-46
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    • 2009
  • 의료 분야의 정보화 움직임으로 인해 단순한 정보 저장과 검색 시스템에서 벗어나 지능화된 서비스를 제공 해주는 시멘틱 웹 기반의 의료 시스템이 요구되고 있다. 이에 한의학 분야도 한의사의 진단을 보조할 수 있는 지식 기반 시스템에 대한 요구가 증대되고 있으며 관련 시스템들이 개발되어지고 있다. 온톨로지는 시멘틱 웹의 핵심적인 지식 체계로 지식의 처리와 추론이 가능하므로 질의 및 논리 추론을 통하여 진단을 내리는 한의학 지식 데이터베이스 구축에 적합하다. 본 연구에서는 한의학 분야의 지식을 보다 의미적이고 체계적으로 표현하고 온톨로지를 이용한 검색 결과의 이점을 보여주기 위해 추론 기술을 접목시켜 한의학 온톨로지를 개발하였다.

A Study on the Development of Anomaly Detection Prediction Model for Deep Learning-Based Drilling Equipment (딥러닝 기반 시추장비 이상 예측 및 진단 모델 개발 연구)

  • Han, Dong-Kwon;Kim, Min-Soo;Kwon, Sun-Il;Choi, Jung-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.404-407
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    • 2021
  • 석유개발 현장에서 시추장비의 고장으로 인한 장비교체 및 시추시간 증가는 막대한 비용소모를 발생시킨다. 본 논문은 딥러닝 기반의 시추장비 중 드릴비트의 동력을 구동시키는 디젤엔진의 고장 요소를 분류하고 이 요소에 따른 고장여부를 판별하는 딥러닝 기반의 이상 예측 및 진단 모델을 개발하였다. 또한 제안한 모델의 우수성을 확인하기 위해 로지스틱 회귀분석 분류모델과의 예측성능 비교분석도 수행하였다.

홀추력기 플라즈마 특성 연구를 위한 $E{\times}B$ 진단계 전산모사 및 개발

  • Kim, Ho-Rak;Seo, Mi-Hui;Seon, Jong-Ho;Lee, Hae-Jun;Choe, Won-Ho
    • Proceedings of the Korean Vacuum Society Conference
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    • 2013.02a
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    • pp.564-564
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    • 2013
  • 홀 추력기는 플라즈마를 이용하는 전기추력기 중 하나로, 인공위성의 자세제어, 궤도수정, 궤도천이 뿐만아니라 행성간 임무수행을 위한 우주선의 엔진으로 사용된다. 홀 추력기 채널 내부에 발생된 Xe 이온들은 양극과 음극 사이에 존재하는 전기장에 의해 가속되어 추력을 발생시킨다. 이때 Xe 이온들은 자기장에 의해 감금된 전자와 중성 Xe 원자 사이의 충돌에 의해 발생하며, 실험적 및 이론적 연구를 통해 단일 전하를 띤 이온(Xe II)뿐만 아니라 다중 전하(Xe III 등)를 띤 이온도 생성되는 것으로 알려져 있다. 이온의 전하량 비율은 홀 추력기의 추력효율 및 연료효율에 영향을 미치며, 다중 전하를 띤 이온의 높은 에너지는 채널벽의 침식문제를 야기하는 등 홀 추력기 이온빔의 전하량 분석 연구는 물리적 연구측면 뿐만아니라 실용적인 측면에서도 매우 중요하다. 본 연구에서는 자기장과 그에 수직한 방향의 전기장에서 발생하는 로렌츠 힘을 이용하여 이온의 전하량을 분석할 수 있는 $E{\times}B$ 탐침을 설계 및 개발하였다. 개발된 $E{\times}B$ 탐침은 70 mm 길이의 집속기와 $148{\times}138{\times}90mm$의 본체, 40 mm길이의 콜렉터로 구성된다. $E{\times}B$ 탐침 설계에 가장 중요한 균일한 자기장 설계를 위해 전산모사를 통해 최적화 작업을 진행하였으며, 실험을 위한 진단계의 최적화와 초기 실험결과가 발표될 예정이다.

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Development of the Vehicle Diagnosis Program Using OBD-II (OBD-II 시스템을 활용한 자동차 고장진단 프로그램 개발)

  • Yoo, Changhyun;Ko, Yongseo
    • Transactions of the Korean Society of Automotive Engineers
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    • v.23 no.3
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    • pp.271-278
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    • 2015
  • This paper develops an OBD Diagnostic Program (Program) using Visual Studio (C#), which was used to diagnosis malfunction information from OBD-II system vehicles. We accomplished this using the Program, Diagnostic tests, Board (STN1110), FTDI Basic Cable, Mini USB Cable, OBD Data Cable, and both hybrid and regular vehicles. The Program tests real-time data output, DTC output, sensor value output, engine RPM, waveform data, OBD type check, PID inspection, and whole monitoring. We found vehicles used in this research had 19 PIDs, which was within OBD-II regulations. We also gathered data on control and diagnostic code regulated by OBD-II system, such as, sensor output value, engine RPM, DTC output, each PID analytic value, OBD type, fuel mode, and whole monitoring result value. Using the data collected through the Program appropriately can lead to more effective diagnostic practices and contribute to education.

Implementation of pressure monitoring system(PMS) for ship's engine performance analysis(SEPA) based on the web (웹기반 선박엔진 성능분석용 압력모니터링 시스템 구현)

  • Yang, Hyun-Suk;Kwon, Hyuk-Joo;Lee, Sung-Geun
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.7
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    • pp.929-935
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    • 2014
  • This paper is study on the pressure monitoring system(PMS) for ship's engine performance analysis( SEPA) based on web, with high speed and accuracy. This system is composed of pressure sensor, monitoring module with multi channel A/D converter, TCP/IP and satellite internet communication system. Existing domestic products measure cylinder pressure when piston of first explosive cylinder reached TDC(the top dead center) point and then measure next cylinder pressure manually each angle divided by a constant rotating interval. But presented system monitors in the local and web computer, using pressure information transmitted from pressure sensor installed on each engine. In this system, it is possible to increase the accuracy of the engine performance analysis because not only each TDC points but cylinder pressures synchronized with the TDC points could be measured in real time, accurately. And therefore, it may be used in a various diagnosis of main engines, such as deviations of each cylinder maximum pressures(Pmax) and the TDC firing positions and combustion conditions.

A study on dermatologic diseases of workers exposed to cutting oil (절삭유 취급 근로자의 피부질환에 관한 연구)

  • Chun, Byung-Chul;Kim, Hee-Ok;Kim, Soon-Duck;Oh, Chil-Hwan;Yum, Yong-Tae
    • Journal of Preventive Medicine and Public Health
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    • v.29 no.4 s.55
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    • pp.785-799
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    • 1996
  • We investigated the 1,004 workers who worked in a automobile factory to study the epidemiologic characterists of dermatoses due to cutting oils. Among the workers, 667(66.4%) answered the questionaire. They are belong to 5 departments of the factory-the Engine-Work(258 workers), Gasoline engine Assembly(210), Diesel engine Assembly(96), Power train Work(86), Power train Assembly(17). We measured the oil mist concentration in air of the departments and examined the workers who had dermatologic symptoms. The results were follows; 1) Oil mist concentration ; Of all measured points(52),9 points(17.2%) exeeded $5mg/m^3$- the time-weighed PEL-and one department had a upper confidence limit(95%) higher than $5mg/m^3$. 2) Dermatologists examined 213 workers. 172 of them complained any skin symptoms at that time - itching(32.5%), papule(21.6%), scale(15.7%), vesicle(12.5%) in order. The abnormal skin site found by dermatologist were palm(29.3%), finger & nail(24.6%), forearm(16.2%), back of hand(8.4%) in order. 3) As the result of physical examination, we found that 160 workers had skin diseases. Contact dermatitis was the most common; 69 workers had contact dermatitis alone(43.1%), 11 had contact dermatitis with acne(6.9%), 10 had contact dermatitis with folliculitis(6.3%), 1 had contact dermatitis with acne & folliculitis, and 1 had contact dermatitis with abnormal pigmentation. Others were folliculitis(9 workers, 5.6%), acne(8, 5.0%), folliculitis & acne (2, 1.2%), keratosis(1, 0.6%), abnormal pigmentation (1, 0.6%), and non-specific hand eczema (47, 29.3%). 4) The prevalence of any skin diseases was 34.0 pet 100 in cutting oil users, and 13.3 per 100 in non- users. Especially, the prevalence of contact dermatitis was 23.0 per 100 in cutting oil users and 23.0 per 100 in non-users. 5) We tried patch test(standard serise, oil serise, organic solvents) on 49 patients to differentiate allergic contact dermatitis from irritant contact dermatitis and found 20 were positive. 6) In a multivariate analysis(independant=age, tenure, kinds of cutting oil), the risk of skin diseases was higher in the water-based cutting oil user and both oil user than non-user or neat oil user(odds ratio were 2.16 and 2.78, respectively). And the risk of contact dermatitis was much higher at the same groups(odds ratio were 5.16 and 6.82, respectively).

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Study on the method of safety diagnosis of electrical equipments using fuzzy algorithm (퍼지알고리즘을 이용한 전기전자기기의 안전진단방법에 대한 연구)

  • Lee, Jae-Cheol
    • Journal of Digital Convergence
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    • v.16 no.7
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    • pp.223-229
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    • 2018
  • Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.