• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2818-2820
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• 2005

Recently, a request of protection environment for ocean has been increased. Owing to the reason above the development of highly efficient control technique for low pollution vessel diesel engine is concerned. In this paper, we study a method of remote diagnosis and monitoring for vessel diesel engine which is better safe and environmental friendly. Specially we propose the user interface building method of vessel diesel engine remote monitoring system using Internet.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 추계학술대회 논문집
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• pp.529-530
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• 2012

• Journal of Advanced Marine Engineering and Technology
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• 제37권2호
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• pp.183-191
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• 2013

SOLAS 선박표준 네트워크는 기계시스템 간 실시간 제어감시가 필요한 제어계측 네트워크와 운용자가 컴퓨터 모니터를 통하여 기계를 제어감시 하는 선박제어네트워크 및 외부와의 무선통신 네트워크로 구성되어 있다. 본 논문은 실시간 제어감시가 요구되는 제어계측네트워크로서 국제표준화 된 IEC 61162-3 (NMEA2000 네트워크)에 적합한 프로토콜 스택을 개발하고, 개발된 프로토콜 스택을 사용하여 기관실 모니터링시스템을 개발하였다. 개발된 기관실모니터링시스템을 NMEA에서 제공한 공식인증시험 툴을 사용하여 표준에서 요구하는 항목에 따라 약 1600여 가지의 인증시험과정을 통과하여 인증을 득하였으며 이에 관하여 기술한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.607-610
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• 2009

The abnormal combustion in the running engine results to knocking which increases the pressure and temperature in the cylinder, thereby decreasing the generated power by reducing the thermal efficiency. When the temperature and pressure in the cylinder increased rapidly by knocking, abnormal combustion takes place and the engine power is decreased. To investigate the knocking phenomenon, accelerometers are installed in the cylinder head to monitor and diagnose the vibration signal. As method of signal analysis, the time-frequency analysis method was adapted for acquisition of vibration signal and analyzes engine combustion in the short time. In this experiment, after analyzing time data which is stored in the signal recorder in one unit work (4 strokes: 2 revolutions), the signal with frequency and Wavelet methods with extracted one engine combustion data was also analyzed. Then, normal condition with no knocking signal is analyzed at this time. Hereafter, the experiments made a standard for distinguishing normal and abnormal condition to be carried out in acquisition of vibration signal at all cylinders and extracting knocking signal. In addition, analyzing methods can be diverse with Symmetry Dot Patterns (SDP), Time Synchronous Average (TSA), Wigner-Ville Distribution (WVD), Wigner-Ville Spectrum (WVS) and Mean Instantaneous Power (MIP) in the cold test [2]. With signal processing of vibration from engine knocking sensor, the authors adapted a part of engine /rotor vibration analysis and monitoring system for marine vessels to prevent several problems due to engine knocking

• 대한조선학회논문집
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• 제55권6호
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• pp.505-513
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• 2018

Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel's main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel's main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel's main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel's availability and provide a basis for a condition-based maintenance that can support proactive management of vessel's main engine in the future.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• International Journal of Aeronautical and Space Sciences
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• 제15권2호
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.

• Journal of Advanced Marine Engineering and Technology
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• 제38권6호
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• pp.744-750
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• 2014

선박용 디젤엔진의 상태 감시 및 이상 경보에 대한 신속하고 적절한 조치는 선박 운항에 있어서 안전성 및 경제성을 위해서 매우 중요하다. 만약 유지보수 업무를 담당하는 엔지니어의 고장원인에 대한 진단 오류 등으로 인하여 적절한 조치를 취하지 못하게 되면 이는 곧 대형 사고로 이어질 수 있다. 따라서 선박용 디젤엔진의 객관적인 진단에 도움을 주는 통합 감시 및 진단 시스템이 필요하다. 본 논문에서는 실시간으로 측정된 시계열 데이터를 분석한 후, 분석된 데이터의 상태 및 변화 추이를 감시하고 이를 기반으로 진단에 도움을 주기 위한 목적을 가진 시스템의 개발에 관한 내용을 다룬다. 이러한 감시 및 진단을 수행함으로써 이상이 발생하면 신속하게 경보를 제공하여 적절한 조치를 취할 수 있게 되어 선박용 디젤엔진의 안정성이 향상된다.

• 한국정보통신학회논문지
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• 제3권2호
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• pp.455-463
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• 1999

This study is on the development of an engine monitoring system which can be applied not only for mid-size vessels but also small vessels less than 20 gross tonnage. Monitoring system consists of a set LMU(Local Monitoring Unit) that collect data from local machinery, a host computer that controls LMU and a stable communication system which adopts CSMA/CD protocol. The LMU is composed of 80C196KC microprocessor, which consists of CPU, digital input/output, analog input/output and communication module. Communication system between the host computer(compatible IBM PC) and LMUs is the multidrop configuration using RS-485 method and confirmed high performance communication by the aid of polling method as well as carrier sense multiple access with collision detection(CSMA/CD) protocol.

• Journal of Advanced Marine Engineering and Technology
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• 제39권4호
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• pp.483-488
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• 2015

본 논문에서는 엔진유지관리 개선을 위해 Web 기반 선박엔진성능분석용 장기모니터링시스템을 구현하고자 한다. 이 시스템은 시뮬레이터, 다채널 A/D 변환기가 내장된 감시모듈, 모니터링 컴퓨터, 네트워크저장기(NAS), RS485 및 무선인터넷 통신시스템으로 구성된다. 기존 제품은 각 엔진마다 압력센서를 설치하고 이를 감시모듈에서 실시간으로 계측한 후 통신에 의해 현장 제어실 PC나 Web 상에서 모니터링이 가능하지만 많은 샘플링 압력데이터 용량으로 인해 통신전송속도가 느려지고, 장기모니터링에 오류가 발생할 수 있다. 이와 같은 문제점을 개선하기 위하여 본 논문에서는 각 실린더별 압력센서에서 받은 원본 압력데이터는 NAS에 저장하고, 원본 압력데이터를 구간별 다운샘플링을 하여 제어실에서 장기모니터링하고, Web에서의 장기모니터링을 위하여 다운샘플 데이터를 무선전송 한다. 제안한 방식에서는 전송량을 1/10로 하였으므로 작은 용량을 가진 메모리를 사용할 수 있고, 빠른 통신속도를 유지할 수 있어 통신비용이 절감되며, 화면전체에 약 30일간의 장기모니터링이 가능하여 엔진의 유지관리에 큰 기여를 할 수 있을 것으로 사료된다.