• Title/Summary/Keyword: Network-engine

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Oil Flow Distribution Control of Engine Lubrication System Using Orifice Component (오리피스를 이용한 엔진 윤활시스템 유량분배 제어)

  • Yun Jeong-Eui
    • Tribology and Lubricants
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    • v.22 no.1
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    • pp.47-52
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    • 2006
  • It is very important to control pressure and flow rate distribution on each component of engine lubrication network. Sometimes many kinds of orifice are used to control flow rate in the hydraulic lubrication field. In this study orifices were adopted on the lubrication network to control oil flow rate distribution. And unsteady transient flow network analysis was carried out to find out the effects of orifices on the engine oil circuit system.

A Study on Fault Detection of a Turboshaft Engine Using Neural Network Method

  • Kong, Chang-Duk;Ki, Ja-Young;Lee, Chang-Ho
    • International Journal of Aeronautical and Space Sciences
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    • v.9 no.1
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    • pp.100-110
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    • 2008
  • It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

Numerical Prediction of Flow and Heat Transfer on Lubricant Supplying and Scavenging Flow Path of An Aero-engine Lubrication System

  • Liu, Zhenxia;Huang, Shengqin
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.22-24
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    • 2008
  • This paper presents a numerical model of internal flows in a lubricant supplying and scavenging flow path of an aero-engine lubrication system. The numerical model was built in the General Analysis Software of Aero-engine Lubrication System, GASLS, developed by Northwestern Polytechnical University. The lubricant flow flux, pressure and temperature distribution at steady state were calculated. GASLS is a general purpose computer program employed a 1-D steady state network algorithm for analyzing flowrates, pressures and temperatures in a complex flow network. All kinds of aero-engine lubrication systems can be divided into finite correlative typical elements and nodes from which the calculation network be developed in GASLS. Special emphasis is on how to use combined elements which is a type of typical elements to replace some complex components like bearing bores, accessory gearboxes or heat exchangers. This method can reduce network complexity and improve calculation efficiency. Final computational results show good agreement with experimental data.

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Turbojet Engine Control Using Artificial Neural Network PID Controller With High Gain Observer (고이득 관측기가 적용된 터보제트엔진의 인공신경망 PID 제어기 설계)

  • Kim, Dae-Gi;Jie, Min-Seok
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.22 no.1
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    • pp.1-6
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    • 2014
  • In this paper, controller propose to prevent compressor surge and improve the transient response of the fuel flow control system of turbojet engine. Turbojet engine controller is designed by applying Artificial Neural Network PID control algorithm and make an inference by applying Levenberg-Marquartdt Error Back Propagation Algorithm. Artificial Neural Network inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbojet engine for UAV. High Gain Observer is used to estimate to compressor rotation speed of turbojet engine. Using MATLAB to perform computer simulations verified the performance of the proposed controller. Response characteristics pursuant to the gain were analyzed by simulation.

Marine Engine State Monitoring System using DPQ in CAN Network (CAN의 분산 선행대기 열 기법을 이용한 선박 엔진 모니터링 시스템)

  • Lee, Hyun;Lee, Jun-Seok;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.1
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    • pp.13-20
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    • 2012
  • This paper proposes a marine engine state monitoring system using a DPQ (Distributed Precedence Queue) mechanism which collects the state of bearings, temperature and pressure of engine through the CAN network. The CAN is developed by Bosch Corp. in the early 1980' for automobile network. The data from various sensors attached in the marine engine are converted to digital by the analog to digital converter and formatted to fit the CAN protocol at the CAN module. All the CAN modules are connected to the SPU (Signal Processing Unit) module for the efficient communication and processing. This design reduces the cost for wiring and improves the data transmission reliability by recognizing the sensor errors and data transmission errors. The DPQ mechanism is newly developed for the performance improvement of the marine engine system, which is demonstrated through the experiments.

An Embedded Network-Engine for Video On Demand Service (VOD(Video On Demand) 서비스를 위한 임베디드 네트워크 엔진)

  • Md, Amiruzzaman;Son, Sung-Ok;No, Jae-Chun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06a
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    • pp.145-148
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    • 2007
  • Although the embedded network-engine is a demand of time, it is observed that up to this time the network-engines are not sufficient to control the input and output device for Video On Demand (VOD). In this paper we have proposed the wireless network-engine with the capability of controlling the input and output device.

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Design and Implementation of the Game Engine for the Multiplayer Mobile Network Game (다중사용자 모바일 네트워크 게임을 위한 게임엔진의 설계 및 구현)

  • Jeong, Chul-Gon;Choi, Hwan-Eon;Jeong, Sun-Wung
    • Journal of Korea Game Society
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    • v.7 no.2
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    • pp.101-112
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    • 2007
  • Along with the development of mobile technology, mobile game has undergone a change from downloadable game to network game, where a large number of users connect to server and play real-time game with a mobile phone. In order to develop these mobile network games economically, a proper, suitable game engine is needed. This study proposes the result of design and implementation of RWMMO-GE(Realtime Wireless Massively Multiplayer Online RPG Game Engine) that is used to develop a mobile network game. The structure of RWMMO-GE, which is the research result of this study, consists of major components such as Network/Client Module, Object Module, Map Tool, Script Editor, and Character Editor. The characteristics of the multiplayer mobile game developed by this engine is that a large number of players can play real-time game in a single map, which implies a possibility of a new business model in this area. This research is a result of the RWMMO-GE supported by 2006 IT Excellent Technology Support Project(No:A1300-0601-0125) of IITA(Institute Information Technology Advancement).

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Application of Neural Network for Damage Diagnosis of Marine Engine Cylinder Liner (선박 엔진의 실린더 라이너의 손상 진단을 위한 신경회로망의 적용)

  • Cho, Yonsang;Koo, Hyunhoo;Park, Junhong;Park, Heungsik
    • Tribology and Lubricants
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    • v.30 no.6
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    • pp.356-363
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    • 2014
  • Marine diesel engines operate in environments in which damage easily occurs from corrosion. Recently, damage to cylinder liners has increased from corrosion wear caused by increased engine power. This damage can cause serious problems in the economy. Thus, many researchers have treated and studied damaged cylinder liners. However, a method is necessary for real-time monitoring of damage to cylinder liners during operation of the engine, before serious damage can occur. This study carries out reciprocating friction and wear tests on a cast iron specimen under various corrosion atmospheres and verifies the variations of friction coefficient and friction surface. Additionally, the friction coefficient and friction status are predicted by using a neural network that learns the vibration and frequency spectrum data from an acceleration sensor. According to our conclusions, amplitude is distributed highly at high frequencies, and values of standard deviation and kurtosis are high when damage to the friction surface is serious. The accuracy rate of the friction coefficient predicted by the neural network is over 80% of the real measured value without NaCl, and application of the neural network is very effective for diagnosing the friction condition and damage to the cylinder liner.

A Study on the Engine Lubrication System Analysis Adapting Discontinuous Oil Supply Crankshaft System (불연속 오일공급 크랭크샤프트 시스템을 채택한 엔진 윤활시스템의 해석)

  • 윤정의
    • Tribology and Lubricants
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    • v.20 no.1
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    • pp.27-32
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    • 2004
  • This paper presents unsteady oil flow behaviors in the engine lubrication network to clarify the differences between continuous and discontinuous oil supply crankshaft system. Using commercial network analysis program, Flowmaster2, engine lubrication network system analysis were carried out. And effects of crankshaft speed and supplied oil pressure on pressure fluctuation in oil groove and oil flow rate to each bearing were analyzed.

A Study on the System Identification based on Neural Network for Modeling of 5.1. Engines (S.I. 엔진 모델링을 위한 신경회로망 기반의 시스템 식별에 관한 연구)

  • 윤마루;박승범;선우명호;이승종
    • Transactions of the Korean Society of Automotive Engineers
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    • v.10 no.5
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    • pp.29-34
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    • 2002
  • This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.