• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2446-2452
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• 2012

In order to meet the recently enhanced emission standards at home and abroad, it is necessary to develop the CRDI ECU control algorithm that users can adjust fuel injection timing and amount in response to their needs. Therefore, this study developed the simulator for knocking analysis that enables knocking discrimination and engine balance correction applicable to the ECU exclusive to the industrial CRDI engine. The purpose of this study is to provide the driver-oriented diagnostic service that enable drivers to diagnose vehicles directly by developing diagnostic devices for vehicles with ths use of the results of the developed simulator for knocing analysis according to the OBD-II standards. For this purpose, this study aims to improve the fuel efficiency of vehicles by proposing the S/W design method of the OBD-II diagnosis device that can provide real-time communcations with the use of wired system and bluetooth module as a wireless system to send and recevice automobile fault diagnosis signal and sensor output signal, and to suggest an improvement for engine efficiency by minimizing the generation of harmful exhaust gas.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.339-347
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• 1996

object-oriented programming is used to develop next-generation telecommu- nications services running on the distributed processing environment. In order to test these services efficiently at the system-level during not only in the development phase but also in the operation phase, we define an embedded monitor service within the infrastructure to monitor the operation of the distributed programs, and describe a system-level test mechanism based on the monitor service. By separating the function of monitor server which monitors operations of objects and collects monitored data and that of tester which makes analysis and decides the sequence of test events, the invasive effect of monitoring can be minimized. At the same time, accurate diagnosis on the system can be achieve by exploiting the test mechanism. The mechanism, as a core component for the implementation of real-time fault-tol-erant systems, is applicable to general-purpose distributeded systems as well.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.41-49
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• 2008

Many machineries and equipments are being changing to various and complicated by development of recent technology and arrival of convergence age in distant future. These various and complicate equipments need more precise outcomes and low-power consumption sensors to get close and exact results. In this paper, we proposed fault tolerance and feedback theorem for sensor network and MEMS circuit which has a benefit of energy efficiency through wireless sensor network. The system is provided with independent sensor communication if possible as unused action, using idle condition of system and is proposed the least number of circuits. These technologies compared system efficiency after examining product of each Moving Distance by developed sensor which gives effects to execution of system witch is reduced things like control of management side and requirement for hardware, time, and interaction problems. This system is designed for practical application; however, it can be applied to a normal life and production environment such as "Ubiquitous City", "Factory Automata ion Process", and "Real-time Operating System", etc.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.10
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• pp.805-812
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• 2013

The operational flight program(OFP) which has the functions of I/O processing with avionics, flight control logic calculation, fault diagnosis and redundancy mode is embedded in the flight control computer of Smart UAV. The OFP was developed in the environment of PowerPC 755 processor and VxWorks 5.5 real-time operating system. The OFP consists of memory access module, device I/O signal processing module and flight control logic module, and each module was designed to hierarchical structure. Memory access and signal processing modules were verified from bench test, and flight control logic module was verified from hardware-in-the-loop simulation(HILS) test, ground integration test, tethered test and flight test. This paper describes development environment, software structure, verification and management method of the OFP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1949-1954
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• 2016

Smart grid technology can be called grid techniques to improve the efficiency of the electric power by exchanging bidirectional information of electric power with real-time between electric power suppliers and consumers. Recently, the solar power generation system is being applied actively. However the solar power system has several problems leading to reduce overall electricity generation, because the difficult of the diagnosis and the solar power system failure such as PV(PhotoVoltaics) and inverter. In order to build an efficient smart grid, a stable electric power energy requirements capture and management and early fault detection is essentially required in solar power generation system. In this paper, it is designed to monitor the operating status of the solar power monitoring system from a remote location through a RS-485 or TCP/IP communication module to monitoring the output of solar power energy and abnormal phenomenon, to developing the measurement module and to transfer measured data.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.102-108
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• 2024

With the recent increase in the development of domestic independent turbofan engines for aircraft, there is a need to develop software for FADEC(Full Authority Digital Engine Control) with real-time fault diagnosis functions to enhance fuel efficiency, engine performance, and reliability. As engine control algorithms become more sophisticated, software is being developed using Model-Based Design(model-based development) methods. This paper introduces the Middleware architecture of FADEC(Full Authority Digital Engine Control), which connects hardware with Model-Based Design(model-based development) software. Given the high reliability and safety required for turbofan engines in aircraft, the design complies with DO-178C[1] International Airborne Systems and Equipment Certification Guidelines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.613-622
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• 2015

The convergence of IT technology and marine facilities monitoring system is needed for effective monitoring systems to marine facilities. Especially the spread of smart device such as smart phone, smart pad, smart TV provide an environment that can check the status of the marine facility for marin facilities manager. However, smart phones and smart pads are used in a variety of OS used. Thus the monitoring system of the various service environments is difficult. In addition, There is inconvenience that must individually developed monitoring system for each device. In order to solve this problem NMMS (N-Screen Marine-facility Monitoring System) is proposed. NMMS is consist of Real-time monitoring system, Fault diagnosis system, Data storage system. To improve variety of smart devices accessibility, we use HTML 5. Through NMMS, marine facilities manager can use smart device such as PC, Notebook, smart phone, smart pad for marine facilities monitoring.

• Nuclear Engineering and Technology
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• v.53 no.8
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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.