• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.2
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• pp.81-88
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• 2023

SHM (Structural Health Monitoring) technique for monitoring aircraft structural health and damage, EHM (Engine Health Monitoring) for monitoring aircraft engine performance, and APM (Application Performance Management) is used for each function. APMS (Airplane Performance Monitoring System) is a program that comprehensively applies these techniques to identify the difference between the performance manual provided by the manufacturer and the actual fuel mileage of the aircraft and reflect it in the flight plan. The main purpose of using APMS is to understand the performance of each aircraft, to plan and execute flights in an optimal way, and consequently to reduce fuel consumption. First, it is to check the fuel efficiency trend of each aircraft, check the correlation between the maintenance work performed and the fuel mileage, find the cause of the fuel mileage increase/decrease, and take appropriate measures in response. Second, it is to find the cause of fuel mileage degradation in detail by checking the trends by engine performance and fuselage drag effect. Third, the APMS is to be used in making maintenance work decisions. Through APMS, aircraft with below average fuel mileage are identified, the cause of fuel mileage degradation is identified, and appropriate corrective actions are determined. Fourth, APMS data is used to analyze the economic analysis of equipment installation investment. The cost can be easily calculated as the equipment installation cost, but the benefit is fuel efficiency improvement, and the only way to check this is the manufacturer's theory. Therefore, verifying the effect after installation and verifying the economic analysis is to secure the appropriateness of the investment. Through this, proper investment in fuel efficiency improvement equipment will be made, and fuel efficiency will be improved.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.5
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• pp.108-120
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• 2017

The technology for health management of gas turbine engine has grown with engine development itself for 60 years and regarded as important area for performance monitoring and maintenance of the system. This technology which is based on several areas such as advanced measurement technology, electronics, software technology and reliable system modeling is realized. This paper analyzed the past, current and future technical trend of a technically advanced country and compared with domestic research status. Based on the analysis, the key research topics for the realization of technology is suggested.

• Environmental Analysis Health and Toxicology
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• v.29
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• pp.9.1-9.3
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• 2014

Diesel exhaust particles (DEP) contain elemental carbon, organic compounds including Polyaromatic hydrocarbons (PAHs), metals, and other trace compounds. Diesel exhaust is complex mixture of thousands of chemicals. Over forty air contaminants are recognized as toxicants, such as carcinogens. Most diesel exhaust particles have aerodynamic diameters falling within a range of 0.1 to $0.25{\mu}m$. DEP was classified as a definite human carcinogen (group 1) by the International Agency for Research on Cancer at 2012 based on recently sufficient epidemiological evidence for lung cancer. Significant decreases in DEP and other diesel exhaust constituents will not be evident immediately, and outworn diesel car having longer mileage still threatens health of people in spite of recent remarkable development in diesel engine technology. Policy change in South Korea, such as introduction of diesel taxi, may raise health risk of air pollution in metropolitan area with these limitations of diesel engine. To protect people against DEP in South Korea, progressive strategies are needed, including disallowance of diesel taxi, more strict regulation of diesel engine emission, obligatory diesel particulate filter attachment in outworn diesel car, and close monitoring about health effects of DEP.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

• Journal of information and communication convergence engineering
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• v.15 no.2
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• pp.85-90
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• 2017

Expert systems for health diagnosis are only for medical experts who have deep knowledge in the field but we need a self-checking pre-diagnosis system for preventive public health monitoring. Korea Traditional Medicine is popular in use among Korean public but there exist few available health information systems on the internet. A computerized self-checking diagnosis system is proposed to reduce the social cost by monitoring health status with simple symptom checking procedures especially for Korea Traditional Medicine users. Based on the national reports for disease/symptoms of Korea Traditional Medicine, we build a reliable database and devise an intelligent inference engine using fuzzy c-means clustering. The implemented system gives five most probable diseases a user might have with respect to symptoms given by the user. Inference results are verified by Korea Traditional Medicine doctors as sufficiently accurate and easy to use.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.65-74
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• 2009

The risk of health impairment due to poor ventilation, fire and explosion by inflammable materials, and other unintended occurrences is always present in dangerous workplaces such as manholes, underground septic tanks, storage tanks and confined areas. Therefore, it a system which can monitor harmful working environment through sensors in workplace on a realtime basis and keep workers safe from the risk is needed. This paper has attempted to design an inference engine to monitor harmful environments in the workplace. The proposed inference engine has a rule-based system structure using JESS. This system is not confined to a particular computing platform and is easily interlocked with OSGi-based middleware.

• Smart Structures and Systems
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• v.5 no.2
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• pp.139-152
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• 2009

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1238-1244
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• 2009

This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module for reducing computer calculating time and a signal generation module for simulating real time performance data are used. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. The reliability and capability of the proposed on-line diagnostic program were confirmed through application to the helicopter engine health monitoring.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.535-550
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• 2016

Securing the safety and the reliability of liquid-propellant rocket engines (LREs) for space vehicles is indispensable as engines consist of many complex components and operate under extremely high energy-dense conditions. Thus, health monitoring has become a mandatory requirement, especially for the reusable LREs that are currently being developed. In this context, a dynamic simulation program based on MATLAB/Simulink was developed in the current research on the Space Shuttle Main Engine (SSME), a partly reusable engine. Then, a series of fault simulations using this program was conducted: at a steady state operating condition (104% Rated Propulsion Level), various simulated fault conditions were artificially injected into the simulation models for the five major valves, the pumps, and the turbines of the SSME. The consequent effects due to each fault were analyzed based on the time responses of the major parameters of the engine. It is believed that this research topic is an essential pre-step for the development of fault detection and diagnosis algorithms for reusable engines in the future.