• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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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.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.341-350
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• 2005

In this study, fault diagnosis and monitoring of serial wound pre-engaged starter motors have been carried out. Starter motors are DC motors that enable internal combustion engine (ICE) to run. In case of breakdown of a starter motor, internal combustion engine can not be worked. Starter motors have vital importance on internal combustion engines. Kohonen network based fault diagnosis system is proposed for fault diagnosis and monitoring of starter motors. A graphical user interface (GUI) software has been developed by using Visual Basic 6.0 for fault diagnosis. Six faults, seen in starter motors, have been diagnosed successfully by using the developed fault diagnosis system. GUI software makes it possible to diagnose the faults in starter motors before they occur by keeping fault records of past occurrences.

• Journal of Power System Engineering
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• v.13 no.5
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• pp.82-88
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• 2009

The purpose of this paper is to provide technical background, techniques and actual diesel engine signature analysis evaluation result. Engine signature analysis(ESA) is a process for monitoring the material condition of diesel engine using external sensors, eliminating the need to periodically disassemble the engine. ESA is also used to balanced the engine. Engine balancing is the process of tuning the engine so that all cylinders carry equal load. ESA is a useful tool to non-intrusively determine the operability and performance and assessment of the material condition of internal component of a diesel engine.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.49-53
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• 2008

A fuzzy inference logic system is proposed for gas turbine engine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. The fuzzy inference logic uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. Inputs to the fuzzy inference logic system are measurement deviations of gas path parameters which are transferred directly from the ECM(Engine Control Monitoring) program and outputs are engine module faults. The proposed fuzzy inference logic system is tested using simulated data developed from the ECM trend plot reports and the results show that the proposed fuzzy inference logic system isolates module faults with high accuracy rate in the environment of high level of uncertainty.

• Tribology and Lubricants
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• v.13 no.2
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• pp.82-88
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• 1997

This paper describes an empirical equation which can be used to predict the engine condition of supersonic aircraft. The equation, which is derived from the trend analysis of JOAP data, represents the concentration of Fe particles in the engine oil. The result of the trend analysis shows that the concentration of Fe particles is a function of running time of engine oil. Meanwhile the slope of Fe concentration is a function of running time of engine. Threfore, the empirical equation was derived as $w=a(t_e).t_o+b$. However, the equation could not enough to diagnose the damaged part of engine quantitatively. To make up for the weak points of the equation, qualitative analysis was carried out. For that purpose wear debris were collected from the abnormal engine and analyzed by EDS to detect the damaged parts of engine.

• Tribology and Lubricants
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• v.24 no.3
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• pp.111-121
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• 2008

An integrated in-line oil monitoring detector assigned for continuous in situ monitoring multiple parameters of oil performance for predicting economically optimal oil change intervals and equipment condition control is presented in this study. The detector estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical intensity of oil in three optical wavebands ("Red", "Green" and "Blue") and water content is evaluated as Relative Saturation of oil by water. The detector is able to monitor oils with low light absorption (hydraulic, transformer, turbine, compressor and etc. oils) as well as oils with rather high light absorption in visible waveband (diesel and etc. oils). In a case study that the detector is applied to a diesel engine oil, it is found that the detector provides good results on oil chemical degradation as well as soot concentration.

• Journal of Power System Engineering
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• v.17 no.4
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• pp.31-35
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• 2013

The emergency AC power supply system of the nuclear power plant is designed to supply the power to the nuclear power plant at the emergency operating condition. The safety function of the diesel generator at the nuclear power plant is to supply AC electric power to the safety system whenever the preferred AC power supply is unavailable. The reliable operation of onsite standby diesel generator should be ensured by a condition monitoring system designed to maintain, monitor and forecast the reliability level of diesel generator. The purpose of this paper is to improve the existing ultrasonic sensor used for condition diagnosis of engine fuel pump and cylinder head for the accurate diagnosis in actual engine condition of emergency diesel generator(EDG). As a result of this study, we could design and develop much more reliable ultrasonic sensor than existing ones.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.112-122
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• 1996

In order to monitior machine tool condition and diagnose alarm states due to electrical and mechanical faults, and expert system using diagnostic parameters of NC machine tools was developed. A model-based knowledge base was constructed via searching and comparing procedures of diagnostic parameters and state parameters of the machine tool. Diagnostic monitoring results generate through a successive type inference engine were graphically displayed on the screen of the console. The validity and reliability of the expert system was rcrified on a vertical machining center equipped with FANUC OMC through a series of experiments.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.4
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• pp.60-68
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• 2003

In this study, a steady state performance analysis program was developed for a turbofan engine, and its performance was analyzed at installed conditions. For the purpose of evaluation, the developed program was compared with the performance data provided by the engine manufacturer. It was confirmed that the developed program was reliable because the results by the developed program were well agreed with those by the engine manufacturer within 3.5%. The non-linear GPA(Gas Path Analysis) program for performance diagnostics were developed, and selection of optimal measurement variables was studied. Furthermore, in order to investigate effects of the number and the kind of measurement variables, the non-linear GPA was analyzed with various measurement sets. Finally, the measurement parameters selected in the previous step were applied to the fault detection analysis of the 2-spool separate flow type turbofan engine.