• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.178-182
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• 2007

This paper reviews on the LRE health monitoring and emergency protection system to protect test object engine system and engine test facility, in case of various fault occurrence at LRE testing. General composition and major technical consideration of LRE health monitoring system and emergency protection system are reviewed. Moreover, some application of LRE health monitoring/emergency protection system to development test of major LRE component such as turbopump testing, gas generator and combustion chamber test are reviewed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• v.y2005m4
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• pp.248-251
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• 2005

In this paper, health monitoring technique has been studied for performance deterioration caused by the defects of the gas turbine. The parameters for performance diagnostics have been extracted by using GSP program for modeling the target engine. The virtual sensor model for the health monitoring has been built of those data. The position and magnitude of the defects of the engine components have been determined by using Multiple Linear Regression technique and the method using the weight in order to diagnose the single and multiple defects.

• Journal of Aerospace System Engineering
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• v.6 no.1
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• pp.13-18
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• 2012

This paper presents a structural health monitoring method of aircraft reciprocating engine using Principal Component Analysis (PCA) which analyzes vibration expressed by Averaged Normalized Power Spectral Density (ANPSD). Because ANPSD of the rotating shaft is sensitive to the rotating speed, this paper proposes to use a post-processing method of ANPSD is used to reduce the sensitivity. The PCA extracts compressed information from the post-processed ANPSDs and the information means the difference between current and normal cases of the engine. The experimental results demonstrate the feasibility and effectiveness of the proposed method to detect abnormal cases of the engine.

• 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 Aeronautical and Space Sciences
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• v.9 no.2
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• pp.64-70
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.1
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• pp.80-88
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• 2013

In currently developed engine condition monitoring systems, most field engine maintenance engineers have difficulties to use them in fields due to complexity, unpractical use, lack of understanding, etc. Therefore a practical usable engine condition monitoring system must be needed. This work proposes a practical performance condition monitoring of a small turbojet engine through comparing between the on-line performance monitoring data and the initial clean performance data calculated by the base engine performance model. Moreover the proposed monitoring system checks the gas path components' on-line health condition through comparing the component performance characteristics between the running engine represented as a deteriorated engine or a degraded engine and the base engine performance model represented as a clean engine. The proposed condition monitoring system is coded in a friendly GUI type program for easy practical application by a commercial tool, MATLAB/SIMULINK and LabVIEW.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.84-88
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.6
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• pp.7-11
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• 2008

The helicopter flies at low level flight mode in its own operational range comparing to other aircraft categories. The low level flight means that the engine operates at variable atmospheric condition such as hot and cold temperature, snow, heavy rain, etc. Furthermore it may increase the entering possibility of engine foreign object damage particles like sand, dust, etc., i.e. this operating condition gives rise to damages of engine gas path components. An on-line condition monitoring program was developed by using SIMULINK, where measurement signals were simulated as an input module. The reliability and capability of the developed on-line condition monitoring were confirmed through application to a real helicopter engine health monitoring.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.11a
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• pp.163-166
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• 2008

The helicopter flies at low level flight mode in its own operational range comparing to other aircraft categories. The low level flight means that the engine operates at variable atmospheric condition such as hot and cold temperature, snow, heavy rain, etc. Furthermore it may increase the entering possibility of engine foreign object damage particles like sand, dust, etc., i.e. this operating condition gives rise to damages of engine gas path components. An on-line condition monitoring program was developed by using SIMULINK, where measurement signals were simulated as an input module. The reliability and capability of the developed on-line condition monitoring were confirmed through application to a real helicopter engine health monitoring.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.39-45
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• 2006

Structural health monitoring has been conducted by non-destructive evaluation method when a turbine rotor system of an aircraft engine has cracks. Local stiffness of a turbine rotor system is degraded and critical speed is changed due to the presence of cracks in rotor. Critical speed which is affected by location and depth of crack, is obtained using compliance matrix of cracked rotor. The database of the obtained critical speed is used to evaluate structural health monitoring of a rotor system of a gas turbine engine.