• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.6
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• pp.624-629
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• 2014

The purpose of this study is to carry out the task of engine hesitation which occurred intermittently in driving due to the defective CKPS of LPI vehicles. As the result of the wrong data from the equipment of D-logger, the signal error of CKPS caused the engine hesitation. We performed a study in the followings to analyze and investigate the cause effectively. First, we have investigated the control wiring harness and connector pin contact defect inspection. Second, we have inspected the defection of CKPS separately. From this study, it was found that the engine hesitation were caused by the bad durability and we have showed how to diagnosis the fault of the engine hesitation intermittently while driving. Therefore, it is determined that we have to improve the durability of the CKPS through a strict quality control and to increase the reliability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.717-727
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• 2022

An algorithm is realized for estimating the component fault and health diagnosis such as a deterioration. Based on the turbofan engine health diagnosis model, from the health parameters which are estimated by a real time tracking filter, the outliers are eliminated efficiently by an effective median filter to minimize an false alarm. The difference between the fault and deterioration trends is identified by the detection measure for abrupt change, thereby the clear diagnosis classifying the fault and the health condition is possible. The effectiveness of the algorithm for fault and health diagnosis is verified from the simulated results of engine component faults and deterioration.

• 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.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.89-95
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• 2003

We consider a problem of application of analytical redundancy to engine synchronization process of spark ignition engines, which is critical to timing for every ECU process including ignition and injection. The engine synchronization process we consider here is performed using the pulse signal obtained by the revolution of crankshaft trigger wheel (CTW) coupled to crank shaft. We propose a discrete-time linear model for the signal, for which we construct FDI (Fault Detection & Isolation) system consisting residual generator and threshold based on linear observer.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.218-223
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• 2017

This paper deals with a fault diagnosis algorithm using the Kalman filter for a 75-ton Liquid Propellant Rocket Engine (LPRE). To design the Kalman filter, we linearized a non-linear simulation model of a 75-ton LPRE at an operating point, and checked the performance of the Kalman filter by comparing the measured values with estimated values of the states. Then, we artificially injected a fault of the turbopump efficiency into the simulation to confirm the performance of the fault diagnosis algorithm with the developed Kalman filter by comparing the variation of the residuals of the normal state with that of the fault cases.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.2
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• pp.88-97
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• 2021

The controller of the gas turbine engine is a component that needs to be developed for the development of the gas turbine engine because it is impossible to get the technology transferred from the engine manufacturer due to the import and export regulation. As a part of the engine control logic research, the Korea Aerospace Research Institute conducted a failure diagnostic research using a small gas turbine engine. Before simulating the engine fault, the ground test was performed to analyze normal behavior and performance of engine. Afterwards, the control logic analysis test equipment was established to simulate various engine fault. It is intended to provide background knowledge to engine control logic research for various engine failure conditions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.345-349
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• 2007

In this study a fuzzy trend monitoring method for detecting the engine 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. etc. Using engine condition data set as a input which generated by linear regression analysis of real engine instrument data, an application of fuzzy logic in diagnostics estimate a cause of fault in each components.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.321-325
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• 2005

These days, it is needed that more stability and reliability of Diesel engine. So it is essential that a systematic and comprehensive fault diagnosis analysis technology. this technology makes fault diagnosis analysis system more efficient. Expert System is required to make fault diagnosis analysis system. In this paper, fault and early diagnosis system is implemented to use Expert System development tools.