• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.13 no.2
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• pp.27-34
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• 2005

This study is performed to analyze the turbulence distribution of Fev. & Mar. in 2000 by the analysis of the parameters related with flight data of FDR(Flight Data Recorder). In the analysis, we selected the Solid State Flight Data Recorder(SSFDR) & Universal Flight Data Recorder(UFDR) flight data of the exact same aircraft(capacity 120 persons). Through this study, we verified that turbulence is concerned with configuration of the ground and flight situation of aircraft.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.10 no.1
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• pp.45-56
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• 2002

This study is performed to analyze the turbulence effect by the analysis of the parameters related with flight data of FDR(Flight Data Recorder). In the analysis, the SSFDR(Solid State Flight Data Recorder) flight data of B747-400 and B767-300 model aircraft was selected. Through this study, we verified that turbulence interfere with flight safety because it is modifiable to flight situation and condition of aircraft.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.5
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• pp.57-64
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• 2005

Modern versions of supersonic jet fighter aircraft using digital flight-by-wire flight control system receive aircraft flight condition such as altitude, airspeed and AoA(angle of attack) from IMFP(Integrated Multi-Function Probe). IMFP sensors data have triplex structure using three IMFP sensors. An air data reconfiguration mode is applied to a T-50 flight control law to guarantee the aircraft flight stability when 2 or 3 IMFP sensors data are invalided. In this study, linear analysis and HQS(Handling Quality Simulator) pilot simulation are performed to analyze flight stability when the air data reconfiguration mode is applied to the control law. And we propose an example that the air data reconfiguration mode is applied to the control law due to second failure of IMFP during T-50 flight. It is found that the aircraft flight stability is not affected when the T-50 flight control law is changed to the air data reconfiguration mode.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.10 no.1
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• pp.21-34
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• 2002

This study is performed to secure the safety of civil aviation by establishing systematic analysis ability of Flight Data Recorder. Through this study, downloading SSFDR(Solid State Flight Data Recorder) to personal computer, editing interface file, flight data numerical analysis and regulations relayed to the aircraft with changes in destination airport in flight are performed. In the analysis, the flight data of B747-400 model aircraft between Los Angeles(KLAX) and Jeju(RKPC) was selected.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.10
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• pp.823-832
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• 2018

In general, the fidelity of the aircraft dynamic model is verified by comparison with the flight test results of the target aircraft. Therefore, the reference flight data for performance comparisons must be extracted. This process requires a lot of time and manpower to extract useful data from the vast quantity of flight test data containing various noise for comparing fidelity. In particular, processing of flight data is complex because rotorcraft have high non-linearity characteristics such as coupling and wake interference effect and perform various maneuvers such as hover and backward flight. This study defines flight data processing criteria for rotorcraft and provides procedures and methods for automated processing of static and dynamic flight data using data mining techniques. Finally, the methods presented are validated using flight data.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.391-395
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• 2023

Helicopter accidents due to spatial disorientation in low visibility conditions continue to persist as a major issue. These incidents often stem from human error, typically induced by stress, and frequently result in fatal outcomes. This study employs machine learning to analyze flight data and evaluate the efficacy of a flight illusion detection algorithm, laying groundwork for further research. This study collected flight data from approximately 20 pilots using a simulated flight training device to construct a range of flight scenarios. These scenarios included three stages of flight: ascending, level, and descent, and were further categorized into good visibility conditions and 0-mile visibility conditions. The aim was to investigate the occurrence of flight illusions under these conditions. From the extracted data, we obtained a total of 54,000 time-series data points, sampled five times per second. These were then analyzed using a machine learning approach.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.425-436
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• 2015

This paper presents the procedures used for estimating the stability and control derivatives of a general aviation canard aircraft from flight data. The maximum likelihood estimation method which accounts for both process and measurement noise was used for the flight data analysis of a four seat canard aircraft, the Firefly. Without relying on the parameter estimation method, several aerodynamic derivatives were obtained by analyzing the steady state flight data. A wind tunnel test, a flight test of a 1/4 scaled remotely controlled model aircraft, and the prediction of aerodynamic coefficients using the USAF Stability and Control Digital Data Compendium (DATCOM), Advanced Aircraft Analysis (AAA), and Computer Fluid Dynamics (CFD) were performed during the development phase of the Firefly and the results were compared with flight determined derivatives of a full scaled flight prototype. A correlation between the results from each method could be used for the design of the canard aircraft as well as for building the aerodynamic database.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.93-107
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• 2003

This study is performed to secure the safety of civil aviation by establishing systematic analysis ability of Flight Data Recorder. Through this study, readouting UFDR(Universal Flight Data Recorder) to personal computer, flight data numerical analysis and regulations of Missed Approach. In the analysis, the flight data of B747-400 model aircraft with Missed Approach in San Francisco(KSFO) was selected.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.149-157
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• 2011

In this paper, we propose a new DPCM-based transmission scheme for flight data. The amount of the flight data from LRU to MC has been increased due to the emergence and development of avionics systems and functions. It becomes a serious issue for satisfying the hard real-time processing required in the MC. In order to solve this problem, we observed the flight data produced by X-Plane simulator and discovered that the most flight data are moderately varied during flight. Based on this fact, a new data format is suggested by modifying that of ARINC-429 protocol in this paper. And the different value of the flight data is transmitted in the proposed scheme. The simulation results show that the proposed scheme achieves 20% data transfer gain compared to the ARINC-429 based transmission method.