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flight data analysis for the photovoltaic array space power plus diagnostics experiment

JOURNAL OF SPACECRAFT AND ROCKETS 1997年第1期34卷 92-103页

作者： Soldi, JD Hastings, DE Hardy, D Guidice, D Ray, K USAF PHILLIPS LABGEOPHYS DIRECTORATEHANSCOM AFBMA 01731

As power demands continue to increase, spacecraft power systems are being designed to operate at higher voltages. When operating at high negative voltages, however, arcing may occur on the solar cells, generating electromagnetic interference and solar cell damage. Numerical and analytic models have! been developed to simulate the arcing onset process, showing good agreement with experimental data. This simulation was used to predict arcing levels for the conventional geometry solar cells flown on the Photovoltaic Array Space Power (PASP) Plus experiment. Both preflight and postflight simulations showed good agreement with the flight data. The flight data were analyzed to examine correlations between are rates and the various material, environmental, and operational parameters and to validate the theoretical model. Arcing levels were found to depend strongly on bias voltage, with the scalings suggested by the model proving to relate the arcing rates on the different modules accurately. Cell temperature was also verified as being a critical parameter, with high arcing rates seen at low temperatures. As expected from the model, there is a critical temperature, above which no arcing occurs. The ion flux was also seen to affect are rates, as expected. Radiation flux to the arrays, however, did not affect arcing levels, although the data to support this conclusion are limited. Thus, the model was found to predict arcing levels for the cells under varying environmental and operational conditions and to allow data from one module to be accurately scaled to a module with different material and geometric parameters. This simulation could then be used to perform power system or solar cell design trade studies, with much less ground and flight testing needed for verification.

关键词： flight data analysis Solar Cells Critical Temperature Power System EMI Plasma Environment Satellites Eclipses Dielectric Constant Space Environment

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flight data analysis of the HyShot 2 scramjet flight experiment

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AIAA JOURNAL 2006年第10期44卷 2366-2375页

作者： Smart, Michael K. Hass, Neal E. Paull, Allan NASA Langley Res Ctr Hyperson Airbreathing Prop Branch Hampton VA 23681 USA Univ Queensland Div Mech Engn Brisbane Qld 4072 Australia

The development of scramjet propulsion for alternative launch and payload delivery capabilities has been composed largely of ground experiments for the last 40 years. With the goal of validating the use of short duration ground test facilities, a ballistic reentry vehicle experiment called HyShot was devised to achieve supersonic combustion in flight above Mach 7.5. It consisted of a double wedge intake and two back-to-back constant area combustors;one supplied with hydrogen fuel at an equivalence ratio of 0.34 and the other unfueled. Of the two flights conducted, HyShot 1 failed to reach the desired altitude due to booster failure, whereas HyShot 2 successfully accomplished both the desired trajectory and satisfactory scramjet operation. Postflight data analysis of HyShot 2 confirmed the presence of supersonic combustion during the approximately 3 s test window at altitudes between 35 and 29 km. Reasonable correlation between flight and some preflight shock tunnel tests was observed.

关键词： Scramjet flight data analysis Combustors Aerodynamic Testing Combustion Efficiency Hydrogen Fuels data analysis Reentry Vehicles Angle of Attack Yaw

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Momentum Management of Reaction Wheels for an Asymmetric Geostationary Satellite: with GK-2A flight data analysis

Momentum Management of Reaction Wheels for an Asymmetric Geo...

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AIAA SciTech Forum

作者： Yoon, Hyungjoo Kim, Hyeongcheol Yun, Jeongin Yoon, Hyosang Korea Aerosp Res Inst Satellite Technol Res & Dev Div 169-84 Gwahak Ro Daejeon 34133 South Korea Korea Adv Inst Sci & Technol Dept Aerosp Engn 291 Daehak Ro Daejeon 34141 South Korea

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Solar Radiation Pressure (SRP), the dominant torque disturbance for a GEO satellite with asymmetric solar panel arrays, is accumulated in a cluster of reaction wheels on the satellite. To prevent wheel speeds from reaching their limits, most GEO satellites use thrusters to dump angular momentum. Since the satellite missions should be halted during thruster-based off-loading, a key goal of momentum management strategy is to extend the time interval between momentum dumping processes. The momentum management strategy proposed in the present paper ensures that wheel speeds remain within their maximum and minimum (zero-speed) limits. A detailed analysis of the torque and momentum accumulation on GEO satellites is conducted. By giving an offset momentum to the reaction wheel opposite to the expected momentum accumulation, the required momentum capacity of the reaction wheel array is reduced. The momentum capacity of a cluster of reaction wheels is analyzed, and the wheel speed target for the dumping as well as wheel speed trajectories are determined. The target wheel speeds are optimally determined by minimizing the distance from the reference wheel speed in order to avoid the minimum and maximum speed limits as much as possible. The entire process is enhanced by a feedback controller and validated through both simulations and flight data. Annual changes in daily momentum accumulation were able to be expected with the proposed disturbance model, and the momentum management strategy worked effectively in real-world conditions, as evidenced by flight data.

关键词： Reaction Wheels flight data analysis Geostationary Satellites Solar Radiation Pressure Eclipses Earth Attitude Stability Earth Centered Inertial Static Friction Tachometer

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Incremental Anomaly Identification in flight data analysis by Adapted One-Class SVM Method

Incremental Anomaly Identification in Flight Data Analysis b...

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International Conference on Artificial Neural Networks (ICANN)

作者： Kolev, Denis Suvorov, Mikhail Morozov, Evgeniy Markarian, Garegin Angelov, Plamen Moscow MV Lomonosov State Univ Moscow Russia Univ Lancaster Lancaster LA1 4WA England

ISBN: (纸本)9783319099026

In our work we used the capability of one-class support vector machine (SVM) method to develop a novel one-class classification approach. Algorithm is designed and tested, aimed for fault detection in complex technological systems, such as aircraft. The main objective of this project was to create an algorithm responsible for collecting and analyzing the data since the launch of an aircraft engine. data can be transferred from a variety of sensors that are responsible for the speed, oil temperature and etc. In order to provide high generalization level and sufficient learning data sets an incremental algorithm is considered. The proposed method analyzes both "positive"/"normal" and "negative"/ "abnormal" examples. However, overall model structure is based on one-class classification paradigm. Modified SVM-base outlier detection method is verified in comparison with several classifiers, including the traditional one-class SVM. This algorithm has been tested on real flight data from the Western European and Russia. The test results are presented in the final part of the article.

关键词： flight data analysis Fault Detection and Identification one class SVM

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ARFA: Automated Real-time flight data analysis using Evolving Clustering, Classifiers and Recursive Density Estimation

ARFA: Automated Real-time Flight Data Analysis using Evolvin...

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IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Kolev, Denis Angelov, Plamen Markarian, Garegin Suvorov, Mikhail Lysanov, Sergey

ISBN: (纸本)9781467358552

In this paper a novel approach to autonomous real time flight data analysis (FDA) is proposed and investigated. The anomaly detection is based on recursive density estimation (RDE) and the fault identification is based on the evolving self-learning classifiers introduced recently. The paper starts with a brief critical analysis of the currently used FDA methods and tools. Then the problems of fault detection (FD) and identification are described formally. The importance of the ability to process the data in real time and on-line (in flight) is directly related to the efficiency and safety. Therefore, in this paper the focus is on the recursive approaches which are computationally lean and suitable for on-line mode of operation. The novel concept of ARFA (Automated Real-time FDA) is then applied to real flight data from Russian and USA made aircrafts. The results are compared and analyzed. Both, advantages that this novel methodology and algorithms offer as well as the current limitations and future directions of research are pointed out and future work outlined.

关键词： flight data analysis Fault Detection and Identification Recursive Density Estimation (RDE) Evolving Classifier eClass

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Applying the ADS-B out to Facilitate flight data analysis for General Aviation

Applying the ADS-B out to Facilitate Flight Data Analysis fo...

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作者： Huang Chenyu Purdue University

学位级别：Ph . D

The International Civil Aviation Organization (ICAO) and major airlines believe that flight data analysis is an effective approach to mitigate the risk of aviation accidents (International Civil Aviation Organization, 2010; International Air Transport Association, 2016). In the United States, flight data analysis is encouraged by the Federal Aviation Administration (FAA) through the flight operational quality assurance (FOQA) program. Among all aviation activities, general aviation (GA) has the highest accident rate (National Transportation Safety Board, 2014). However, implementation of flight data analysis for GA not only requires expensive investment on flight data recording devices, but also increases long-term labor cost due to regular data collection and data analysis. Automatic Dependent Surveillance Broadcast Out (ADS-B Out) is a precise satellite-based surveillance system that periodically broadcasts flight data retrieved from satellites and onboard avionics of the ADS-B Out capable aircraft. Based on the standard technical provisions of the ADS-B Out, the use of ADS-B data is expected to be a possible approach to facilitate the flight data analysis for general aviation. This research explored the use of ADS-B data to facilitate flight data analysis for general aviation. Researchers started the current study phase from analyzing the structure and content of the ADS-B message by referring to the ICAO technical provisions (2008) and the operational performance standard of ADS-B from the Radio Technical Commission for Aeronautics (RTCA) (2009). Based upon the findings of the ADS-B data structure and content, a set of retrievable aircraft parameters was identified, and additional aircraft parameters were derived from the basic ADS-B information. Furthermore, sets of flight metrics were developed using the aircraft parameters broadcasted by ADS-B Out. The development of flight metrics was expected to be essential for measuring flight operational performance to s

关键词： Applied sciences Communication and the arts Social sciences ADS-B flight data analysis General aviation

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APPLICATIONS OF STATE ESTIMATION IN AIRCRAFT flight-data analysis

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JOURNAL OF AIRCRAFT 1985年第7期22卷 547-554页

作者： BACH, RE WINGROVE, RC NASA Ames Research Center Moffett Field California

This paper traces the evolution of the use of state estimation in the analysis of aircraft flight data and discusses some recent applications associated with airline turbulence encounters and high angle-of-attack flight tests. A unifying mathematical framework for state estimation is reviewed, and several examples are shown that illustrate a general approach for estimating variables that are difficult to measure. The diversity of the applications discussed and examples presented serve to demonstrate the potential advantages of using state estimation methods. © 1985 American Institute of Aeronautics and Astronautics, Inc., All rights reserved.

关键词： flight data analysis Sikorsky Aircraft Aerodynamic Angle flight Testing Euler Angles True Airspeed Radar Tracking Angle of Sideslip Earth Accelerometer

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analysis of Mars 2020 Entry Vehicle Aerothermal flight data

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JOURNAL OF SPACECRAFT AND ROCKETS 2023年第4期60卷 1201-1219页

作者： Edquist, Karl T. West, Thomas K. Mahzari, Milad Alpert, Hannah S. NASA Langley Res Ctr Atmospher Flight & Entry Syst Branch Mail Stop 489 Hampton VA 23681 USA NASA Langley Res Ctr Vehicle Anal Branch Mail Stop 451 Hampton VA 23681 USA NASA Ames Res Ctr Entry Syst & Vehicle Dev Branch Moffett Field CA 94035 USA NASA Ames Res Ctr Moffett Field CA 94035 USA Analyt Mech Associates Inc Hampton VA USA

The Mars 2020 entry vehicle's thermal protection system included measurements of in-depth temperature on the heatshield and backshell, and surface heating on the backshell. This paper describes the flight data and resulting analysis: subsurface temperatures at 11 heatshield and 6 backshell locations, measured total heat flux at two backshell locations, and a radiometer on the backshell to measure shock layer radiation. All temperatures were within allowable material limits. Total surface heat flux was derived from the in-depth temperature measurements at the thermocouple locations. Turbulent boundary-layer conditions occurred at nine heatshield locations and the radiometer provided evidence that heating from shock layer radiation significantly exceeded convective heating on the backshell. Computational results on the reconstructed entry trajectory are compared to the flight data. After boundary-layer transition, total heat flux from algebraic turbulence model calculations qualitatively matches the reconstructed heating, but with lower peak magnitudes. On the backshell, laminar heat flux predictions generally exceed the as-flown values by less than 1 W/cm2, with shock layer radiation predicted to contribute the majority of heating. At the radiometer location, the maximum predicted radiative heat flux exceeds the measurement, with the measured value likely suppressed by ablation products on the sapphire window.

关键词： Mars Science Laboratory Thermal Control and Protection Heat Flux Radiative Heating Boundary Layer Transition Shock Layers Cebeci Smith Model Ablative Materials Aerothermodynamics flight data analysis

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Self-supervised contrast learning based UAV fault detection and interpretation with spatial-temporal information of multivariate flight data

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 267卷

作者： Wang, Shengdong Jia, Zhen Liu, Zhenbao Tang, Yong Qin, Xinshang Wang, Xiao Northwestern Polytech Univ Sch Civil Aeronaut Intelligent Unmanned Aerial Vehicle Lab Xian 710072 Peoples R China

Precise fault detection and interpretation can effectively enhance the safety of unmanned aerial vehicles (UAV) flight missions. However, sufficient fault data covering all fault modes is generally inaccessible, which poses a formidable challenge to the traditional supervised learning strategy. In this study, a novel UAV fault detection approach based on self-supervised contrast learning and spatial-temporal information of multivariate flight data is proposed. In the contrast learning task, a series of specific sample transformations are first designed, and the feature distribution of normal data can be modeled in self-supervised manner through comparing the similarity of different transformed samples. In above process, an auxiliary classification task that distinguishes different sample transformations is further introduced to facilitate the learning of critical features. In order to extract comprehensive spatial-temporal information from multivariate flight data, a multi-channel spatial-temporal encoder is designed in which two independent graph multi-head attention neural networks (GMAT) are implemented to mine the temporal features and multivariate spatial features, respectively. The extracted spatial-temporal features are then fused with the designed locally-enhanced token fusion module and the powerful multi-headed self-attention module. Finally, the occurrence of faults can be detected by comparing the reconstruction error with the fault threshold. With the box-plot analysis, the flight variables whose reconstruction errors are far from the overall distribution will be regarded as the possible fault sources to implement fault interpretation. Experimental results on the self-developed fixed-wing UAVs demonstrated the prominent performance of our method on fault detection and interpretation.

关键词： UAV Fault detection flight data analysis Condition monitoring Graph neural network

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AERODYNAMIC PARAMETERS ESTIMATED FROM flight AND WIND-TUNNEL data

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JOURNAL OF AIRCRAFT 1986年第4期23卷 306-312页

作者： KLEIN, V BATTERSON, JG Joint Institute for Advancement of Flight Services George Washington University NASA Langley Research Center Hampton Virginia NASA Langley Research Center Hampton Virginia

A procedure for determination of aerodynamic model structure and estimation of aerodynamic parameters is applied to data from a modern fighter operating within an angle of attack range of 5-60 deg. The paper briefly describes the airplane, available flight and wind tunnel data, postulated models for airplane aerodynamic coefficients, and flight data analysis. The results presented contain only a small number of selected longitudinal and lateral parameters. These parameters were obtained from various maneuvers and subsets of joined data from several flights. The estimated parameters are in good agreement with the wind tunnel measurements. The resulting aerodynamics model equations seem to be satisfactory for the prediction of airplane motion.

关键词： Wind Tunnel Tests Aeroplane Aerodynamic Coefficients flight data analysis Roll Control Angle of Attack Stabilator Mean Aerodynamic Chord Directional Stability Tailplane

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