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23rd International Conference on Artificial Neural Networks (ICANN)

作者： Suvorov, Mikhail Ivliev, Sergey Markarian, Garegin Kolev, Denis Zvikhachevskiy, Dmitry Angelov, Plamen Univ Lancaster Sch Comp & Commun Lancaster LA14WA England

ISBN: (纸本)9783642407277;9783642407284

In this paper a novel one-class classification approach (called OSA) is proposed. The algorithm is particularly suitable for fault detection in complex technological systems, such as aircraft. This study is based on the capability of one-class support vector machine (SVM) method to classify correctly the observation and measurement data, obtained during the exploitation of the system such as airborne aircraft into a single class of 'normal' behavior and, respectively, leave data that is not assigned to this class as suspected anomalies. In order to ensure real time (in flight) application a recursive learning procedure of the method is proposed. The proposed method takes into account both "positive"/"normal" and "negative"/"abnormal" examples of the base class, keeping the overall model structure as an outlier-detection approach. This approach is generic for any fault detection problem (for example in areas such as process control, computer networks, analysis of data from interrogations, etc.). The advantages of the new algorithm based on OSA are verified by comparison with several classifiers, including the traditional one-class SVM. The proposed approach is tested for fault detection problem using real flight data from a large number of aircraft of different make (USA, Western European as well as Russian).

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

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Store Trajectory Validation through Artificial Neural Networks for Safe-Separation flight Testing

Store Trajectory Validation through Artificial Neural Networ...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Fontanella, Rita Chimetto, Paolo Bindi, Francesco G. Bellati, Bruno Leonardo SpA Flight Test Engn & Conduct Ground & Flight Validat & Verificat Leonardo Aircraft Via Ingegnere Paolo Foresio 1 I-21040 Venegono Superiore VA Italy Leonardo SpA Ground & Flight Validat & Verificat Leonardo Aircraft Via Ingegnere Paolo Foresio 1 I-21040 Venegono Superiore VA Italy Leonardo SpA Flight Test Engn & Conduct Ground & Flight Validat & Verificat Leonardo AircraftAvion & Armament Discipline Str Malanghero I-10072 Caselle Torinese TO Italy Leonardo SpA Flight Test Engn & Conduct Ground & Flight Validat & Verificat Str Malanghero I-10072 Caselle Torinese TO Italy

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper presents an innovative machine-learning method to validate store separation trajectory and attitude computed by exploiting flight test data. It consists in generating high-accurate Artificial Neural Networks models of store separation motion for the different release conditions identified by some critical parameters: aircraft/store configuration, flight conditions, camera position and attitude and store features. Artificial Neural Networks models can then be adopted as benchmarks to quickly assess the quality of test data and, consequently, to detect latent failures of flight test instrumentation. The proposed method allows to exclude erroneous measurement, improving the timeliness and reducing the computational burden in store trajectory and attitude computation, and to reduce the number and frequency of repeated tests due to sensors failures, ensuring flight test program is conducted both safely and cost effectively.

关键词： flight Test Instrumentation Artificial Neural Network Sensors Machine Learning Conduction Mathematical Models flight data analysis Aircraft Fuselages Yaw Six Degree of Freedom

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NASA's Space Launch System: Artemis I Results and the Path Forward

NASA's Space Launch System: Artemis I Results and the Path F...

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AIAA SciTech Forum

作者： Honeycutt, John Blevins, John Cobb, Sharon Bryan, William NASAs Space Launch Syst Program Huntsville AL 35808 USA Aeyon Mfg Tech Solut Inc MTS NASAs Space Launch Syst Program Huntsville AL 35808 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

On Nov. 16, 2022, NASA launched the Artemis I mission on the agency's new SLS ( Space Launch System) rocket. The debut launch of the integrated vehicle sent an uncrewed Orion spacecraft into a distant retrograde (DRO) orbit about the Moon to accomplish multiple mission objectives, including evaluating Orion's heatshield at lunar return velocities and collecting critical data from the first flight of the new superheavy lift launch vehicle. Post-flight data analyses show that the rocket performed with a high degree of precision and accuracy. In addition to completing testing and launch of the Artemis I SLS in 2022, notable progress was made on hardware for future launch vehicles that will support Artemis missions II, III, IV, and V. The Artemis II core stage is mostly complete, and its RS-25 engines were integrated in the fall of 2023. The Artemis II solid rocket booster motor segments were shipped to the launch site in September 2023. Propellant tanks are being manufactured for additional missions, solid booster segments are being cast and prepared, software is being developed, and production of new RS-25 engines is underway. A more capable upper stage is in development, as well as a large adapter to encapsulate a 10-metric ton (t) co- manifested payload. This paper will provide details on the Artemis I flight as well as cover hardware progress for the future flights as available.

关键词： Booster Obsolescence and Life Extension Solid Rocket Boosters Rockets Super Heavy Lift Launch Vehicle NASA Moon Propellant Orion Spacecrafts flight data analysis Space Launch System Program

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Evidence based training

Evidence based training

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AIAA Modeling and Simulation Technologies Conference 2012

作者： Michael Varney

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Comparison of algorithms for anomaly detection in flight Recorder data of airline operations 12

Comparison of algorithms for anomaly detection in flight Rec...

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12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary analysis and Optimization Conference

作者： Das, Santanu Li, Lishuai Srivastava, Ashok N. John Hansman, R. UARC NASA Ames Research Center Moffett Field CA 94035 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology MIT 77 Massachusetts Avenue Cambridge MA 02139 United States NASA Ames Research Center Moffett Field CA 94035 United States

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Evaluation of flight Parameters During Approach and Landing Phases by Applying Principal Component analysis

Evaluation of Flight Parameters During Approach and Landing ...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Jasra, Sameer K. Valentino, Gianluca Muscat, Alan Zammit-Mangion, David Camilleri, Robert Univ Malta Inst Aerosp Technol MSD-2080 Msida Malta Univ Malta Dept Commun & Comp Engn MSD-2080 Msida Malta QuAero Ltd MST-3503 Mosta Malta

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

This paper adopts an unsupervised learning technique, Principal Component analysis (PCA) to analyze flight data. While the flight parameters for a stable approach have been established for a while, the paper reevaluates these flight parameters using PCA for a set of airports across the United States of America. Certain flight parameters were found to be more sensitive to some airports. The parameters have been cross-checked with experts in the industry to better interpret their significance.

关键词： flight data analysis Angle of Attack Pilot Ailerons Tail Number Autothrottle System Instrument flight Rules Airspeed Indicator Aircraft Configurations Airspeed

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The longitudinal handling characteristics of the Skysurfer X8

The longitudinal handling characteristics of the Skysurfer X...

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作者： Juffermans, Stefan Delft University of Technology

学位级别：硕士

For decades the physical appearance of aircraft remained more or less unchanged. The increase in efficiency which still can be made by improving this design, is limited. More researchers have started to investigate new design options that represent a departure from established concepts. The main drivers behind these endeavors are the tightening regulations on emissions and noise as well as the expected profitability for the customer. With the use of scale models for flight testing, it is possible to validate novel aircraft concepts while minimizing investments in terms of costs and time. Novel aircraft often have unproved handling characteristics which is why a quick method to verify these new models would be beneficial. The objective of this research is to investigate the longitudinal handling characteristics of the Skysurfer X8 by assessing whether the criteria for the short period damping, phugoid damping, bandwidth and Control Anticipation Parameter are in accordance with the military standards. Mathematical models for the aircraft's behavior are extracted from the aircraft by performing system identification in the frequency domain. This is done by measuring the aircraft's input and output signals while performing frequency sweeps on one of the control inputs during a flight test. These measurements are used to derive the input-output system. This procedure is followed for every longitudinal control variable of the aircraft. The models derived from the flight test are validated by comparing the handling characteristics (short period damping, phugoid damping and Control Anticipation) to a simulation performed in XFLR5. The frequency identification method described there is validated with frequency sweep data generated from an aircraft’s known state space system and the flight tests are performed with a modified Skysurfer X8 which is equipped with two wing mounted engines. Based on the validation the method proves to be reliable. The experiment shows that the han

关键词： flight testing flight characteristics Handling Qualities UAV Drone flight data analysis

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Klasifikace testovacích manévrů z letových dat

Klasifikace testovacích manévrů z letových dat

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作者： Funiak, Martin Brno University of Technology

Zapisovač letových údajů je zařízení určené pro zaznamenávání letových dat z různých senzorů v letadlech. Analýza letových údajů hraje důležitou roli ve... 详细信息

Zapisovač letových údajů je zařízení určené pro zaznamenávání letových dat z různých senzorů v letadlech. Analýza letových údajů hraje důležitou roli ve vývoji a testování avioniky. Testování a hodnocení charakteristik letadla se často provádí pomocí testovacích manévrů. Naměřená data z jednoho letu jsou uložena v jednom letovém záznamu, který může obsahovat několik testovacích manévrů. Cílem této práce je identi kovat základní testovací manévry s pomocí naměřených letových dat. Teoretická část popisuje letové manévry a formát měřených letových dat. Analytická část popisuje výzkum v oblasti klasi kace založené na statistice a teorii pravděpodobnosti potřebnou pro pochopení složitých Gaussovských směšovacích modelů. Práce uvádí implementaci, kde jsou Gaussovy směšovací modely použité pro klasifi kaci testovacích manévrů. Navržené řešení bylo testováno pro data získána z letového simulátoru a ze skutečného letadla. Ukázalo se, že Gaussovy směšovací modely poskytují vhodné řešení pro tento úkol. Další možný vývoj práce je popsán v závěrečné kapitole.

关键词： analýza letových dat klasifikace učení bez učitele identi kace letových manévrů EM algoritmus Gaussove směšovací modely flight data analysis classi cation unsupervised learning identi cation of flight maneuvers EM algorithm Gaussian Mixture Mod

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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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SOLUTION STRATEGY FOR 3-DIMENSIONAL CONFIGURATIONS AT HYPERSONIC SPEEDS

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JOURNAL OF SPACECRAFT AND ROCKETS 1993年第4期30卷 385-394页

作者： WEILMUENSTER, KJ GNOFFO, PA NASA Langley Research Center Hampton Virginia 23681

A procedure that reduces the memory requirements for computing the viscous flow over a modified Orbiter geometry at a hypersonic flight condition is presented. The Langley aerothermodynamic upwind relaxation algorithm (LAURA) code, that which incorporates a thermochemical nonequilibrium chemistry model, a finite rate catalytic wall boundary condition, and wall temperature distribution based on radiation equilibrium, is used in this study. In addition, the effect of choice of second-order flux formulations, eigenvalue limiter, and grid density on surface heating is investigated. The surface heating from a flowfield calculation at Mach number 22, altitude of 230,000 ft, and 40-deg angle of attack is compared with flight data from three Orbiter flights.

关键词： flight data analysis Freestream Conditions Angle of Attack Nonequilibrium Flows Temperature Distribution Aerothermodynamic analysis Hypersonic flight Computing Aspect Ratio Total Variation Diminishing

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