Martin J. Brenner, Martin J. Brenner · 1997
Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique. NOMENCLATURE a wavelet scaling parameter
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David K. Taniguchi, R.L. Hagrman · IEEE Potentials · 1991
The calibration of measurements of the four critical parameters that define an aircraft's air data state, the state of an aircraft relative to the air mass through which it is flying, is discussed. The parameters are altitude, airspeed, angle-of-attack, and angle-of-sideslip. The measurements are taken by external probes, usually located on the aircraft's forebody, and are affected by the aircraft contours, which tend to disturb the local airflow across the probes. It is shown that using an expert system to calibrate the data improves the process.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Romualdo Ruotolo, W. Basso, Cecilia Surace · PORTO Publications Open Repository TOrino (Politecnico di Torino) · 1996
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Durston, Nicholas, Tran, Dac, Delille, Thomas et al. · elib (German Aerospace Center) · 2023
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G. Wulff · elib (German Aerospace Center) · 1993
A main task of the Mathematical Methods and Data Handling Branch of the DLR Institute of Flight Mechanics at Braunschweig is the development of software for data analysis. The Aircraft and Helicopter Flight Mechanics Branches are gathering increasing amounts of data of aircraft (for example: VFW-614 ''In-Flight Simulator ATTAS) and helicopters (for example: BO 105 ''In-Flight Simulator ATTHeS'') demanding adequate software to extract the relevant information from large data sets before the application of time consuming software, for example, for system identification. For this task the program system DIVA (Dialogprogramm zur Versuchsdaten-Analyse) has been developed. It consists of modules for data analysis in the time domain as well as in the frequency domain. A German and an English version of DIVA are running on the IBM main frame computers of DLR und the operating systems MVS and VM. The main features of DIVA are shown the report and the theoretical background of these methods of flight test data analysis are presented together with practical examples. The MIMO analysis procedures of DIVA are handled separately. (orig./AKF)
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Yu‐Wei Wu, Xiaoya Li, Huiyang Hu · 2023
With the increasing amount of flight test data, the traditional single-thread technology has been unable to meet the needs of rapid processing of massive flight test data. In order to improve the efficiency of flight test data processing, the characteristics of flight test data processing are analyzed, and a parallel flight test data processing method is proposed. This method realizes two-level parallel processing of multi-link parallel and data frame analysis parallel of flight test data. The method is verified by actual data, and the results show that the efficiency of this method is significantly improved compared with the traditional single-thread data processing method.
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Şimşek, Orkun · OpenMETU (Middle East Technical University) · 2019
In this study, a linear model of an unmanned aerial vehicle (UAV) is developed by using frequency domain system identification methods. The data used in the identification methods are obtained by performing flight tests. To obtain appropriate flight test data for identification process, flight test maneuvers are designed. These flight test data are used in two main frequency domain system identification methods, namely, transfer function modeling and state space modeling. The linear models obtained by using these two methods are verified in time domain using flight test data obtained by applying inputs called as verification inputs. A UAV is designed, produced and instrumented in Turkish Aerospace Industries, Inc. (TAI) as a test platform. In this thesis, this test platform is used to obtain flight test data. In identification process, two programs are mainly used, namely, Comprehensive Identification from Frequency Responses (CIFER) and MATLAB & Simulink.
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Kim D. Turver · UA Campus Repository (The University of Arizona) · 1993
International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, Nevada
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Baggerman, Bob · UA Campus Repository (The University of Arizona) · 2022
There is currently quite a bit of development taking place within the DoD flight test range community in “Big Data” computing. A problem plaguing development is a lack of suitable data sets for development and test of software analysis tools. Most actual flight test data has restricted distribution and so isn't available for many developers. Also, it can be difficult to find actual recorded flight test data which have “interesting” properties such as specific flight profiles and events. Synthesized IRIG 106 Chapter 10 format flight test data solves these problems by providing data files to developers that are very similar to what might be expected from an actual flight test. Synthetic data files are complete and properly formed data files that contain fake but realistic flight test data as if it had been recorded during an actual flight test. The data in these data files is designed to provide interesting test cases for software tool developers to use.
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G. E. Bennett · Defense Technical Information Center (DTIC) · 1974
After starting with an assessment of the general requirement for a flight test data acquisition system, following with a general discussion of the complete system, the report is subsequently concerned with some of the more important individual functions of the system--their nature and implementation. The functions selected are those most intimately involved in determining the performance of the system and its efficiency in acquiring the data. In the case of the recording aspects emphasis is placed on the basic recording process, its capabilities and its problems, and on the techniques necessary to overcome its shortcomings. Basic design principles of airborne tape transports and the characteristics of write/read heads and magnetic tape are also discussed. The report concludes with a discussion of the problems involved in specifying a requirement for a flight test data acquisition system and with comments on the likely nature of future systems.
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Adrian Hiliuta, Ruxandra Mihaela Botez · Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering · 2007
In the current paper, a new technique for a helicopter model estimation based on flight test data is presented. The state space helicopter models, for different flight conditions, are computed. The method is automatic and is applied when one knows the motion parameters types x, y, and u of a real helicopter and in the absence of any seed matrices. The method is highly convergent, and very good results are obtained for all flight cases. In the introductory part, a bibliographic research is carried on, and the necessary data collection is presented. In the next step, the preliminary estimation of seed matrices, for state-space representation is performed using a non-linear model and small perturbation theory. The last paragraph deals with the seed optimization with respect to different flight conditions. In the end, the model validation and the conclusion on possibilities to further develop and use the present methodology is investigated.
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E.J. Hammond · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 1965
FLIGHT-2 is a data reduction and analysis program for ;' SNAP lOA transient FLIGHT test data.The purpose of the FLIGHT-2 computer code is to:1. Permit rapid analysis and evaluation of the perforaance of the SNAP lOA system during its ;, orbital flight.: -• ^. .... , ., 2. Facilitate reporting of the experimental results to project management.
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Prof Dr, Bülent E. Platin, Prof Dr et al. · 2011
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Daniel O. Adams · Journal of the American Helicopter Society · 1988
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Chester Gong, Minghong G. Wu · 2015
The Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS) Project conducted flight test program, referred to as Flight Test 3, at Armstrong Flight Research Center from June - August 2015. Four flight test days were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as Autoresolver. The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Resulting flight test data and analysis results will be used to evaluate the DAA system performance (e.g., trajectory prediction accuracy, threat detection) and to add fidelity to simulation models used to inform Minimum Operating Performance Standards (MOPS) for integrating UAS into routine NAS operations.
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Heinrich Steinmann, Donald L. Marshall, Boeing Vertol Co. · 1974
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Barclay H. Boirun · Journal of the American Helicopter Society · 1979
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Kohlman, David L., 1937-, Langley Research Center., University of Kansas. Center for Research. · The Journal of the Abraham Lincoln Association
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Cynthia Faure, Jérôme Lacaille, Jean‐Marc Bardet et al. · PHM Society European Conference · 2016
An important amount of data is provided every day in Safran Aircraft Engines’ test benches. Produced by thousands of sensors, test and flight data represent a big interest for engineers but manual analysis of the information is too complex, if not impossible. As specific data are extracted from the database, it is not unusual to miss interesting information when focusing on a given problem. Defining the data as a succession of labels where each label appears as transient or stabilized phases would be one way to solve the problem. The start and stop points of the different phases will be computed by an offline change-point detection algorithm. In order to detect potential crucial changes of characteristic variables, it is relevant to develop powerful algorithms. The Pruned Exact Linear Time (PELT) method (Killick R. & Eckley, 2012) is a parametric change-point detection which searches the optimal partition of a monovariate signal (temporal series of onevariable) in our case (but can also be applied to a multivariate signal) with a linear complexity. This algorithm meets our expectations in many ways: robustness, fast computing and accurate results. Then on a multivariate aspect, patterns are built with parameters and initial conditions and, classified in a specific category with a map/reduce scheme. This clustering will allow different analysis: the comparison of different patterns with the definition of a distance and the research of a specific pattern in a large database. For example if an engine shows a specific engine temperature pattern after the test pilot changes the shaft rotation speed from one level to another, engineers may ask if this behavior is usual. If not, it should be very interesting to see if such pattern happens in the past on other engines or other tests and dig from the database the old documents related to those rare events and eventually the people concerned. The objective of this project is to progressively score and classify different patterns in an increasing database of labels. The first step was to implement the PELT algorithm. Then it is possible to identify the different transient phases extracted from small subsets of temporal measurements and compute models for each patterns. These codification of transient phase will lead to a classification into labels or topics. After defining enough patterns, each new record of measurements will be automatically classified.
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Engineering Sciences Data Unit, London (UK) · OpenGrey (Institut de l'Information Scientifique et Technique) · 1983
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