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At least 1,009 records · Page 56

Nonparametric identification of a class of nonlinear close-coupled dynamic systems

A nonparametric identification technique for the identification of close coupled dynamic systems with arbitrary memoryless nonlinearities is presented. The method utilizes noisy recorded data (acceleration, velocity and displacement) to identify the restoring forces in the system. The masses in the system are assumed to be known (or fairly well estimated from the design drawings). The restoring forces are expanded in a series of orthogonal polnomials and the coefficients of these polynomial expansions are obtained by using least square fit method. A particularly simple and computationally efficient method is proposed for dealing with separable restoring forces. The identified results are found to be relatively insensitive to measurement noise. An analysis of the effects of measurement noise on the quality of the estimates is given. The computations are shown to be relatively quick (when compared say to the Wiener identification method) and the core storage required relatively small, making the method suitable for onboard identification of large space structures.

Udwadia, F. E.↗

An approximation theory for the identification of nonlinear distributed parameter systems

An abstract approximation framework for the identification of nonlinear distributed parameter systems is developed. Inverse problems for nonlinear systems governed by strongly maximal monotone operators (satisfying a mild continuous dependence condition with respect to the unknown parameters to be identified) are treated. Convergence of Galerkin approximations and the corresponding solutions of finite dimensional approximating identification problems to a solution of the original finite dimensional identification problem is demonstrated using the theory of nonlinear evolution systems and a nonlinear analog of the Trotter-Kato approximation result for semigroups of bounded linear operators. The nonlinear theory developed here is shown to subsume an existing linear theory as a special case. It is also shown to be applicable to a broad class of nonlinear elliptic operators and the corresponding nonlinear parabolic partial differential equations to which they lead. An application of the theory to a quasilinear model for heat conduction or mass transfer is discussed.

Banks, H. T.↗

An approximation theory for the identification of nonlinear distributed parameter systems

An abstract approximation framework for the identification of nonlinear distributed parameter systems is developed. Inverse problems for nonlinear systems governed by strongly maximal monotone operators (satisfying a mild continuous dependence condition with respect to the unknown parameters to be identified) are treated. Convergence of Galerkin approximations and the corresponding solutions of finite dimensional approximating identification problems to a solution of the original finite dimensional identification problem is demonstrated using the theory of nonlinear evolution systems and a nonlinear analog of the Trotter-Kato appproximation result for semigroups of bounded linear operators. The nonlinear theory developed here is shown to subsume an existing linear theory as a special case. It is also shown to be applicable to a broad class of nonlinear elliptic operators and the corresponding nonlinear parabolic partial differential equations to which they lead. An application of the theory to a quasilinear model for heat conduction or mass transfer is discussed.

Banks, H. T.↗

A smart pattern recognition system for the automatic identification of aerospace acoustic sources

An intelligent air-noise recognition system is described that uses pattern recognition techniques to distinguish noise signatures of five different types of acoustic sources, including jet planes, propeller planes, a helicopter, train, and wind turbine. Information for classification is calculated using the power spectral density and autocorrelation taken from the output of a single microphone. Using this system, as many as 90 percent of test recordings were correctly identified, indicating that the linear discriminant functions developed can be used for aerospace source identification.

Cabell, R. H.↗

Space shuttle orbital maneuvering system failure detection and identification software requirements (uncontrolled)

Candidate designs and their software implementation are presented for the Orbital Maneuvering System (OMS) Failure Detection and Identification (FDI) algorithms in the Redundance Management (RM) module of the Space Shuttle Guidance, Navigation, and Control (GN&C) software. The OMS engine FDI algorithm monitors OMS engine thrust performance, and the OMS actuator FDI algorithm monitors OMS gimbal actuator performance. The software functional requirements of the algorithms are described along with the objective of each algorithm. A list of the assumptions which have governed its design, input/output requirements, a functional description of the algorithm (including a functional block diagram), and input interface requirements are given. The HAL (the language of the space shuttle flight computer) software formulation of the algorithms is considered including structured flowcharts of the procedures, estimates of flight computer core storage and CPU time, and processing requirements. A glossary of the symbols used to define the software requirements and formulations is included.

Damario, L. A.↗

Hypergames and Cyber-Physical Security for Control Systems

The identification of the Stuxnet worm in 2010 provided a highly publicized example of a cyber attack that physically damaged an industrial control system. This raised public awareness about the possibility of similar attacks against other industrial targets—including critical infrastructure. Here, we use hypergames to analyze how strategic perturbations of sensor readings and calibrated parameters can be used to manipulate a system that employs optimal control. Hypergames form an extension of game theory that enables us to model strategic interactions where the players may have significantly different perceptions of the game(s) they are playing. Past work with hypergames has focused on relatively simple interactions consisting of a small set of discrete choices for each player. Here, we apply single-stage hypergames to larger systems with continuous variables. We find that manipulating constraints can be a more effective attacker strategy than manipulating objective function parameters. Moreover, the attacker need not change the underlying system to carry out a successful attack—it may be sufficient to deceive the defender controlling the system. It is possible to scale our approach up to even larger systems, but this will depend on the characteristics of the system in question, and we identify several characteristics that will make those systems amenable to hypergame analysis.

97 MATHEMATICS AND COMPUTING↗

Automated identification of deformation twin systems in Mg WE43 from SEM DIC

In this study, the application of machine learning and computer vision approaches to microscale deformation data for the automated identification of deformation twinning systems, and their associated twin area, is introduced. Deformation data was obtained during in-situ SEM compression testing of a WE43 Mg alloy using digital image correlation (DIC) modified for use with electron microscopy. A 5.7 mm × 3.4 mm area of interest was analyzed, generating ~100 million data points of deformation. Experimental twin trace directions were determined by applying k-means clustering, morphological thinning, and Hough transforms to the deformation data. The identification of deformation twinning was achieved by consideration of the twin trace direction, its strain value, and its evolution. The deformation map was divided into areas corresponding to individual active twin systems, enabling the analysis of microstructure dependence of deformation behavior and twinning activity. The performance of the proposed twinning identification approach was evaluated by accuracy, precision, and sensitivity metrics. The effect of the tuning parameters used in the algorithm on the performance is also discussed.

36 MATERIALS SCIENCE↗

The star identification, pointing and tracking system of UVSTAR, an attached payload instrument system for the Shuttle Hitchhiker-M platform

We describe an algorithm for star identification and pointing/tracking of a spaceborne electro-optical system and simulation analyses to test the algorithm. The algorithm will be implemented in the guiding system of UVSTAR, a spectrographic telescope for observations of astronomical and planetary sources operating in the 500-1250 A waveband at approximately 1 A resolution. The experiment is an attached payload and will fly as a Hitchhiker-M payload on the Shuttle. UVSTAR includes capabilities for independent target acquisition and tracking. The spectrograph package has internal gimbals that allow angular movement of plus or minus 3 deg from the central position. Rotation about the azimuth axis (parallel to the Shuttle z axis) and elevation axis (parallel to the Shuttle x axis) will actively position the field of view to center the target of interest in the fields of the spectrographs. The algorithm is based on an on-board catalog of stars. To identify star fields, the algorithm compares the positions of stars recorded by the guiding imager to positions computed from the on-board catalog. When the field has been identified, its position within the guiding imager field of view can be used to compute the pointing corrections necessary to point to a target of interest. In tracking mode, the software uses the past history to predict the quasi-periodic attitude control motions of the shuttle and sends pointing commands to cancel the motion and stabilize UVSTAR on the target. The guiding imager (guider) will have an 80-mm focal length and f/1.4 optics giving a field of view of 6 deg x 4.5 deg using a 385 x 288 pixel intensified CCD. It will be capable of providing high accuracy (better than 2 arc-sec) attitude determination from coarse (6 deg x 4.5 deg) initial knowledge of the pointing direction; and of pointing toward the target. It will also be capable of tracking at the same high accuracy with a processing time of less than a few hundredths of a second.

Decarlo, Francesco↗

Composites for Advanced Drive Systems

With the desire for increased power/weight for advanced drive system configurations, the investigation of materials, like composites is being explored to determine the feasibility of integration into advanced drive systems. This area of research directly aligns with the vision of the NASA (National Aeronautics and Space Administration) Revolutionary Vertical Lift Technology (RVLT) Project, which is to enable a generation of vertical lift vehicles that can achieve aggressive goals in the areas of high speed, high efficiency, high performance, low noise, and low emissions.Composite materials are lightweight, especially when comparing to the metallic materials commonly utilized in rotorcraft drive systems. By integrating composite materials into the drive system, the potential for improvements to power/weight exists as well as other potential benefits such as reductions in vibration and/or noise. Each of these areas of potential benefit will largely influence the overall performance and reliability of future vertical lift vehicles. Prior NASA research has been performed that developed a prototype hybrid double helical bull gear which was successfully demonstrated (LaBerge, Kelsen E.; Handschuh, Robert F.; Roberts, Gary; Thorp, Scott;, 2016) and current NASA research is being performed to optimize the hybrid gear design.While the potential benefits of composite materials in vertical lift drive systems mentioned above are highly desirable, many challenges exist that need to be addressed. To address the benefits and challenges with the integration of composite materials in advanced vertical lift drive systems, the identification of advanced drive system configurations and technical challenges is required. For this project, Bell Helicopter Textron identified an advanced drive system configuration and provided conceptual designs for this advanced drive system configuration, identified technical challenges, and provided recommendations as to how those challenges can be overcome.

transmission↗

Trial-based calibration for audio-based identification, recognition, and detection system

The disclosed technologies include methods for generating a calibration model using data that is selected to match the conditions of a particular trial that involves an automated comparison of data samples, such as a comparison-based trial performed by an audio-based recognition, identification, or detection system. The disclosed technologies also include improved methods for selecting candidate data used to build the calibration model. The disclosed technologies further include methods for evaluating the performance of the calibration model and for rejecting a trial when not enough matched candidate data is available to build the calibration model. The disclosed technologies additionally include the use of regularization and automated data generation techniques to further improve the robustness of the calibration model.

McLaren, Mitchell Leigh↗

Remote sensing/vegetation classification

The CALVEG classification system for identification of vegetation is described. This hierarchical system responds to classification requirements and to interpretation of vegetation at various description levels, from site description to broad identification levels. The system's major strength is its flexibility in application of remote sensing technology to assess, describe and communicate data relative to vegetative resources on a state-wide basis. It is concluded that multilevel remote sensing is a cost effective tool for assessment of the natural resource base. The CLAVEG system is found to be an economically efficient tool for both existing and potential vegetation.

Parker, I. E.↗

Satellite provided customer promises services, a forecast of potential domestic demand through the year 2000. Volume 4: Sensitivity analysis

The overall purpose was to forecast the potential United States domestic telecommunications demand for satellite provided customer promises voice, data and video services through the year 2000, so that this information on service demand would be available to aid in NASA program planning. To accomplish this overall purpose the following objectives were achieved: (1) development of a forecast of the total domestic telecommunications demand; (2) identification of that portion of the telecommunications demand suitable for transmission by satellite systems; (3) identification of that portion of the satellite market addressable by consumer promises service (CPS) systems; (4) identification of that portion of the satellite market addressable by Ka-band CPS system; and (5) postulation of a Ka-band CPS network on a nationwide and local level. The approach employed included the use of a variety of forecasting models, a parametric cost model, a market distribution model and a network optimization model. Forecasts were developed for: 1980, 1990, and 2000; voice, data and video services; terrestrial and satellite delivery modes; and C, Ku and Ka-bands.

Kratochvil, D.↗

Identification of the C2 Phillips system in the solar spectrum

A probable identification of the (1,0) band of the C2 Phillips (1948) system in the solar photospheric spectrum is reported. The band oscillator strength derived from an analysis of the equivalent widths is compared with available laboratory and theoretical estimates. An independent search for the (2,0), (3,0), (4,1), and (5,2) bands recently reported by Sinha (1973) is also discussed.

Lambert, D. L.↗

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mathematical correlation of modal-parameter-identification methods via system-realization theory

A unified approach is introduced using system-realization theory to derive and correlate modal-parameter-identification methods for flexible structures. Several different time-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal-parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research toward the unification of the many possible approaches for modal-parameter identification.

Juang, Jer-Nan↗

Identification of linear stochastic systems through projection filters

A novel method is presented for identifying a state-space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relationship between the state-space model and the finite-difference model of linear stochastic systems derived through projection filters. It is proved that least-squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model.

Chen, Chung-Wen↗

Indirect Identification of Linear Stochastic Systems with Known Feedback Dynamics

An algorithm is presented for identifying a state-space model of linear stochastic systems operating under known feedback controller. In this algorithm, only the reference input and output of closed-loop data are required. No feedback signal needs to be recorded. The overall closed-loop system dynamics is first identified. Then a recursive formulation is derived to compute the open-loop plant dynamics from the identified closed-loop system dynamics and known feedback controller dynamics. The controller can be a dynamic or constant-gain full-state feedback controller. Numerical simulations and test data of a highly unstable large-gap magnetic suspension system are presented to demonstrate the feasibility of this indirect identification method.

Huang, Jen-Kuang↗