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At least 253 records · Page 14

Modal vector estimation for closely-spaced-frequency modes

Identification of modal parameters is made more difficult if the system has repeated frequencies or even closely spaced frequencies. This paper discusses the problems associated with closely-spaced-frequency modes and describes two related methods for dealing with these problems. It is demonstrated that proper identification of the system parameters of such systems requires information from multiple inputs and/or multiple outputs. The analytical basis for the 'minimum coincident response method' is outlined, and examples of the use of these two techniques to extract model parameters are presented.

Craig, R. R., Jr.↗

Aeroservoelastic Uncertainty Model Identification from Flight Data

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Brenner, Martin J.↗

Approximation techniques for domain identification in two-dimensional parabolic systems under boundary observations

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is considered. The domain identification treated is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Results of numerical experiments to demonstrate the efficiency of the theoretical ideas are reported.

Banks, H. T.↗

Spline-based distributed system identification with application to large space antennas

A parameter and state estimation technique for distributed models is demonstrated through the solution of a problem generic to large space antenna system identification. Assuming the position of the reflective surface of the maypole (hoop/column) antenna to be approximated by the static two-dimensional, stretched-membrane partial differential equation with variable-stiffness coefficient functions, a spline-based approximation procedure is described that estimates the shape and stiffness functions from data set observations. For given stiffness functions, the Galerkin projection with linear spline-based functions is applied to project the distributed problem onto a finite-dimensional subspace wherein algebraic equations exist for determining a static shape (state) prediction. The stiffness functions are then parameterized by cubic splines and the parameters estimated by an output error technique. Numerical results are presented for data descriptive of a 100-m-diameter maypole antenna.

Banks, H. T.↗

Using partially labeled data for normal mixture identification with application to class definition

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

Shahshahani, Behzad M.↗

Identification challenges for large space structures

The paper examines the on-orbit modal identification of large space structures, stressing the importance of planning and experience, in preparation for the Space Station Structural Characterization Experiment (SSSCE) for the Space Station Freedom. The necessary information to foresee and overcome practical difficulties is considered in connection with seven key factors, including test objectives, dynamic complexity of the structure, data quality, extent of exploratory studies, availability and understanding of software tools, experience with similar problems, and pretest analytical conditions. These factors affect identification success in ground tests. Comparisons with similar ground tests of assembled systems are discussed, showing that the constraints of space tests make these factors more significant. The absence of data and experiences relating to on-orbit modal identification testing is shown to make identification a uniquely mathematical problem, although all spacecraft are constructed and verified by proven engineering methods.

Pappa, Richard S.↗

Structural model optimization using statistical evaluation

The results of research in applying statistical methods to the problem of structural dynamic system identification are presented. The study is in three parts: a review of previous approaches by other researchers, a development of various linear estimators which might find application, and the design and development of a computer program which uses a Bayesian estimator. The method is tried on two models and is successful where the predicted stiffness matrix is a proper model, e.g., a bending beam is represented by a bending model. Difficulties are encountered when the model concept varies. There is also evidence that nonlinearity must be handled properly to speed the convergence.

Collins, J. D.↗

Study of low-cost fabrication of ablative heat shields

The major objectives were accomplished in three tasks: (1) modification of the ablative material composition for ease of fabrication as well as thermal and mechanical performance; (2) scaled-up, simplified, manufacturing techniques which resulted in cost reductions; and (3) the identification of a significant design problem caused by the differential pressure buildup imposed on mechanically attached ablative heat shield panels during launch.

Norwood, L. B.↗

Thermogravimetric-quadrupole mass-spectrometric analysis of geochemical samples.

Thermogravimetric-quadrupole mass-spectrometric-analysis techniques can be used to study a wide variety of problems involving decomposition processes and identification of released volatile components. A recording vacuum thermoanalyzer has been coupled with a quadrupole mass spectrometer. The rapid scan capabilities of the quadrupole mass spectrometer are used to identify the gaseous components released. The capability of the thermogravimetric-quadrupole mass spectrometer to provide analytical data for identification of the released volatile components, for determination of their sequence of release and for correlation of thermal-decomposition studies is illustrated by an analysis of the Orgueil carbonaceous chondrite.

Gibson, E. K., Jr.↗

Methods of Measurement for Semiconductor Materials, Process Control, and Devices

The development of methods of measurement for semiconductor materials, process control, and devices is reported. Significant accomplishments include: (1) Completion of an initial identification of the more important problems in process control for integrated circuit fabrication and assembly; (2) preparations for making silicon bulk resistivity wafer standards available to the industry; and (3) establishment of the relationship between carrier mobility and impurity density in silicon. Work is continuing on measurement of resistivity of semiconductor crystals; characterization of generation-recombination-trapping centers, including gold, in silicon; evaluation of wire bonds and die attachment; study of scanning electron microscopy for wafer inspection and test; measurement of thermal properties of semiconductor devices; determination of S-parameters and delay time in junction devices; and characterization of noise and conversion loss of microwave detector diodes.

Bullis, W. M.↗

Engineering studies related to geodetic and oceanographic remote sensing using short pulse techniques

For the Skylab S-193 radar altimeter, data processing flow charts and identification of calibration requirements and problem areas for defined S-193 altimeter experiments are presented. An analysis and simulation of the relationship between one particular S-193 measurement and the parameter of interest for determining the sea surface scattering cross-section are considered. For the GEOS-C radar altimeter, results are presented for system analyses pertaining to signal-to-noise ratio, pulse compression threshold behavior, altimeter measurement variance characteristics, desirability of onboard averaging, tracker bandwidth considerations, and statistical character of the altimeter data in relation to harmonic analysis properties of the geodetic signal.

Miller, L. S.↗

Machine processing of remotely sensed data; Proceedings of the Conference, Purdue University, West Lafayette, Ind., October 16-18, 1973

Topics discussed include the management and processing of earth resources information, special-purpose processors for the machine processing of remotely sensed data, digital image registration by a mathematical programming technique, the use of remote-sensor data in land classification (in particular, the use of ERTS-1 multispectral scanning data), the use of remote-sensor data in geometrical transformations and mapping, earth resource measurement with the aid of ERTS-1 multispectral scanning data, the use of remote-sensor data in the classification of turbidity levels in coastal zones and in the identification of ecological anomalies, the problem of feature selection and the classification of objects in multispectral images, the estimation of proportions of certain categories of objects, and a number of special systems and techniques. Individual items are announced in this issue.

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An asymptotic analysis of a general class of signal detection algorithms

For applications to the problem of radio frequency interference identification, or in the search for extraterrestrial intelligence, it is important to have a basic understanding of signal detection algorithms. A general technique for assessing the asymptotic sensitivity of a broad class of signal detection algorithms is given. In these algorithms, the decision is based on the value of X sub 1 + X sub 2...+ X sub n where the X sub 1's are obtained by sampling and preliminary processing of a physical process.

Mceliece, R. J.↗

Accuracy assessment: The statistical approach to performance evaluation in LACIE

A statistical methodology was developed to check the accuracy of the products of the experimental operations throughout crop growth and to determine whether the procedures are adequate to accomplish the desired accuracy and reliability goals. It has allowed the identification and isolation of key problems in wheat area yield estimation, some of which have been corrected and some of which remain to be resolved. The major unresolved problem in accuracy assessment is that of precisely estimating the bias of the LACIE production estimator. Topics covered include: (1) evaluation techniques; (2) variance and bias estimation for the wheat production estimate; (3) the 90/90 evaluation; (4) comparison of the LACIE estimate with reference standards; and (5) first and second order error source investigations.

Houston, A. G.↗

IUS solid rocket motor contamination prediction methods

A series of computer codes were developed to predict solid rocket motor produced contamination to spacecraft sensitive surfaces. Subscale and flight test data have confirmed some of the analytical results. Application of the analysis tools to a typical spacecraft has provided early identification of potential spacecraft contamination problems and provided insight into their solution; e.g., flight plan modifications, plume or outgassing shields and/or contamination covers.

Mullen, C. R.↗

Report of subpanel on feature extraction

The state of knowledge in feature extraction for Earth resource observation systems is reviewed and research tasks are proposed. Issues in the subpixel feature estimation problem are defined as: (1) the identification of image models which adequately describe the data and the sensor it is using; (2) the construction of local feature models based on those image models; and (3) the problem of trying to understand these effects of preprocessing on the entire process. The development of ground control point (GCP) libraries for automated selection presents two concerns. One is the organization of these GCP libraries for rectification problems, i.e., the problems of automatically selecting by computer the specific GCP's for particular registration tasks. Second is the importance of integrating ground control patterns in a data base management system, allowing interface to a large number of sensor image types with an automatic selection system. The development of data validation criteria for the comparison of different extraction techniques is also discussed.

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Analysis of the Earth's variable rotation

The objective was to analyze the Earth's rotation, and to compare the observations with the atmospheric and seismic excitation functions. The variation in the Earth's rotation can be separated into the length-of-day (LOD) variation and the polar motion. Possible driving mechanisms include: atmospheric/oceanic circulations, seismic activities, solar-lunar tides, mantle convection, core-mantle coupling, and solar activities. The major problem of concern was the identification of these dynamical processes as primary driving mechanisms for the various features in the variation of the Earth's rotation.

Chao, B. F.↗

Detection and evaluation of mixed pixels in Landsat agricultural scenes

A major problem area encountered in the identification and estimation of agricultural crop proportions in Landsat imagery involves the large proportion of the pixels which are mixed pixels, whose spectral response is influenced by more than one ground cover type. The development of methods for the detection and estimation of crop proportions in mixed pixels is presently reported. The procedure designated CASCADE, based on the estimation of the gradient image for the detection of mixed pixels, considers the consequences of a linear mixing model and is found to provide a method for the allocation of mixed pixels to the surrounding homogeneous region.

Merickel, M. B.↗