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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Practical aspects of on-orbit modal identification using free-decay data

Future large space structures such as Space Station Freedom can be tested as a total structure on Earth. Size, zero g design, and the existing atmosphere conflict with traditional structural dynamic testing. On-orbit modal identification will become necessary. Practical aspects of performing such tests using time domain analysis of free decay data are discussed. The effects of environmental constraints, structural characteristics, and excitation and sensing are reviewed. A recent laboratory application and sensing are reviewed. In this test, an on-orbit experiment is simulated using free decay data and a limited number of excitation and measurement points. The test article is dynamically similar to the truss/solar arrays of Space Station. The identified modal parameters from this simulation correlate well, though not uniquely, with those obtained in a complete modal survey. Practical difficulties in performing the correlation are illustrated. Model parameters are identified with the Eigensystem Realization Algorithm.

Schenk, Axel↗
NASA NTRS1985

A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm

The accuracy of the Ibrahim time Domain (ITD) identification algorithm in extracting structural model parameters from free response functions was studied using computer simulated data for 65 positions on an isotropic, uniform thickness plate with mode shapes obtained by NASTRAN analysis. Natural frequencies were used to study identification results over ranges of modal parameter values and user selectable algorithm constants. Effects of superimposing various levels of noise onto the functions were investigated. No detrimental effects were observed when the number of computational degrees of freedom allowed in the algorithm was made many times larger than the minimum necessary for adequate identification. The use of a high number of degrees of freedom when analyzing experimental data, for the simultaneous identification of many modes in one computer run are suggested.

Pappa, R. S.↗
NASA NTRS1982

Some statistical performance characteristics of the 'ITD' modal identification algorithm

Performance characteristics of the Ibrahim time-domain algorithms are examined on a statistical basis. The method uses multiple free-response measurements from a test structure directly in the time domain, and displays varying accuracy, with the strongly excited modes identified most accurately and the weakly excited modes least accurately. Sets of computer-generated free-response functions for a simple 1-mode model are used to study the identification performance for several basic changes in the modal characteristics of the data, the user-selectable analysis constants, and the level of superimposed noise. Results indicate the existence of a direct and often linear effect of noise on the scatter of identified parameters, and good identification is maintained at the 1% noise level down to the point in frequency when only 1/4-cycle of data is analyzed.

Pappa, R. S.↗
NASA NTRS1983

A study of the effects of a cubic nonlinearity on a modern modal identification technique

The effect of a geometric nonlinearity on the Ibrahim Time Domain (ITD) modal data analysis technique has been studied using two analytically derived models and one laboratory model. Response data for the three models were analyzed by the ITD method. Indicators of nonlinear response were found which include harmonically related frequencies with repetitive mode shapes, clusters of frequencies in a narrow band around each harmonic, and variations in frequency with amplitude of oscillation. Also,for the cases studied, the presence of a nonlinearity has no detrimental effect on identifying linear responses. A potential for applying the algorithm to the identification of a certain class of nonlinear system was indicated.

Horta, L. G.↗
NASA NTRS1977

Modal identification of structures from the responses and random decrement signatures

The theory and application of a method which utilizes the free response of a structure to determine its vibration parameters is described. The time-domain free response is digitized and used in a digital computer program to determine the number of modes excited, the natural frequencies, the damping factors, and the modal vectors. The technique is applied to a complex generalized payload model previously tested using sine sweep method and analyzed by NASTRAN. Ten modes of the payload model are identified. In case free decay response is not readily available, an algorithm is developed to obtain the free responses of a structure from its random responses, due to some unknown or known random input or inputs, using the random decrement technique without changing time correlation between signals. The algorithm is tested using random responses from a generalized payload model and from the space shuttle model.

Brahim, S. R.↗
NASA NTRS1988

Modal identification using single-mode projection filters and comparison with ERA and MLE results

The Single-Mode Projection Filter (SPF) is a newly developed algorithm for eigensystem parameter identification from both analytical results and test data. The SPF is formulated with a single mode only and practical for parallel processing implementation. Explicit formulations of SPF are derived for the multi-input multi-output (MIMO) system by using the orthogonal matrices of the controllability and observability matrices in the general sense. The modal parameters of SPF are initially obtained from an analytical model in modal space. The experimental data are then processed through SPF to update its modal parameters and to minimize a cost function defined by the norm of an error matrix. The updated modal parameters represent the characteristics of the test data. A two-dimensional global minimum optimization algorithm is developed and applied for the filter update by using the interval analysis method. The SPF is developed based on a single-mode subsystem and identifies only one modal frequency and one modal damping within a specified region. For an n-modes structure, n SPF can be implemented for parallel processing to reduce the computational burden. The SPF is applied to analyze the simulated data for the MAST beam structure. The estimated modal parameters are comparable to those from the Eigensystem Realization Algorithm (ERA) and repeated modal frequencies are identified. The modal analysis of the Spacecraft Control Laboratory Experiment (SCOLE) data is also performed by using the ERA and the Maximum Likelihood Estimate (MLE). The result shows that the first five modal frequencies are very close from ERA and MLE. However, there are slight disparities in the damping rates and the computational burdens are quite different among these two algorithms.

Huang, Jen-Kuang↗
NASA NTRS1991

Variance and bias computations for improved modal identification using ERA/DC

Variance and bias confidence criteria were recently developed for the eigensystem realization algorithm (ERA) identification technique. These criteria are extended for the modified version of ERA based on data correlation, ERA/DC, and also for the Q-Markov cover algorithm. The importance and usefulness of the variance and bias information are demonstrated in numerical studies. The criteria are shown to be very effective not only by indicating the accuracy of the identification results, especially in terms of confidence intervals, but also by helping the ERA user to obtain better results by seeing the effect of changing the sample time, adjusting the Hankel matrix dimension, choosing how many singular values to retain, deciding the model order, etc.

Longman, Richard W.↗
NASA NTRS1988

Parameter identification using modal data

Parameter identification using experimental modal data is examined. The following approaches are discussed: (1) Direct - using actual sensor measurements to obtain parameters (e.g., ERA, ITD); and (2) Indirect - identifies parameters using measured modal data. In this work, only the natural frequencies are used to identify physical parameters.

Meirovitch, L.↗
NASA NTRS1986

An Eigensystem Realization Algorithm in Frequency Domain for modal parameter identification

This paper demonstrates the close conceptual relationships between time domain and frequency domain approaches to identification of modal parameters for linear systems. A frequency domain eigensystem realization algorithm, via transfer functions, is developed using a known procedure formulated for a time domain eigensystem realization algorithm, via free decay measurement data. An important feature is the capability of windowing to concentrate analysis on the frequency range of interest. The procedure of overlap averaging is used to produce smoother spectra to reduce the effect of noise on identified modal parameters. Examples from simulation and experiments are given to illustrate the validity of formulations derived in the paper.

Juang, J.-N.↗
NASA NTRS1992

Comparison of candidate methods to distinguish noise modes from system modes in structural identification

In modal identification, nonphysical noise or computation modes always appear to help match the input-output data. This paper studies the ability of four criteria to distinguish which modes in a model are noise modes: (1) modal amplitude coherency, (2) the relative contribution of each mode to the pulse response indicated by the mode singular value, (3) the variances of the mode frequencies and damping factors produced by a chosen measurement noise level, and (4) identification of the backward-time in order to let the shift from positive to negative damping of the true system modes distinguish these modes from noise modes. Both simulated and experimental data are used to study the four criteria.

Longman, Richard W.↗
NASA NTRS1983

Time-Domain Modal Vibration Identification

Ibrahim Time-Domain modal vibration identification program (ITD) uses multiple free-decay responses of test structure directly in time domain to identify modal parameters of structure: natural frequencies, damping factors and damped mode shapes. ITD written in FORTRAN.

Ibrahim, S. R.↗
NASA NTRS1989

Identification of local modes using modal mass distributions

An approach for local modal identification using a modal mass spatial distribution matrix is proposed. This modal mass matrix is obtained by overlay multiplying the modal matrix to the product of the mass and the modal matrices of the structure. Each column in the spatial modal mass matrix can be interpreted as a measure of the kinetic energy distribution over the physical degrees of freedom for the corresponding mode. Local modes are identified due to the highly concentrated kinetic energy distribution in the localized regions. This spatial modal mass approach is more sensitive than the modal amplitude ratio method, since kinetic energy is in the quadratic form of modal amplitudes. Numerical examples involving identification of local modes using the proposed modal mass spatial distribution matrix approach are presented and discussed.

Chou, Chaur-Ming↗
NASA NTRS1987

An eigensystem realization algorithm using data correlations (ERA/DC) for modal parameter identification

A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.

Juang, Jer-Nan↗
NASA NTRS1986

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 and frequency-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 towards the unification of the many possible approaches for modal parameter identification.

Juang, J. N.↗
NASA NTRS1987

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↗
NASA NTRS1985

An eigensystem realization algorithm for modal parameter identification and model reduction

A method called the eigensystem realization algorithm is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular-value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system and noise modes. For illustration of the algorithm, an example is shown using experimental data from the Galileo spacecraft.

Juang, J.-N.↗
NASA NTRS1983

Direct structural parameter identification by modal test results

A direct identification procedure is proposed to obtain the mass and stiffness matrices based on the test measured eigenvalues and eigenvectors. The method is based on the theory of matrix perturbation in which the correct mass and stiffness matrices are expanded in terms of analytical values plus a modification matrix. The simplicity of the procedure enables real time operation during the structural testing.

Chen, J.-C.↗