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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

An enhanced mode shape identification algorithm

A mode shape identification algorithm is developed which is characterized by a low sensitivity to measurement noise and a high accuracy of mode identification. The algorithm proposed here is also capable of identifying the mode shapes of structures with significant damping. The combined results indicate that mode shape identification is much more dependent on measurement noise than identification of natural frequencies. Accurate detection of modal parameters and mode shapes is demonstrated for modes with damping ratios exceeding 15 percent.

Roemer, Michael J.↗
NASA NTRS1993

Nonlinear smoothing identification algorithm with application to data consistency checks

A parameter identification algorithm for nonlinear systems is presented. It is based on smoothing test data with successively improved sets of model parameters. The smoothing, which is iterative, provides all of the information needed to compute the gradients of the smoothing performance measure with respect to the parameters. The parameters are updated using a quasi-Newton procedure, until convergence is achieved. The advantage of this algorithm over standard maximum likelihood identification algorithms is the computational savings in calculating the gradient. This algorithm was used for flight-test data consistency checks based on a nonlinear model of aircraft kinematics. Measurement biases and scale factors were identified. The advantages of the presented algorithm and model are discussed.

Idan, M.↗
NASA NTRS1996

A Frequency-Domain Substructure System Identification Algorithm

A new frequency-domain system identification algorithm is presented for system identification of substructures, such as payloads to be flown aboard the Space Shuttle. In the vibration test, all interface degrees of freedom where the substructure is connected to the carrier structure are either subjected to active excitation or are supported by a test stand with the reaction forces measured. The measured frequency-response data is used to obtain a linear, viscous-damped model with all interface-degree of freedom entries included. This model can then be used to validate analytical substructure models. This procedure makes it possible to obtain not only the fixed-interface modal data associated with a Craig-Bampton substructure model, but also the data associated with constraint modes. With this proposed algorithm, multiple-boundary-condition tests are not required, and test-stand dynamics is accounted for without requiring a separate modal test or finite element modeling of the test stand. Numerical simulations are used in examining the algorithm's ability to estimate valid reduced-order structural models. The algorithm's performance when frequency-response data covering narrow and broad frequency bandwidths is used as input is explored. Its performance when noise is added to the frequency-response data and the use of different least squares solution techniques are also examined. The identified reduced-order models are also compared for accuracy with other test-analysis models and a formulation for a Craig-Bampton test-analysis model is also presented.

Blades, Eric L.↗
NASA NTRS1998

Comparison of Five System Identification Algorithms for Rotorcraft Higher Harmonic Control

This report presents an analysis and performance comparison of five system identification algorithms. The methods are presented in the context of identifying a frequency-domain transfer matrix for the higher harmonic control (HHC) of helicopter vibration. The five system identification algorithms include three previously proposed methods: (1) the weighted-least- squares-error approach (in moving-block format), (2) the Kalman filter method, and (3) the least-mean-squares (LMS) filter method. In addition there are two new ones: (4) a generalized Kalman filter method and (5) a generalized LMS filter method. The generalized Kalman filter method and the generalized LMS filter method were derived as extensions of the classic methods to permit identification by using more than one measurement per identification cycle. Simulation results are presented for conditions ranging from the ideal case of a stationary transfer matrix and no measurement noise to the more complex cases involving both measurement noise and transfer-matrix variation. Both open-loop identification and closed- loop identification were simulated. Closed-loop mode identification was more challenging than open-loop identification because of the decreasing signal-to-noise ratio as the vibration became reduced. The closed-loop simulation considered both local-model identification, with measured vibration feedback and global-model identification with feedback of the identified uncontrolled vibration. The algorithms were evaluated in terms of their accuracy, stability, convergence properties, computation speeds, and relative ease of implementation.

Jacklin, Stephen A.↗
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 NTRS1993

Star-field identification algorithm

A description of a new star-field identification algorithm that is suitable for implementation on CCD-based imaging cameras is presented. The minimum identifiable star pattern element consists of an oriented star triplet defined by three stars, their celestial coordinates, and their visual magnitudes. The algorithm incorporates tolerance to faulty input data, errors in the reference catalog, and instrument-induced systematic errors.

Scholl, M. S.↗
NASA NTRS2010

Crater Identification Algorithm for the Lost in Low Lunar Orbit Scenario

Recent emphasis by NASA on returning astronauts to the Moon has placed attention on the subject of lunar surface feature tracking. Although many algorithms have been proposed for lunar surface feature tracking navigation, much less attention has been paid to the issue of navigational state initialization from lunar craters in a lost in low lunar orbit (LLO) scenario. That is, a scenario in which lunar surface feature tracking must begin, but current navigation state knowledge is either unavailable or too poor to initiate a tracking algorithm. The situation is analogous to the lost in space scenario for star trackers. A new crater identification algorithm is developed herein that allows for navigation state initialization from as few as one image of the lunar surface with no a priori state knowledge. The algorithm takes as inputs the locations and diameters of craters that have been detected in an image, and uses the information to match the craters to entries in the USGS lunar crater catalog via non-dimensional crater triangle parameters. Due to the large number of uncataloged craters that exist on the lunar surface, a probability-based check was developed to reject false identifications. The algorithm was tested on craters detected in four revolutions of Apollo 16 LLO images, and shown to perform well.

Hanak, Chad↗
NASA NTRS1977

Comparison of continuous and discrete adaptive identification algorithms

Discretization of a popular continuous-time control algorithm is effected and an equivalent discrete-time identification law developed and compared to a published discrete identification algorithm developed from Lyapunov Theory. Results are compared as regards asymptotic stability as insured using Lyapunov theory. Some analysis and design guidelines are proposed as regards implementation and practical utility.

Colburn, B. K.↗
NASA NTRS1993

Experimental demonstration of a star-field identification algorithm

A fault-tolerant, six-feature, all-sky star-field identification algorithm has been integrated with a CCD-based imaging camera. This autonomous intelligent camera identifies in real time any star field without a priori knowledge and requires a reference catalog incorporating fewer than 1000 stars. Observatory tests on star fields with this intelligent camera are described.

Scholl, M. S.↗
NASA NTRS2015

Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as for hail damage swath identification. Initial validation of the automated algorithm is based upon Storm Prediction Center storm reports but also the National Severe Storm Laboratory (NSSL) Maximum Estimated Size Hail (MESH) product. Opportunities for future work are also shown, with focus on expansion of this algorithm with pixel-based image classification techniques for tracking surface changes as a result of severe weather.

Bell, Jordan R.↗
NASA NTRS1985

Experimental Verification of Identification Algorithms for Control of Flexible Structures

An on going simple laboratory experiment, referred to as the Beam Control Experiment (BCE) is described which has the essential features of a large flexible structure. The experiment is used to develop and evaluate identification and control algorithms which lock promising in the active control of high performance large space structures. Some results on the maximum likelihood identification of the parameters of the beam actuator sensor assembly from experimental data is presented.

Sridher, B.↗
NASA NTRS1996

Cassini Star Tracking and Identification Algorithms, Scene Simulation, and Testing

The Cassini mission will use autonomous star identification for initial attitude determination and a star tracking function for maintaining attitude. Because of the complexity of the StarID software, special software simulation tools were created to simulate the Stellar Reference Unit (SRU) output as a function of commands, spacecraft attitude, and star scene, and to allow the introduction of fault conditions. This paper gives the overview of the algorithm design and SRU simulation and a description of the simulation test results and a comparison with field test results obtained using the engineering model SRU.

Cassini↗
NASA NTRS1986

Investigation of scene identification algorithms for radiation budget measurements

The computation of Earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12% of the respective exitances.

Diekmann, F. J.↗
NASA NTRS1989

Investigation of scene identification algorithms for radiation budget measurements

The computation of earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12 percent of the respective exitances.

Diekmann, F. J.↗
NASA NTRS1991

A class of least-squares filtering and identification algorithms with systolic array architectures

A unified approach is presented for deriving a large class of new and previously known time- and order-recursive least-squares algorithms with systolic array architectures, suitable for high-throughput-rate and VLSI implementations of space-time filtering and system identification problems. The geometrical derivation given is unique in that no assumption is made concerning the rank of the sample data correlation matrix. This method utilizes and extends the concept of oblique projections, as used previously in the derivations of the least-squares lattice algorithms. Exponentially weighted least-squares criteria are considered for both sliding and growing memory.

Kalson, Seth Z.↗
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.↗