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At least 145 records · Page 8

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NASA NTRS2007

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least-squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

Litt, Jonathan S.↗

NASA NTRS2007

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

Litt, Jonathan S.↗

NASA NTRS2010

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗

NASA NTRS2019

Characterization of Low Frequency Auditory Filters

The purpose of this study is to characterize auditory filters at low frequencies, defined as below about 100 Hz. Three experiments were designed and executed. They were conducted in the Exterior Effects Room at the NASA Langley Research Center, a psychoacoustic facility designed for presentation of aircraft flyover sounds to groups of test subjects. The first experiment measured 36 subjects’ hearing threshold for pure tones (at 25, 31.5, 40, 50, 63 and 80 Hz) in “quiet” conditions. The subjects, male and female, had a wide age range. This experiment allowed the performance of the test facility to be assessed and also provided screened test subjects for participation in subsequent experiments. The second and third experiments used 20 and 10 test subjects, respectively, and measured psychophysical tuning curves (PTCs) that describe auditory filters with center frequencies of approximately 63 and 50 Hz. The latter is assumed to be the lowest (bottom) auditory filter; thus, sounds at frequencies below about 50 Hz are perceived via the lower skirt of this lowest filter. All experiments used an adaptive, three-alternative forced-choice test procedure using either variable level tones or variable level, narrowband noise maskers. Measured PTCs were found to be very similar to other recently published data, both in terms of mean values and intersubject variation, despite different experimental protocols, different test facilities, and a wide range in subjects’ age.

Rafaelof, Menachem↗

NASA NTRS2020

Fast Neutron Spectroscopy with Organic Scintillation Detectors in a High-Radiation Environment

Organic scintillators with pulse shape discrimination capability are widely used in both research and practical applications of neutron detection. The neutron and gamma-ray identification performance of the detector depends on the classification algorithms, noise filters and pileup rejection criteria in a high-flux bremsstrahlung radiation environment. In this paper, a technique has been developed and implemented for the neutron detection with multiple filter and discrimination steps, which to a high confidence level eliminates counting of gamma-ray pulses. Such a technique is merited when making measurements in a high flux bremsstrahlung and secondary fluorescence environment. The EJ-309 and stilbene detectors coupled to the digital data acquisition system were used for the calibration assessments with standard gamma-ray and neutron sources such as 137Cs, 60Co, 252Cf, and Am-Be. The MCNPX-PoliMi and GEANT4 toolkits were used to simulate the light output and the optical photon transport in the scintillators and create detector response functions for each type of detector. The neutron spectrum unfolding algorithm, GRAVELW, was used to recreate and calibrate with the Am-Be as final step before applying the neutron detection system to extract fusion neutron spectra generated in an intense bremsstrahlung radiation environment. This new technique described offers the user the ability to measure neutron spectra in a high-flux gamma-ray field and tune the parameters to meet required filtering needs.

Neutron Detector, Organic Scintillator, PulseShape↗

NASA NTRS2009

Latency and User Performance in Virtual Environments and Augmented Reality

System rendering latency has been recognized by senior researchers, such as Professor Fredrick Brooks of UNC (Turing Award 1999), as a major factor limiting the realism and utility of head-referenced displays systems. Latency has been shown to reduce the user's sense of immersion within a virtual environment, disturb user interaction with virtual objects, and to contribute to motion sickness during some simulation tasks. Latency, however, is not just an issue for external display systems since finite nerve conduction rates and variation in transduction times in the human body's sensors also pose problems for latency management within the nervous system. Some of the phenomena arising from the brain's handling of sensory asynchrony due to latency will be discussed as a prelude to consideration of the effects of latency in interactive displays. The causes and consequences of the erroneous movement that appears in displays due to latency will be illustrated with examples of the user performance impact provided by several experiments. These experiments will review the generality of user sensitivity to latency when users judge either object or environment stability. Hardware and signal processing countermeasures will also be discussed. In particular the tuning of a simple extrapolative predictive filter not using a dynamic movement model will be presented. Results show that it is possible to adjust this filter so that the appearance of some latencies may be hidden without the introduction of perceptual artifacts such as overshoot. Several examples of the effects of user performance will be illustrated by three-dimensional tracking and tracing tasks executed in virtual environments. These experiments demonstrate classic phenomena known from work on manual control and show the need for very responsive systems if they are indented to support precise manipulation. The practical benefits of removing interfering latencies from interactive systems will be emphasized with some classic final examples from surgical telerobotics, and human-computer interaction.

Ellis, Stephen R.↗

NASA NTRS2004

Tunable-Bandwidth Filter System

A tunable-bandwidth filter system (TBFS), now undergoing development, is intended to be part of a remote sensing multispectral imaging system that will operate in the visible and near infrared spectral region (wavelengths from 400 to 900 nm). Attributes of the TBFS include rapid tunability of the pass band over a wide wavelength range and high transmission efficiency. The TBFS is based on a unique integration of two pairs of broadband Raman reflection holographic filters with two rotating spherical lenses. In experiments, a prototype of the TBFS, was shown to be capable of spectral sampling of images in the visible range over a 200 nm spectral range with a spectral resolution of 30 nm. The figure depicts the optical layout of a prototype of the TBFS as part of a laboratory multispectral imaging system for the spectral sampling of color test images in two orthogonal polarizations. Each pair of broadband Raman reflection holographic filters is mounted at an equatorial plane between two halves of a spherical lens. The two filters in each pair are characterized by steep spectral slopes (equivalently, narrow spectral edges), no ripple or side lobes in their pass bands, and a few nanometers of non-overlapping wavelength range between their pass bands. Each spherical lens and thus the filter pair within it is rotated in order to rapidly tune its pass band. The rotations of are effected by electronically controlled, programmable, high-precision rotation stages. The rotations are coordinated by electronic circuits operating under overall supervision of a personal computer in order to obtain the desired variation of the overall pass bands with time. Embedding the filters inside the spherical lenses increases the range of the hologram incidence angles, making it possible to continuously tune the pass and stop bands of the filters over a wider wavelength range. In addition, each spherical lens also serves as part of the imaging optics: The telephoto lens focuses incoming light to a field stop that is also a focal point of each spherical lens. A correcting lens in front of the field stop compensates for the spherical aberration of the spherical lenses. The front surface of each spherical lens collimates the light coming from the field stop. After the collimated light passes through the filter in the spherical lens, the rear surface of the lens focuses the light onto a charge-coupled-device image detector.

Bailey, John W.↗

NASA NTRS2006

Tunable-Bandwidth Filter System

A tunable-bandwidth filter system (TBFS), now undergoing development, is intended to be part of a remote-sensing multispectral imaging system that will operate in the visible and near infrared spectral region (wavelengths from 400 to 900 nm). Attributes of the TBFS include rapid tunability of the pass band over a wide wavelength range and high transmission efficiency. The TBFS is based on a unique integration of two pairs of broadband Raman reflection holographic filters with two rotating spherical lenses. In experiments, a prototype of the TBFS was shown to be capable of spectral sampling of images in the visible range over a 200-nm spectral range with a spectral resolution of .30 nm. The figure depicts the optical layout of a prototype of the TBFS as part of a laboratory multispectral imaging system for the spectral sampling of color test images in two orthogonal polarizations. Each pair of broadband Raman reflection holographic filters is mounted at an equatorial plane between two halves of a spherical lens. The two filters in each pair are characterized by steep spectral slopes (equivalently, narrow spectral edges), no ripple or side lobes in their pass bands, and a few nanometers of non-overlapping wavelength range between their pass bands. Each spherical lens and thus the filter pair within it is rotated in order to rapidly tune its pass band. The rotations of the lenses are effected by electronically controlled, programmable, high-precision rotation stages. The rotations are coordinated by electronic circuits operating under overall supervision of a personal computer in order to obtain the desired variation of the overall pass bands with time. Embedding the filters inside the spherical lenses increases the range of the hologram incidence angles, making it possible to continuously tune the pass and stop bands of the filters over a wider wavelength range. In addition, each spherical lens also serves as part of the imaging optics: The telephoto lens focuses incoming light to a field stop that is also a focal point of each spherical lens. A correcting lens in front of the field stop compensates for the spherical aberration of the spherical lenses. The front surface of each spherical lens collimates the light coming from the field stop. After the collimated light passes through the filter in the spherical lens, the rear surface of the lens focuses the light onto a charge-coupled-device image detector.

Aye, Tin↗

NASA NTRS1995

An automated method of tuning an attitude estimator

Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.

Mason, Paul A. C.↗

NASA NTRS2009

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Simon, Donald L.↗

NASA NTRS2003

Performance Enhancement of Tunable Bandpass Filters Using Selective Etched Ferroelectric Thin Films

The inclusion of voltage-tunable barium strontium titanate (BSTO) thin films into planar band pass filters offers tremendous potential to increase their versatility. The ability to tune the passband so as to correct for minor deviations in manufacturing tolerances, or to completely reconfigure the operating frequencies of a microwave communication system, are highly sought-after goals. However, use of ferroelectric films in these devices results in higher dielectric losses, which in turn increase the insertion loss and decrease the quality factors of the filters. This study explores the use of patterned ferroelectric layers to minimize dielectric losses without degrading tunability. Patterning the ferroelectric layers enables us to constrict the width of the ferroelectric layers between the coupled microstrip lines, and minimize losses due to ferroelectric layers. Coupled one-pole microstrip bandpass filters with fundamental resonances at approx. 7.2 GHz and well defined harmonic resonances at approx. 14.4 and approx. 21.6 GHz, were designed, simulated and tested. For one of the filters, experimental results verified that its center frequency was tunable by 528 MHz at a center frequency of 21.957 GHz, with insertion losses varying from 4.3 to 2.5 dB, at 0 and 3.5 V/micron, respectively. These data demonstrate that the tuning-to-loss figure of merit of tunable microstrip filters can be greatly improved using patterned ferroelectric thin films as the tuning element, and tuning can be controlled by engineering the ferroelectric constriction in the coupled sections.

Miranda, Felix A.↗

NASA NTRS2004

A New Approach to Identify Optimal Properties of Shunting Elements for Maximum Damping of Structural Vibration Using Piezoelectric Patches

The use of shunted piezoelectric patches in reducing vibration and sound radiation of structures has several advantages over passive viscoelastic elements, e.g., lower weight with increased controllability. The performance of the piezoelectric patches depends on the shunting electronics that are designed to dissipate vibration energy through a resistive element. In past efforts most of the proposed tuning methods were based on modal properties of the structure. In these cases, the tuning applies only to one mode of interest and maximum tuning is limited to invariant points when based on den Hartog's invariant points concept. In this study, a design method based on the wave propagation approach is proposed. Optimal tuning is investigated depending on the dynamic and geometric properties that include effects from boundary conditions and position of the shunted piezoelectric patch relative to the structure. Active filters are proposed as shunting electronics to implement the tuning criteria. The developed tuning methods resulted in superior capabilities in minimizing structural vibration and noise radiation compared to other tuning methods. The tuned circuits are relatively insensitive to changes in modal properties and boundary conditions, and can applied to frequency ranges in which multiple modes have effects.

Park, Junhong↗

NASA NTRS2000

Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)

Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.

Peterson, Chariya↗

NASA NTRS2014

Improving FermiI Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecrafts ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45 improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗

NASA NTRS2014

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗

NASA NTRS2013

Optimized tuner selection for engine performance estimation

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Simon, Donald L.↗

NASA NTRS2004

Heterodyne Interferometer with a Phase Modulated Source

The present invention relates to a heterodyne interferometer system with a pre-processing of the target signal to isolate and remove self-interference signals using a known phase modulation of the carrier signal's frequency. Where self- interference signals do not include a time delay inherent in the target signal that travels to the target reflector, by selecting a modulation frequency tuned to the time delay and then filtering the resultant signal the target beam can be isolated and the self-interference signal can be effectively removed The system includes a modulation unit to apply a phase modulation to the carrier signal, and a mixing unit that demodulates the target signal at the modulation frequency to isolate the target beam.

Serge Dubovitsky↗

NASA NTRS2010

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Simon, Donald L.↗