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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Aircraft Engine Sensor/Actuator/Component Fault Diagnosis Using a Bank of Kalman Filters

In this report, a fault detection and isolation (FDI) system which utilizes a bank of Kalman filters is developed for aircraft engine sensor and actuator FDI in conjunction with the detection of component faults. This FDI approach uses multiple Kalman filters, each of which is designed based on a specific hypothesis for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, from which a specific fault is isolated. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The performance of the FDI system is evaluated against a nonlinear engine simulation for various engine faults at cruise operating conditions. In order to mimic the real engine environment, the nonlinear simulation is executed not only at the nominal, or healthy, condition but also at aged conditions. When the FDI system designed at the healthy condition is applied to an aged engine, the effectiveness of the FDI system is impacted by the mismatch in the engine health condition. Depending on its severity, this mismatch can cause the FDI system to generate incorrect diagnostic results, such as false alarms and missed detections. To partially recover the nominal performance, two approaches, which incorporate information regarding the engine s aging condition in the FDI system, will be discussed and evaluated. The results indicate that the proposed FDI system is promising for reliable diagnostics of aircraft engines.

Kobayashi, Takahisa↗
NASA NTRS2003

Application of a Bank of Kalman Filters for Aircraft Engine Fault Diagnostics

In this paper, a bank of Kalman filters is applied to aircraft gas turbine engine sensor and actuator fault detection and isolation (FDI) in conjunction with the detection of component faults. This approach uses multiple Kalman filters, each of which is designed for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, thereby isolating the specific fault. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The proposed FDI approach is applied to a nonlinear engine simulation at nominal and aged conditions, and the evaluation results for various engine faults at cruise operating conditions are given. The ability of the proposed approach to reliably detect and isolate sensor and actuator faults is demonstrated.

Kobayashi, Takahisa↗
NASA NTRS2004

Interplanetary navigation using a continental baseline large antenna arrays

Navigation is a key component of interplanetary missions and must continue to be precise with the changing landscape of antenna design. Improvements for the Deep Space Network (DSN) may include the use of antenna arrays to simulate the power of a larger single antenna at much lower operating and construction costs. Therefore, it is necessary to test the performance of arrayed antennas from a navigational point-of-view. This initial investigation focuses on the performance of arrayed antennas from a navigational point-of-view. This initial investigation focuses on the performance of delta one-way range measurements using a shorter baseline with more data collection then current systems use. With all other parameter equal, the longer the baseline, the better the accuracy for navigation making the number of data packets very important. This trade study compares baseline distances ranging from 1 to 1000km with an in use baseline, looking at a due east baseline, a due north baseline at 45 degrees East of North. The precision of the baseline systems can be found through a simulated created for this purpose using the Jet Propulsion Lab based Monte navigation and mission design tool. The simulation combines the delta one-way range measurements with two-range and two-way Doppler measurements and puts the measurements through a Kalman filter to determine an orbit solution. Noise is added along with initial errors to give the simulation realism. This study is an important step towards the assessment of the utility of arrays for navigational purposes. The preliminary results have showed a decrease in reliability as the baseline is shortened but the larger continental baselines show comparable results t that of the current Goldstone to Canberra.

very long baseline interferometry (VLBI)↗
NASA NTRS2003

SIRTF Focal Plane Survey: A Pre-flight Error Analysis

This report contains a pre-flight error analysis of the calibration accuracies expected from implementing the currently planned SIRTF focal plane survey strategy. The main purpose of this study is to verify that the planned strategy will meet focal plane survey calibration requirements (as put forth in the SIRTF IOC-SV Mission Plan [4]), and to quantify the actual accuracies expected. The error analysis was performed by running the Instrument Pointing Frame (IPF) Kalman filter on a complete set of simulated IOC-SV survey data, and studying the resulting propagated covariances. The main conclusion of this study is that the all focal plane calibration requirements can be met with the currently planned survey strategy. The associated margins range from 3 to 95 percent, and tend to be smallest for frames having a 0.14" requirement, and largest for frames having a more generous 0.28" (or larger) requirement. The smallest margin of 3 percent is associated with the IRAC 3.6 and 5.8 micron array centers (frames 068 and 069), and the largest margin of 95 percent is associated with the MIPS 160 micron array center (frame 087). For pointing purposes, the most critical calibrations are for the IRS Peakup sweet spots and short wavelength slit centers (frames 019, 023, 052, 028, 034). Results show that these frames are meeting their 0.14" requirements with an expected accuracy of approximately 0.1", which corresponds to a 28 percent margin.

pointing↗
NASA NTRS2003

Simpler Alternative to an Optimum FQPSK-B Viterbi Receiver

A reduced-complexity alternative to an optimum FQPSK-B Viterbi receiver has been invented. As described, the reduction in complexity is achieved at the cost of only a small reduction in power performance [performance expressed in terms of a bit-energy-to-noise-energy ratio (Eb/N0) for a given bit-error rate (BER)]. The term "FQPSK-B" denotes a baseband-filtered version of Feher quadrature-phase-shift keying, which is a patented, bandwidth-efficient phase-modulation scheme named after its inventor. Heretofore, commercial FQPSK-B receivers have performed symbol-by-symbol detection, in each case using a detection filter (either the proprietary FQPSK-B filter for better BER performance, or a simple integrate-and-dump filter with degraded performance) and a sample-and-hold circuit.

Lee, Dennis↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

There are many flare forecasting models. For an excellent review and comparison of some of them see Barnes et al. (2016). All these models are successful to some degree, but there is a need for better models. We claim the most successful models explicitly or implicitly base their forecasts on various estimates of components of the photospheric current density J, based on observations of the photospheric magnetic field B. However, none of the models we are aware of compute the complete J. We seek to develop a better model based on computing the complete photospheric J. Initial results from this model are presented in this talk. We present a data driven, near photospheric, 3 D, non-force free magnetohydrodynamic (MHD) model that computes time series of the total J, and associated resistive heating rate in each pixel at the photosphere in the neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of B measured by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series of B in every AR pixel. Errors in B due to these periods can be significant.

Goodman, Michael L.↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

A data driven, near photospheric, 3 D, non-force free magnetohydrodynamic model pre- dicts time series of the complete current density, and the resistive heating rate Q at the photosphere in neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of the magnetic field B observed by the Helioseismic & Magnetic Imager on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series for B in every AR pixel. Errors in B due to these periods can be significant. The number of occurrences N(q) of values of Q > or = q for each AR time series is found to be a scale invariant power law distribution, N(Q) / Q−s, above an AR dependent threshold value of Q, where 0.3952 < or = s < or = 0.5298 with mean and standard deviation of 0.4678 and 0.0454, indicating little variation between ARs. Observations show that the number of occurrences N(E) of coronal flares with a total energy released > or = E obeys the same type of distribution, N(E) / E−S, above an AR dependent threshold value of E, with 0.38 < or approx. S < or approx. 0.60, also with little variation among ARs. Within error margins the ranges of s and S are nearly identical. This strong similarity between N(Q) and N(E) suggests a fundamental connection between the process that drives coronal flares and the process that drives photospheric NLR heating rates in ARs. In addition, results suggest it is plausible that spikes in Q, several orders of magnitude above background values, are correlated with times of the subsequent occurrence of M or X flares.

Goodman, Michael L.↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

A data driven, near photospheric, 3 D, non-force free magnetohydrodynamic model predicts time series of the complete current density, and the resistive heating rate Q at the photosphere in neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of the magnetic field B observed by the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series for B in every AR pixel. Errors in B due to these periods can be significant. The number of occurrences N(q) of values of Q > or = q for each AR time series is found to be a scale invariant power law distribution, N(Q) / Q−s, above an AR dependent threshold value of Q, where 0.3952 < or = s < or = 0.5298 with mean and standard deviation of 0.4678 and 0.0454, indicating little variation between ARs. Observations show that the number of occurrences N(E) of coronal flares with a total energy released > or = E obeys the same type of distribution, N(E) / E−S, above an AR dependent threshold value of E, with 0.38 < or approx. S < or approx. 0.60, also with little variation among ARs. Within error margins the ranges of s and S are nearly identical. This strong similarity between N(Q) and N(E) suggests a fundamental connection between the process that drives coronal flares and the process that drives photospheric NLR heating rates in ARs. In addition, results suggest it is plausible that spikes in Q, several orders of magnitude above background values, are correlated with times of the subsequent occurrence of M or X flares.

Goodman, Michael L.↗
DOE OSTI2020

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material e ects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filterbased methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall eciency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and oine reconstruction for the HL-LHC CMS tracker.

Cerati, Giuseppe↗
NASA NTRS2003

The Imager for Mars Pathfinder Insurance Pan

The Imager for Mars Pathfinder (IMP) obtained a full panorama of the Sagan Memorial Station landing site on Sol 2, before the IMP mast was deployed. The images in this panorama were taken in 4 filters (including stereo) and losslessly compressed to provide a high-quality multispectral survey of the landing site even if the IMP mast did not successfully deploy; this data set was therefore called the Insurance Pan. It was completed late in the afternoon of Sol 2, just before the IMP mast was (successfully) deployed. The data were stored in memory and returned to Earth after it became clear that downlink rates were higher than expected. The Insurance Pan horizontal (azimuth) coverage is nearly complete, with gaps caused by pointing errors and data packet losses. Stereo data were acquired in the blue (445 nm) filter, as well as right-eye green (531 nm), orange (600 nm), and near-infrared (752 nm) data.

K E Herkenhoff↗
NASA NTRS2003

High Order Filter Methods for Shock/Turbulence MHD Flows

Low-dissipative high order filter finite difference methods for shock/turbulence/combustion compressible viscous MHD flows has been constructed. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field (del (raided dot) B) numerical error in the sense that no standard divergence cleaning is required. For certain 2-D MHD test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.

Yee, H. C.↗
NASA NTRS1999

Assimilation of Satellite Altimeter Data With a Four Dimensional Model of the Japan Sea

A data assimilation is carried out to detect the variability of the Japan Sea circulation in the range from a few days to several years and from eddy to basin scale. The model applied in this study is the same 1/6 degree GFDL MOM1 as Kim and Yoon (1999) but is driven by ECMWF daily wind stress, heat and fresh water fluxes. The satellite altimeter data of TOPEX/POSEIDON, ERS-1 (phase C and G) and -2 are assimilated by an approximate Kalman filter (Fukumori and M.Rizzoli, 1995). The approximation is made by seeking an asymptotic steady error covariance matrix (Fukumori et al., 1993) and by introducing a coarser grid model for the innovation (data-model misfit). The coarse grid model is defined on 1/2 degree horizontal resolution and consists of the barotropic stream function, first baroclinic displacement and velocity amplitudes. The assimilated estimates explain about 6cm sea level variability of the data (approximately 12cm in the southern part), which is much larger than the previous reduced-gravity model and TOPEX/POSEIDON altimeter data assimilation (Hirose et al., 1999). The impacts of the T/P and ERS data on the filtered estimates are comparable. The result also shows high correlation to subsurface water temperatures measured by CTD. Many of the mesoscale eddies/disturbances travel east-northeastward with the advection speed of 1-3cm/s though most of them generated in the western region can not pass over the Oki Spur. The quasi-biennial variability found by Hirose and Ostrovskii (1999) did not show clear propagation pattern. The shallow Oki Spur may work as a "western boundary" to this signal. This is more plausible estimation than by the R-G model which has no bottom topography.

Hirose, Naoki↗
NASA NTRS2005

TRMM Re-Entry Planning: Attitude Determination and Control During Thruster Modes

The Tropical Rainfall Measuring Mission (TRMM) spacecraft has been undergoing design for a controlled re-entry to Earth. During simulation of the re-entry plan, there was evidence of errors in the attitude determination algorithms during thruster modes. These errors affected the bum efficiency, and thus planning, during re-entry. During thruster modes, the spacecraft attitude is controlled off of integrated Gyro Error Angles that were designed to closely follow the nominal spacecraft pointing frame (Tip Frame). These angles, however, were not exactly mapped to the Tip Frame from the Body Frame. Additionally, in the initial formulation of the thruster mode attitude determination algorithms, several assumptions and approximations were made to conserve processor speed. These errors became noticeable and significant when simulating bums of much longer duration (-10 times) than had been produced in flight. A solution is proposed that uses attitude determination information from a propagated extended Kalman filter that already exists in the TRMM thruster modes. This attitude information is then used to rotate the Gyro Error Angles into the Tip Frame. An error analysis is presented that compares the two formulations. The new algorithm is tested using the TRMM High-Fidelity Simulator and verified with the TRMM Software Testing and Training Facility. Simulation results for both configurations are also presented.

DeWeese, Keith↗
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
DOE OSTI2026

Generalized Theory and Realization of Reconfigurable Bandpass Filtering Equalizers

Here, in this article, a generalized theory of bandpass filtering equalizers is proposed. A filtering equalizer is a device that combines the frequency-selective properties of a filter with the controllable slope of an equalizer into a single component. The equations used to design the function for a desired slope are provided, and the design methodology to determine the necessary filtering polynomials is also shown. The controllable slope of the dual-function component is realized using variable capacitors, which are used to tune both a transmission zero and a matching network to achieve the desired slope. A third-order bandpass filtering equalizer is designed, fabricated, and measured to verify the generalized theory. The component is designed to operate at 1 GHz with a slope that can be reconfigured from 1 to 3 dB along the passband. This proposed filtering equalizer demonstrates the feasibility of a tunable, low-cost, size, weight, and power (C-SWaP) solution to enable increased flatness in the overall system response and thereby decrease the error vector magnitude (EVM) of future radio frequency (RF) systems and a design process that allows for future development of filtering equalizers.

Filter↗
NASA NTRS1992

Recursive time-varying filter banks for subband image coding

Filter banks and wavelet decompositions that employ recursive filters have been considered previously and are recognized for their efficiency in partitioning the frequency spectrum. This paper presents an analysis of a new infinite impulse response (IIR) filter bank in which these computationally efficient filters may be changed adaptively in response to the input. The filter bank is presented and discussed in the context of finite-support signals with the intended application in subband image coding. In the absence of quantization errors, exact reconstruction can be achieved and by the proper choice of an adaptation scheme, it is shown that IIR time-varying filter banks can yield improvement over conventional ones.

Smith, Mark J. T.↗
NASA NTRS2004

Spitzer Instrument Pointing Frame (IPF) Kalman Filter Algorithm

This paper discusses the Spitzer Instrument Pointing Frame (IPF) Kalman Filter algorithm. The IPF Kalman filter is a high-order square-root iterated linearized Kalman filter, which is parametrized for calibrating the Spitzer Space Telescope focal plane and aligning the science instrument arrays with respect to the telescope boresight. The most stringent calibration requirement specifies knowledge of certain instrument pointing frames to an accuracy of 0.1 arcseconds, per-axis, 1-sigma relative to the Telescope Pointing Frame. In order to achieve this level of accuracy, the filter carries 37 states to estimate desired parameters while also correcting for expected systematic errors due to: (1) optical distortions, (2) scanning mirror scale-factor and misalignment, (3) frame alignment variations due to thermomechanical distortion, and (4) gyro bias and bias-drift in all axes. The resulting estimated pointing frames and calibration parameters are essential for supporting on-board precision pointing capability, in addition to end-to-end 'pixels on the sky' ground pointing reconstruction efforts.

calibration↗
NASA NTRS1972

Space shuttle guidance, navigation and control equation document no. 4: Precision state and filter weighting matrix extrapolation

The Precision State and Filter Weighting Matrix Extrapolation Routine is described which provides the capability to extrapolate any spacecraft geocentric state vector either backwards or forwards in time through a force field consisting of the earth's primary central-force gravitational attraction and a superimposed perturbing acceleration. The routine also provides the capability of extrapolating the filter-weighting matrix along the precision trajectory. This matrix is a square root form of the error covariance matrix and contains statistical information relative to the accuracies of the state vectors and certain other optionally estimated quantities. The routine is a cooled algorithm for the numerical solution of modified forms of the basic differential equations which are satisfied by the geocentric state vector of the spacecraft's center of mass and by the filter-weighting matrix.

Robertson, W. M.↗