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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

Tang, Liang↗
NASA NTRS1983

Approaches to detection of geochemical stress in vegetation

Work has been carried out to elucidate fundamental relationships between spectral properties of plants and geochemical stress, and a programme of field and laboratory work is in progress. The most significant results and conclusions at this stage are described and attention is focused on the new concepts for stress detection which have been generated. The applications of the research are relevant to the understanding of current remotely sensed data as well as relating to ideas for new instrumentation.

Horler, D. N. H.↗
NASA NTRS1987

A gridding approach to detect patterns of change in coastal wetlands from digital data

The conversion of land to water or water to land in the Grand Bayou wetlands area from 1972 to 1981 is evaluated on the basis of Landsat MSS band 2 and 4 images. A postclassification (land vs water) procedure is employed, and grids 1, 5, 10, 25, and 50 pixels square are superimposed on the classified data in an effort to reduce the effects of poor georegistration of the images (simulated by shifting one set of grids two pixels vertically and horizontally). The results are presented in tables, maps, and sample images and characterized in detail. Grids 5 or 10 pixels square are found to give percentage land/water change values and locations similar to those obtained in pixel-by-pixel analysis of nearly perfectly matched images.

Pelletier, R. E.↗
NASA NTRS1988

A photometric approach to detecting earth-sized planets

The photometric method for searching for planets around stars depends on the observation of the decrease in light flux produced by the transit of a planet across the stellar disk. It is shown that a three-year observation period should permit meaningful statements to be made about the frequency of solar-type planetary systems. A state-of-the-art photometer is being developed to test components and concepts. The goal is the development of a photometer that can routinely measure the relative brightness of stars to a precision of 1 part in 100,000.

Borucki, W. J.↗
NASA NTRS1993

A model-based approach for detection of objects in low resolution passive millimeter wave images

A model-based vision system to assist the pilots in landing maneuvers under restricted visibility conditions is described. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere, but their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. These data are exploited to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. Also analytical expressions were derived from the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.

Kasturi, Rangachar↗
NASA NTRS1993

A model-based approach for detection of objects in low resolution passive-millimeter wave images

We describe a model-based vision system to assist pilots in landing maneuvers under restricted visibility conditions. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere; but, their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. We exploit these data to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. We also derive analytical expressions for the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.

Tang, Yuan-Liang↗
NASA NTRS1994

A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.

Kasturi, Rangachar↗
NASA NTRSDate not supplied

Autoencoders for Denoising Atmospheric Profiles from ICESat-2

Abstract: The 2nd generation Ice, Cloud, and land Elevation Satellite (ICESat-2) is an altimetry mission designed primarily for measuring ice sheet elevation and sea ice thickness, provides atmospheric profiles of clouds and aerosols at 532 nm using a photo counting detection approach. While highly sensitive for the detection of tenuous aerosol and cloud features, during the day signal-to-noise-ratio (SNR) photon counting detectors are adversely impacted by solar contributions to the total signal. Averaging the data to coarser horizontal resolutions has been the standard way to increase SNR and thus allow clouds and aerosols to be more easily detectable. Recent work has demonstrated success in boosting SNR without decreasing resolution using advanced filtering techniques [Yorks et al., 2021], however, rapid advancements in Deep Learning based image denoising algorithms can further improve the SNR. Here, we present results using a state-of-the-art Deep Learning autoencoder applied to noisy ICESat-2 data to improve daytime SNR and discuss implications for atmospheric feature detection, classification, and optical property retrievals.

denoising↗
NASA NTRS2007

Applicability of a Conservative Margin Approach for Assessing NDE Flaw Detectability

Nondestructive Evaluation (NDE) procedures are required to detect flaws in structures with a high percentage detectability and high confidence. Conventional Probability of Detection (POD) methods are statistical in nature and require detection data from a relatively large number of flaw specimens. In many circumstances, due to the high cost and long lead time, it is impractical to build the large set of flaw specimens that is required by the conventional POD methodology. Therefore, in such situations it is desirable to have a flaw detectability estimation approach that allows for a reduced number of flaw specimens but provides a high degree of confidence in establishing the flaw detectability size. This paper presents an alternative approach called the conservative margin approach (CMA). To investigate the applicability of the CMA approach, flaw detectability sizes determined by the CMA and POD approaches have been compared on actual datasets. The results of these comparisons are presented and the applicability of the CMA approach is discussed.

Koshti, ajay M.↗
NASA NTRS2002

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

Hilbert, Kent↗
NASA NTRSDate not supplied

Generating Global CH4 NASA GEOS Product by Assimilating TROPOMI

Radiative properties of methane (CH4) significantly contribute to climate change and the recent acceleration of global CH4 growth requires thorough investigation into its causes. Examination of temporal and spatial CH4 variability is crucial for better understanding the shifts that are currently taking place. Integrating different CH4 observations to create a reliable, easily to use global atmospheric CH4 product could contribute to assessment of emissions processes, but remains challenging due to the lack of long satellite data records. Here we present the NASA Goddard Earth Observing System (GEOS) based global CH4 product constrained by atmospheric transport from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and assimilated CH4 from the TROPOspheric Monitoring Instrument (TROPOMI). This product uses the Constituent Data Assimilation System (CoDAS) component of the GEOS capability, which has been expanded and generalized to assimilate any satellite, ground-based, or in situ observation of atmospheric composition that can be expressed as a vertical sounding or point sample. The product is similar to the one generated by assimilating carbon dioxide (CO2) data into GEOS from Orbiting Carbon Observatory 2 (OCO-2): OCO-2 GEOS Level 3 daily and monthly, 0.5x0.625 assimilated CO2 V10r. The preliminary product is investigated using a variety of quality check approaches with the help of in situ observations to examine bias correction, error inflation, and performance of the assimilation system. Potential applications of this approach include support for interpretation of high-resolution point source detection approaches, climate and greenhouse gas reanalyses, and boundary conditions for regional modeling approaches.

Nikolay Balashov↗
NASA NTRS2013

A Systems-Level Perspective on Engine Ice Accretion

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8% of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗