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At least 235 records · Page 13

Detecting Faults By Use Of Hidden Markov Models

Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

Smyth, Padhraic J.↗

Uses And Characteristics Of Dynamic Tradeoff Evaluation

Report discusses basic concepts, some applications, and performance characteristics of dynamic tradeoff evaluation (DTE). Basic concepts of DTE also described in "Dynamic Restructuring of Problems in Artificial Intelligence" (NPO-18488). DTE is method of enhancing real-time performance of artificial-intelligence system such as might be used to monitor data from multiple sensors in factory, aircraft, spacecraft, or other complex system of equipment. Report presents evaluation of DTE as applied to spacecraft-monitoring problems.

Schwuttke, Ursula M.↗

Acoustic Study of B Helical Mode for Choked Axisymmetric Nozzle

An acoustic near-field study was performed for an axisymmetric conical convergent nozzle operating at a pressure ratio corresponding to a fully expanded Mach number of 1.3. The acoustic measurements were performed in the nozzle exit plane using multiple sensors arranged around the periphery of the nozzle. The acquired data were simultaneously digitized. The acoustic spatial characteristics, describing the large-scale structure associated with the preferred shear layer instability mode, were determined for the dominant B screech mode. The nozzle was fitted with a lip thickening device to determine the effect of this geometric variable on the spatial structure of the jet. For the thin-lipped configuration, the flapping structure of the B screech mode was found to precess in a time- dependent manner about the jet axis. Increasing of the nozzle exit lip thickness altered the spatial characteristics of this mode from a flapping to a time-dependent flapping or spinning. Using the autobicoherence spectrum, frequency dependencies were found to exist in the acoustic data of the thick-lipped configuration. These dependencies may be related to the nonlinearity of the jet and/or the time-dependent nature of the B mode spatial structure.

Ponton, Michael K.↗

A Comparison of Vibration and Oil Debris Gear Damage Detection Methods Applied to Pitting Damage

Helicopter Health Usage Monitoring Systems (HUMS) must provide reliable, real-time performance monitoring of helicopter operating parameters to prevent damage of flight critical components. Helicopter transmission diagnostics are an important part of a helicopter HUMS. In order to improve the reliability of transmission diagnostics, many researchers propose combining two technologies, vibration and oil monitoring, using data fusion and intelligent systems. Some benefits of combining multiple sensors to make decisions include improved detection capabilities and increased probability the event is detected. However, if the sensors are inaccurate, or the features extracted from the sensors are poor predictors of transmission health, integration of these sensors will decrease the accuracy of damage prediction. For this reason, one must verify the individual integrity of vibration and oil analysis methods prior to integrating the two technologies. This research focuses on comparing the capability of two vibration algorithms, FM4 and NA4, and a commercially available on-line oil debris monitor to detect pitting damage on spur gears in the NASA Glenn Research Center Spur Gear Fatigue Test Rig. Results from this research indicate that the rate of change of debris mass measured by the oil debris monitor is comparable to the vibration algorithms in detecting gear pitting damage.

Dempsey, Paula J.↗

NASA SMART Probe: Breast Cancer Application

There is evidence in breast cancer and other malignancies that the physiologic environment within a tumor correlates with clinical outcome. We are developing a unique percutaneous Smart Probe to be used at the time of needle biopsy of the breast. The Smart Probe will simultaneously measure multiple physiologic parameters within a breast tumor. Direct and indirect measurements of tissue oxygen levels, blood flow, pH, and tissue fluid pressure will be analyzed in real-time. These parameters will be interpreted individually and collectively by innovative neural network techniques using advanced intelligent software. The goals are 1) develop a pecutaneous Smart Probe with multiple sensor modalities and applying advanced Information Technologies to provide real time diagnostic information of the tissue at tip of the probe, 2) test the percutaneous Smart Probe in women with benign and malignant breast masses who will be undergoing surgical biopsy, 3) correlate probe sensor data with benign and malignant status of breast masses, 4) determine whether the probe can detect physiologic differences within a breast tumor, and its margins, and in adjacent normal breast tissue, 5) correlate probe sensor data with known prognostic factors for breast caner, including tumor size, tumor grade, axillary lymph node metastases, estrogen receptor and progesterone receptor status.

Mah, Robert W.↗

Radiation Climatology of the Greenland Ice Sheet Derived from Greenland Climate Network Data

The magnitude of shortwave and longwave dative fluxes are critical to surface energy balance variations over the Greenland ice sheet, affecting many aspects of its climate, including melt rates, the nature of low-level temperature inversions, the katabatic wind regime and buoyant stability of the atmosphere. Nevertheless, reliable measurements of the radiative fluxes over the ice sheet are few in number, and have been of limited duration and areal distribution (e.g. Ambach, 1960; 1963, Konzelmann et al., 1994, Harding et al., 1995, Van den Broeke, 1996). Hourly GC-Net radiation flux measurements spanning 1995-2001 period have been used to produce a monthly dataset of surface radiation balance components. The measurements are distributed widely across Greenland and incorporate multiple sensors

Steffen, Konrad↗

Effect of altered sensory conditions on multivariate descriptors of human postural sway

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

NASA Discipline Neuroscience↗

Atmospheric Composition Data and Information Services Center (ACDISC)

NASA's GSFC Earth Sciences (GES) Data and Information and Data Services Center (DISC) manages the archive, distribution and data access for atmospheric composition data from AURA'S OMI, MLS, and hopefully one day, HIRDLS instruments, as well as heritage datasets from TOMS, UARS, MODIS, and AIRS. This data is currently archived in the GES Distributed Active Archive Center (DAAC). The GES DISC has begun the development of a community driven data management system that's sole purpose is to manage and provide value added services to NASA's Atmospheric Composition (AC) Data. This system, called the Atmospheric Composition Data and Information Services Center (ACDISC) will provide access all AC datasets from the above mentioned instruments, as well as AC datasets residing at remote archive sites (e.g, LaRC DAAC) The goals of the ACDISC are to: 1) Provide a data center for Atmospheric Scientists, guided by Atmospheric Scientists; 2) Be absolutely responsive to the data and data service needs of the Atmospheric Composition (AC) community; 3) Provide services (i.e., expertise) that will facilitate the effortless access to and usage of AC data; 4) Collaborate with AC scientists to facilitate the use of data from multiple sensors for long term atmospheric research. The ACDISC is an AC specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques that facilitate science data usage. The purpose of this presentation is to provide the evolution path that the GES DISC in order to better serve AC data, and also to receive continued community feedback and further foster collaboration with AC data users and providers.

Kempler, S.↗

Multipoint sensing by intelligent collectives

Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.

multipoint measurement sensor networks↗

FPGA development for high altitude subsonic parachute testing

This paper describes a rapid, top down requirements-driven design of a Field Programmable Gate Array (FPGA) used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and control storage of telemetry data from multiple sensors throughout launch, ascent, deployment and descent phases of the subsonic parachute test.

Field Programmable Gate Array (FPGA)↗

High altitude subsonic parachute field programmable gate array

This paper describes a rapid, top down requirements-driven design of an FPGA used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and control storage of telemetry data from multiple sensors throughout; launch, ascent, deployment and descent phases of the subsonic parachute test.

FPGA methodology↗

An Overview of Inter-comparison Methodologies for Terra and Aqua MODIS Calibration

With increasing efforts on data fusion and long-term climate data records (CDR) using observations made by multiple sensors, on the same or different platforms, their cross-calibration and validation work has become more and more important. The uncertainties of the climate models and data records depend not only on the calibration quality of individual sensors but also on their calibration consistency. This paper provides an overview of methodologies used by the MODIS Characterization Support Team (MCST) at NASA GSFC for the inter-comparison studies of Terra and Aqua MODIS on-orbit calibration. Each MODIS was built with a set of onboard calibrators (OBC) that include a blackbody (BB), a solar diffuser (SD), and a solar diffuser stability monitor (SDSM). The BB is primarily used for the thermal emissive bands (TEB) calibration and the SD/SDSM system for the reflective solar bands (RSB) calibration. Although the-instrument design and calibration approach are nearly identical for both Terra and Aqua MODIS and they all went through an extensive and similar pre-launch calibration and characterization process, still their on-orbit calibration consistency needs to be carefully examined and validated as many science products have been generated from observations made by both instruments. Methodologies discussed in this paper include inter-comparison studies using the Moon, a third sensor, and ground targets. Our results show that Terra and Aqua reflective solar bands and thermal emissive bands have been calibrated consistently with excellent long-term stabilities. For the 11 and 12 micrometers sea surface temperature (SST) bands, the calibration difference of Terra and Aqua MODIS is less than 0.2K.

Xiong, X.↗

Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

Brown, Molly E.↗

Cryogenic Chamber for Servo-Hydraulic Materials Testing

A compact cryogenic test chamber can be cooled to approximately 5 to 6 Kelvin for materials testing. The system includes a temperature controller and multiple sensors to measure specimen temperature at different locations. The testing chamber provides a fast and easy method to perform materials testing at lower than liquid nitrogen temperature (77 K). The purpose of the chamber is to cool a composite lap shear specimen to approximately 20 K so that tensile test force and displacement data may be acquired at this cryogenic temperature range.

Francis, John J.↗

Automated Detection of Events of Scientific Interest

A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

James, Mark↗

Updates of Land Surface and Air Quality Products in NASA MAIRS and NEESPI Data Portals

Following successful support of the Northern Eurasia Earth Sciences Partner Initiative (NEESPI) project with NASA satellite remote sensing data, from Spring 2009 the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has been working on collecting more satellite and model data to support the Monsoon Asia Integrated Regional Study (MAIRS) project. The established data management and service infrastructure developed for NEESPI has been used and improved for MAIRS support.Data search, subsetting, and download functions are available through a single system. A customized Giovanni system has been created for MAIRS.The Web-based on line data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) allows scientists to explore, quickly analyze, and download data easily without learning the original data structure and format. Giovanni MAIRS includes satellite observations from multiple sensors and model output from the NASA Global Land Data Assimilation System (GLDAS), and from the NASA atmospheric reanalysis project, MERRA. Currently, we are working on processing and integrating higher resolution land data in to Giovanni, such as vegetation index, land surface temperature, and active fire at 5km or 1km from the standard MODIS products. For data that are not archived at the GESDISC,a product metadata portal is under development to serve as a gateway for providing product level information and data access links, which include both satellite, model products and ground-based measurements information collected from MAIRS scientists.Due to the large overlap of geographic coverage and many similar scientific interests of NEESPI and MAIRS, these data and tools will serve both projects.

Shen, Suhung↗

MODIS Solar Reflective Calibration Traceability

Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify, measurement uncertainties, and to establish absolute scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for both the Terra and Aqua missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. MODIS RSB on-orbit calibration is reflectance based with reference to the bidirectional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser monitor (SDSM). This paper provides details of this calibration chain, from prelaunch to on-orbit operation, and associated uncertainty assessments. Using MODIS as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.

Xiong, Xiaoxiong↗

Gas Concentration Mapping of Arenal Volcano Using AVEMS

The Airborne Volcanic Emissions Mass Spectrometer (AVEMS) System developed by NASA-Kennedy Space Center and deployed in collaboration with the National Center for Advanced Technology (CENAT) and the University of Costa Rica was used for mapping the volcanic plume of Arenal Volcano, the most active volcano in Costa Rica. The measurements were conducted as part of the second CARTA (Costa Rica Airborne Research and Technology Application) mission conducted in March 2005. The CARTA 2005 mission, involving multiple sensors and agencies, consisted of three different planes collecting data over all of Costa Rica. The WB-57F from NASA collected ground data with a digital camera, an analog photogrametric camera (RC-30), a multispectral scanner (MASTER) and a hyperspectral sensor (HYMAP). The second aircraft, a King Air 200 from DoE, mounted with a LIDAR based instrument, targeted topography mapping and forest density measurements. A smaller third aircraft, a Navajo from Costa Rica, integrated with the AVEMS instrument and designed for real-time measurements of air pollutants from both natural and anthropogenic sources, was flown over the volcanoes. The improved AVEMS system is designed for deployment via aircraft, car or hand-transport. The 85 pound system employs a 200 Da quadrupole mass analyzer, has a volume of 92,000 cubic cm, requires 350 W of power at steady state, can operate up to an altitude of 41,000 feet above sea level (-65 C; 50 torr). The system uses on-board gas bottles on-site calibration and is capable of monitoring and quantifying up to 16 gases simultaneously. The in-situ gas data in this work, consisting of helium, carbon dioxide, sulfur dioxide and acetone, was acquired in conjunction of GPS data which was plotted with the ground imagery, topography and remote sensing data collected by the other instruments, allowing the 3 dimensional visualization of the volcanic plume at Arenal Volcano. The modeling of possible scenarios of Arenal s activity and its direct impact on the surrounding populated areas in now possible with the combined set of data, linking in-situ data with remote sensing data. The study also helps in the understanding of pyroclastic flow behavior in case of a major eruption.

Diaz, J. Andres↗