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At least 721 records · Page 40

A distributed data acquisition system for aeronautics test facilities

The NASA Lewis Research Center is in the process of installing a new data acquisition and display system. This new system will provide small and medium sized aeronautics test facilities with a state-of-the-art real-time data acquisition and display system. The new data system will provide for the acquisition of signals from a variety of instrumentation sources. They include analog measurements of temperatures, pressures, and other steady state voltage inputs; frequency inputs to measure speed and flow; discrete I/O for significant events, and modular instrument systems such as multiplexed pressure modules or electronic instrumentation with a IEEE 488 interface. The data system is designed to acquire data, convert it to engineering units, compute test dependent performance calculations, limit check selected channels or calculations, and display the information in alphanumeric or graphical form with a cycle time of one second for the alphanumeric data. This paper describes the system configuration, its salient features, and the expected impact on testing.

Fronek, Dennis L.↗

A distributed data acquisition system for aeronautics test facilities

The NASA Lewis Research Center is in the process of installing a new data acquisition and display system. This new system will provide small and medium sized aeronautics test facilities with a state-of-the-art real-time data acquisition and display system. The new data system will provide for the acquisition of signals from a variety of instrumentation sources. They include analog measurements of temperatures, pressures, and other steady state voltage inputs; frequency inputs to measure speed and flow; discrete I/O for significant events, and modular instrument systems such as multiplexed pressure modules or electronic instrumentation with a IEEE 488 interface. The data system is designed to acquire data, convert it to engineering units, compute test dependent performance calculations, limit check selected channels or calculations, and display the information in alphanumeric or graphical form with a cycle time of one second for the alphanumeric data. This paper describes the system configuration, its salient features, and the expected impact on testing.

Fronek, Dennis L.↗

Data Driven Online Learning of Power System Dynamics

With the advancement of sensing and communication in power networks, high-frequency real-time data from a power network can be used as a resource to develop better monitoring capabilities. In this work, a systematic approach based on data-driven operator theoretic methods involving Koopman operator is proposed for the online identification of power system dynamics. In particular, a new algorithm is provided, which unlike any previously existing algorithms, updates the Koopman operator iteratively as new data points are acquired. The proposed algorithm has three advantages: a) allows for real-time monitoring of the power system dynamics b) linear power system dynamics (this linear system is usually in a higher dimensional feature space and is not same as linearization of the underlying nonlinear dynamics) and c) computationally fast and less intensive when compared to the popular Extended Dynamic Mode Decomposition (EDMD) algorithm. The efficiency of the proposed algorithm is illustrated on an IEEE 9 bus system using synthetic data from the nonlinear model and on IEEE 39 bus system using synthetic data from the linearized model.

Sinha, Subhrajit↗

On-chip learning of hyper-spectral data for real time target recognition

As the focus of our present paper, we have used the cascade error projection (CEP) learning algorithm (shown to be hardware-implementable) with on-chip learning (OCL) scheme to obtain three orders of magnitude speed-up in target recognition compared to software-based learning schemes. Thus, it is shown, real time learning as well as data processing for target recognition can be achieved.

on-chip learning Cascade Error Projection real tim↗

Hydra: An AI-Based Framework for Interpretable and Portable Data Quality Monitoring

Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7 during experiments. Generally, these sets of images are produced at a rate and quantity that is exceedingly difficult for shift crews to effectively monitor. Significant effort has been devoted to enhancing Hydra’s user interface, to ensure that it provides clear, actionable insights for shift workers and other users. Gradient Weighted Class Activation Maps (GradCAM) provide added interpretability, allowing users to visualize important regions of the image for classification. Hydra has been containerized to enable the creation of portable demos and seamless integration with container-based technologies such as Kubernetes and Docker. With the user interface enhancements and containerization, Hydra can be rapidly deployed for new use cases and experiments. This talk will describe the Hydra framework, its user interface and experience, and the challenges inherent in its design and deployment.

Britton, Thomas [Thomas Jefferson National Acceler↗

High-Temperature Cyclic Oxidation Data, Volume 1

This first in a series of cyclic oxidation handbooks contains specific-weight-change-versus-time data and X-ray diffraction results derived from high-temperature cyclic tests on high-temperature, high-strength nickel-base gamma/gamma' and cobalt-base turbine alloys. Each page of data summarizes a complete test on a given alloy sample.

Barrett, C. A.↗

Improving the Accuracy of Clustering Electric Utility Net Load Data using Dynamic Time Warping

Identifying patterns in electric utility net load data in a time-series format is very useful in preparing the operation for next day. Machine learning algorithms have been used in other domains and those concepts are applied in this paper on real-world net load measurement data. Clustering is the practice of grouping data with similar characteristics as determined by the distance measure. The K-means clustering algorithm is utilized here with actual electric utility data. The paper uses the standard distance measure, Euclidean distance (ED), and compares its performance against the dynamic time warping (DTW) measure. An actual case study with real data is presented, and DTW distance measure-based method observed to result better accuracy compared to the ED based method for substation net load measurements predominantly with residential customers.

clustering↗

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

Early Warning Signs of a Mental Health Tsunami: A Coordinated Response to Gather Initial Data Insights From Multiple Digital Services Providers

The immediate impact of coronavirus 2019 (COVID-19) on morbidity and mortality has raised the need for accurate and real-time data monitoring and communication. The aim of this study is to document the initial observations from multiple digital services providers during the COVID-19 crisis, especially those related to mental health and well-being. We used email and social media to announce an urgent call for support. Digital mental health services providers (N = 46), financial services providers (N = 4), and other relevant digital data source providers (N = 3) responded with quantitative and/or qualitative data insights. People with lived experience of distress, as service users/consumers, and carers are included as co-authors. This study provides proof-of-concept of the viability for researchers and private companies to work collaboratively toward a common good. Digital services providers reported a diverse range of mental health concerns. A recurring observation is that demand for digital mental health support has risen, and that the nature of this demand has also changed since COVID-19, with an apparent increased presentation of anxiety and loneliness. Following this study, we will continue to work with providers in more in-depth ways to capture follow-up insights at regular time points. We will also onboard new providers to address data representativeness. Looking ahead, we anticipate the need for a rigorous process to interpret insights from an even wider variety of sources in order to monitor and respond to mental health needs.

60 APPLIED LIFE SCIENCES↗

Universal approach to analysis of cavitation and liquid-impingement erosion data

Cavitation erosion experimental data was analyzed by using normalization and curve-fitting techniques. Data were taken from experiments on several materials tested in both a rotating disk device and a magnetostriction apparatus. Cumulative average volume loss rate and time data were normalized relative to the peak erosion rate and the time to peak erosion rate, respectively. From this process a universal approach was derived that can include data on specific materials from different test devices for liquid impingement and cavitation erosion studies.

Rao, P. V.↗

Low Cost Coherent Doppler Lidar Data Acquisition and Processing

The work described in this paper details the development of a low-cost, short-development time data acquisition and processing system for a coherent Doppler lidar. This was done using common laboratory equipment and a small software investment. This system provides near real-time wind profile measurements. Coding flexibility created a very useful test bed for new techniques.

Barnes, Bruce W.↗

Composition measurements of the topside ionosphere using a magnetic mass spectrometer, ion mass spectrometer on ISIS-2 spacecraft

The ion mass spectrometer (IMS) on the ISIS-II satellite is described; it measures the composition and distribution of positive ions in the earth's ionosphere in the mass range of 1 to 64 atomic mass units. Significant data were received which show a wide variation in ion composition at night near the equator and in the daytime poleward of the plasmapause. It was found that these data enable further study of the polar wind and that the experiment produced timely data during the August, 1972 magnetic storm to show the development of a unique ionosphere above the plasmapause during the period of the storm. The scientific objectives and results of the experiment, the technical description of the instrument, a bibliography with sample papers attached, and a summary of recommendations for further study are presented.

Hoffman, J. H.↗

Space Borne Event Timer

The Space Borne Event Timer is a part of the NASA laser ranging system that is intended to operate aboard the Space Shuttle orbiting over California. The object is to measure, by laser ranging, the earth movement along the San Andreas fault and possibly forecast future earthquakes. A number of cube reflector targets will be placed along both sides of the fault. The ranging system aboard the Space Shuttle will fire a burst of laser pulses at each target and detect the reflected light. Time differences between pulses from the two sides of the fault will indicate earth displacements. The Space Borne Event Timer is a CAMAC compatible system that provides extremely accurate timing data and controls the operation of the ranging system. For each event the time is given in 19.53 increments from the instant of firing the laser to the instant the reflected light is received back, within a range of 130 days.

Turko, B.↗

Magellan SAR processing algorithm and H/W design

The SAR (synthetic-aperture radar) data-processing algorithm to be used for the Magellan mission is described. Radar system design, SAR data characteristics, and hardware (H/W) constraints, which are critical to the processing algorithm design, are highlighted. Data flow and the H/W architecture are given to show the real-time data processing capability. Simulation results obtained from processing the synthetic point-target echos are presented to demonstrate the performance of the processing algorithm.

Chen, M.↗

Microgravity Environment on the International Space Station

A primary feature of the International Space Station will be its microgravity environment--an environment in which the effects of gravity are drastically reduced. The International Space Station design has been driven by a long-standing, high-level requirement for a microgravity mode of operation. Various types of data are gathered when science experiments are conducted. The acceleration levels experienced during experiment operation should be factored into the analysis of the results of most microgravity experiments. To this end, the Space Acceleration Measurement System records the acceleration levels to support microgravity researchers for nearly three years of International Space Station operations. The Principal Investigator Microgravity Services project assists the experiments principal investigators with their analysis of the acceleration (microgravity) environment. The Principal Investigator Microgravity Services project provides cataloged data, periodic analysis summary reports, specialized reports for experiment teams, and real-time data in a variety of user-defined formats. Characterization of the various microgravity carriers (e.g., Shuttle and International Space Station) is also accomplished for the experiment teams. Presented in this paper will be a short description of how microgravity disturbances may affect some experiment classes, a snapshot of the microgravity environment, and a view into how well the space station is expected to meet the user requirements.

DeLombard, Richard↗

IMU/GPS System Provides Position and Attitude Data

A special navigation system is being developed to provide high-quality information on the position and attitude of a moving platform (an aircraft or spacecraft), for use in pointing and stabilization of a hyperspectral remote-sensing system carried aboard the platform. The system also serves to enable synchronization and interpretation of readouts of all onboard sensors. The heart of the system is a commercially available unit, small enough to be held in one hand, that contains an integral combination of an inertial measurement unit (IMU) of the microelectromechanical systems (MEMS) type, Global Positioning System (GPS) receivers, a differential GPS subsystem, and ancillary data-processing subsystems. The system utilizes GPS carrier-phase measurements to generate time data plus highly accurate and continuous data on the position, attitude, rotation, and acceleration of the platform. Relative to prior navigation systems based on IMU and GPS subsystems, this system is smaller, is less expensive, and performs better. Optionally, the system can easily be connected to a laptop computer for demonstration and evaluation. In addition to airborne and spaceborne remote-sensing applications, there are numerous potential terrestrial sensing, measurement, and navigation applications in diverse endeavors that include forestry, environmental monitoring, agriculture, mining, and robotics.

Lin, Ching Fang↗

Revalidation of the Volatile Organic Analyzer Following a Major On-Orbit Maintenance Activity

The Volatile Organic Analyzer (VOA) contributes to the assessment of air quality aboard the International Space Station (ISS) by identifying and quantifying target airborne volatile organic contaminants in the module air. This on-orbit contaminant monitoring capability becomes particularly important during an air quality degradation event such as a system leak. During several ISS air quality degradations, the VOA has generated near real-time data that was used to make decisions or to better understand the contingency. The VOA was operational from January 2002 through June 2003, during which time it was validated by comparing VOA data to simultaneously acquired grab sample containers (GSCs). In January 2003, one of the two analytical channels of the VOA was shutdown because of a component failure, but a redundant channel continued to supply the necessary analytical data. In June 2003, the sole remaining channel was deactivated. Initial assessments of the channel shutdowns pointed to failed fuses or heaters, but neither was considered repairable on orbit. In 2005, it was determined that failed fuses could be replaced on orbit and the crew conducted a diagnostic procedure to identify the failed component. The crew discovered that both channels incurred failed fuses, which lead to a subsequent on orbit maintenance activity and return of the VOA to operational status in December 2005. The VOA has been providing data on the ISS atmosphere since its reactivation in 2005 and this paper will present the VOA data collected during 2006. Special emphasis will be placed upon the revalidation of the repaired VOA using GSCs as well as a summary of the diagnostic and repair procedures.

Limero, Thomas↗