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Results for “Real-time monitoring”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1970

A computer-controlled scintiscanning system and associated computer graphic techniques for study of regional distribution of blood flow.

Two methods whereby a digital computer may be used to regulate a scintiscanning process are discussed from the viewpoint of computer input-output software. The computer's function, in this case, is to govern the data acquisition and storage, and to display the results to the investigator in a meaningful manner, both during and subsequent to the scanning process. Several methods (such as three-dimensional maps, contour plots, and wall-reflection maps) have been developed by means of which the computer can graphically display the data on-line, for real-time monitoring purposes, during the scanning procedure and subsequently for detailed analysis of the data obtained. A computer-governed method for converting scintiscan data recorded over the dorsal or ventral surfaces of the thorax into fractions of pulmonary blood flow traversing the right and left lungs is presented.

Coulam, C. M.↗
NASA NTRS2009

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.

Satellites↗
NASA NTRS2012

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery

Space Propulsion↗
NASA NTRS1972

The University of Wisconsin OAO operating system

The Wisconsin OAO operating system is presented which consists of two parts: a computer program called HARUSPEX, which makes possible reasonably efficient and convenient operation of the package and ground operations equipment which provides real-time status monitoring, commanding and a quick-look at the data.

Heacox, H. C.↗
NASA NTRS1972

Solar flare predictions and warnings

The real-time solar monitoring information supplied to support SPARCS equipped rocket launches, the routine collection and analysis of 3.3-mm solar radio maps, short-term flare forecasts based on these maps, longer-term forecasts based on the recurrence of active regions, and an extension of the flare forecasting technique are summarized. Forecasts for expectation of a solar flare of class or = 2F are given and compared with observed flares. A total of 52 plage regions produced all the flares of class or = 1N during the study period. The following results are indicated: of the total of 21 positive forecasts, 3 were correct and 18 were incorrect; of the total of 31 negative forecasts, 3 were incorrect and 28 were correct; of a total of 6 plage regions producing large flares, 3 were correctly forecast and 3 were missed; and of 46 regions not producing any large flares, 18 were incorrectly forecast and 28 were correctly forecast.

White, K. P., III↗
NASA NTRS1972

Mechanical systems readiness assessment and performance monitoring study

The problem of mechanical devices which lack the real-time readiness assessment and performance monitoring capability required for future space missions is studied. The results of a test program to establish the feasibility of implementing structure borne acoustics, a nondestructive test technique, are described. The program included the monitoring of operational acoustic signatures of five separate mechanical components, each possessing distinct sound characteristics. Acoustic signatures were established for normal operation of each component. Critical failure modes were then inserted into the test components, and faulted acoustic signatures obtained. Predominant features of the sound signature were related back to operational events occurring within the components both for normal and failure mode operations. All of these steps can be automated. The structure borne acoustics technique lends itself to reducing checkout time, simplifying maintenance procedures, and reducing manual involvement in the checkout, operation, maintenance, and fault diagnosis of mechanical systems.

Source record↗
NASA NTRS2026

The Future of in-Situ Sequencing-Based Microbial Monitoring: Development of a Shelf-Stable Method for Artemis and Beyond

Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.

Christian G Mena↗
NASA NTRS1970

Holographic analysis of thin films

Technique for monitoring deposition of films on surfaces, in place on a real-time basis, reads both the thickness and the uniformity of the deposited film. Holograms are produced from both reflected and transmitted light on one plate.

Norden, B. N.↗
NASA NTRS1972

An all-sky X-ray monitor for the UK-5 satellite.

An X-ray imaging system using a pin-hole camera and a position sensitive proportional counter at the image plane has been designed for an all-sky X-ray monitor for UK-5 satellite. This high-sensitivity device with real-time coverage of the entire celestial sphere would aid in programming satellite maneuvers such that transient events in the X-ray sky could be investigated in detail by the other primary satellite experiments. Discussion of design criteria for the camera geometry, the position sensitive proportional detector, and electronics to handle the data is presented in this paper.

Desai, U. D.↗
NASA NTRS1973

Monitoring California's forage resource using ERTS-1 and supporting aircraft data

NASA's Earth Resource Technology Satellite (ERTS-1) launched July 23, 1972, offers for the first time the unique capabilities for regional monitoring of forage plant conditions. The repetitive coverage every 18 days, the synoptic view and the real-time recovery of the imagery for immediate analysis, combine to make the ERTS satellite a valuable tool for improving the evaluation of our rangeland resources. Studies presently underway at the University of California, Berkeley (sponsored jointly by NASA and the Bureau of Land Management), seek to determine if imagery obtained from high altitude aircraft and spacecraft (ERTS) can provide: (1) a means for monitoring the growth and development of annual and perennial range plants in California, and for determining the time and the rate of initial plant growth (germination) and terminal plant growth (maturation and senescence); (2) a means for determining or predicting the relative amount of forage that is produced; and (3) a means for mapping rangeland areas having different forage producing capabilities.

Carneggie, D. M.↗
NASA NTRS1972

Mapping an operator's perception of a parameter space

Operators monitored the output of two versions of the crossover model having a common random input. Their task was to make discrete, real-time adjustments of the parameters k and tau of one of the models to make its output time history converge to that of the other, fixed model. A plot was obtained of the direction of parameter change as a function of position in the (tau, k) parameter space relative to the nominal value. The plot has a great deal of structure and serves as one form of representation of the operator's perception of the parameter space.

Pew, R. W.↗
NASA NTRS1971

Apollo 15 Mission Report

A detailed discussion is presented of the Apollo 15 mission, which conducted exploration of the moon over longer periods, greater ranges, and with more instruments of scientific data acquisition than previous missions. The topics include trajectory, lunar surface science, inflight science and photography, command and service module performance, lunar module performance, lunar surface operational equipment, pilot's report, biomedical evaluation, mission support performance, assessment of mission objectives, launch phase summary, anomaly summary, and vehicle and equipment descriptions. The capability of transporting larger payloads and extending time on the moon were demonstrated. The ground-controlled TV camera allowed greater real-time participation by earth-bound personnel. The crew operated more as scientists and relied more on ground support team for systems monitoring. The modified pressure garment and portable life support system provided better mobility and extended EVA time. The lunar roving vehicle and the lunar communications relay unit were also demonstrated.

Source record↗
NASA NTRS1972

Data processing at the University of Kansas

Two systems for processing remotely sensed image data have been discussed. The first system, IDECS, is a near real-time hardware system oriented towards processing multi-image data sets quickly and economically. The IDECS has convenient film input and color display output capabilities and implements simple kinds of decision rules. The second system, KANDIDATS, is a software system capable of performing many of the more sophisticated processing methods. Because of its monitor which handles all bookkeeping and its modular design, KANDIDATS easily allows the testing of new automatic processing techniques. After a new technique has been proven on KANDIDATS, it may be simplified and hard-wired in IDECS, thereby keeping the volume processing of remotely sensed data always up to the current state-of-the-art.

Haralick, R. M.↗
NASA NTRS1991

SHARP: Automated monitoring of spacecraft health and status

Briefly discussed here are the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory (JPL). Some of the difficulties associated with the existing technology used in mission operations are highlighted. A new automated system based on artificial intelligence technology is described which seeks to overcome many of these limitations. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multi-mission spacecraft and ground data systems operations. The system has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Telecommunications link analysis of the Voyager 2 spacecraft was the initial focus for evaluation of the system in real-time operations during the Voyager spacecraft encounter with Neptune in August 1989.

Atkinson, David J.↗
NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗