Search NASA⌕ Search

SEARCH · Search NASA

Results for “monitoring demonstrations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

Spiral-Bevel-Gear Damage Detected Using Decision Fusion Analysis

Helicopter transmission integrity is critical to helicopter safety because helicopters depend on the power train for propulsion, lift, and flight maneuvering. To detect impending transmission failures, the ideal diagnostic tools used in the health-monitoring system would provide real-time health monitoring of the transmission, demonstrate a high level of reliable detection to minimize false alarms, and provide end users with clear information on the health of the system without requiring them to interpret large amounts of sensor data. A diagnostic tool for detecting damage to spiral bevel gears was developed. (Spiral bevel gears are used in helicopter transmissions to transfer power between nonparallel intersecting shafts.) Data fusion was used to integrate two different monitoring technologies, oil debris analysis and vibration, into a health-monitoring system for detecting surface fatigue pitting damage on the gears.

Dempsey, Paula J.↗

Intelligent Engine Systems Work Element 1.3: Sub System Health Management

The objectives of this program were to develop health monitoring systems and physics-based fault detection models for engine sub-systems including the start, lubrication, and fuel. These models will ultimately be used to provide more effective sub-system fault identification and isolation to reduce engine maintenance costs and engine down-time. Additionally, the bearing sub-system health is addressed in this program through identification of sensing requirements, a review of available technologies and a demonstration of a demonstration of a conceptual monitoring system for a differential roller bearing. This report is divided into four sections; one for each of the subtasks. The start system subtask is documented in section 2.0, the oil system is covered in section 3.0, bearing in section 4.0, and the fuel system is presented in section 5.0.

Ashby, Malcolm↗

Monitoring Delamination of Thermal Barrier Coatings by Near-Infrared and Upconversion Luminescence Imaging

Previous work has demonstrated that TBC delamination can be monitored by incorporating a thin luminescent sublayer that produces greatly increased luminescence intensity from delaminated regions of the TBC. Initial efforts utilized visible-wavelength luminescence from either europium or erbium doped sublayers. This approach exhibited good sensitivity to delamination of electron-beam physical-vapor-deposited (EB-PVD) TBCs, but limited sensitivity to delamination of the more highly scattering plasma-sprayed TBCs due to stronger optical scattering and to interference by luminescence from rare-earth impurities. These difficulties have now been overcome by new strategies employing near-infrared (NIR) and upconversion luminescence imaging. NIR luminescence at 1550 nm was produced in an erbium plus ytterbium co-doped yttria-stabilized zirconia (YSZ) luminescent sublayer using 980-nm excitation. Compared to visible-wavelength luminescence, these NIR emission and excitation wavelengths are much more weakly scattered by the TBC and therefore show much improved depth-probing capabilities. In addition, two-photon upconversion luminescence excitation at 980 nm wavelength produces luminescence emission at 562 nm with near-zero fluorescence background and exceptional contrast for delamination indication. The ability to detect TBC delamination produced by Rockwell indentation and by furnace cycling is demonstrated for both EB-PVD and plasma-sprayed TBCs. The relative strengths of the NIR and upconversion luminescence methods for monitoring TBC delamination are discussed.

Eldridge, J. I.↗

Arterial gas emboli in altitude-induced decompression sickness

Exposure to high altitudes can result in the evolved-gas condition referred to as decompression sickness (DCS). Ultrasonic monitoring techniques have clearly demonstrated the presence of venous gas emboli (VGE) during decompression. Although important to DCS research and our understanding of the physiological mechanisms of this condition, Venus gas emboli have not been considered clinically hazardous, unless in extreme numbers. Arterial gas emboli (AGE), on the other hand, are generally viewed with great concern. Arterial gas emboli can enter the cerebral arterial circulation and arrest blood flow resulting in potentially serious injury. Left ventricular gas emboli were observed with echo imaging in five volunteer subjects during exposure to simulated altitude. These serendipitous findings occurred during altitude exposure under 3 separate research protocols involving 79 subject exposures. The voluntary, fully informed consent of the subjects used in this research was obtained as required by AFR 169-3. A Hewlett-Packard SONOS 1000 Echo Imaging System was used to monitor for precordial gas emboli. The improved resolution of the SONOS 1000 appears to account for these new findings. Four subjects had high incidence DCS and VGE during previous research flights. One subject only had one flight. The altitudes and AGE onset times for the five cases were: (1) 25,500 ft/2:23, (2) 29,000 ft/0:27, (3) 19,500 ft/3:49, (4) 29,500 ft/3:15, and (5) 29,500 ft/1:31. In all five cases, at the time of AGE onset, the VGE scores were high from all monitored locations. Four of the cases were symptomatic at the time of AGE onset (pain and skin mottling). No cerebral manifestations were observed. All subjects were immediately recompressed to ground level and successfully treated with 2 hours of post-breathing or with hyperbaric oxygen therapy. In conclusion, previously undetected AGE were demonstrated--with and without DCS symptoms--during exposure to altitude. It appears that this gas transferred from the venous side to the arterial side via either intracardiac defects or the pulmonary circulation. The clinical and operational implications of this finding are yet to be determined.

Pilmanis, Andrew A.↗

Health Monitoring of Composite Overwrapped Pressure Vessels (COPVs) Using Meandering Winding Magnetometer ((MWM(Registered Trademark)) Eddy Current Sensors

There are 3 mechanisms that affect the life of a COPV are: a) The age life of the overwrap; b) Cyclic fatigue of the metallic liner; c) Stress Rupture life. The first two mechanisms are understood through test and analysis. A COPV Stress Rupture is a sudden and catastrophic failure of the overwrap while holding at a stress level below the ultimate strength for an extended time. Currently there is no simple, deterministic method of determining the stress rupture life of a COPV, nor a screening technique to determine if a particular COPV is close to the time of a stress rupture failure. Conclusions: Demonstrated a correlation between MWM response and pressure or strain. Demonstrated the ability to monitor stress in COPV at different orientations and depths. FA41 provides best correlation with bottle pressure or stress.

Russell, Rick↗

Time aspects of the European Complement to GPS: Continental and transatlantic experimental phases

The CNES project of a European Complement to GPS (CE-GPS) is conceived to fulfill the needs of Civil Aviation for a non-precise approach phase with GPS as sole navigation means. This generates two missions: a monitoring mission - alarm of failure - ,and a navigation mission - generating a GPS-like signal on board the geostationary satellites. The host satellites will be the Inmarsat constellation. The CE-GPS missions lead to some time requirements, mainly the accuracy of GPS time restitution and of monitoring clock synchronization. To demonstrate that the requirements of the CE-GPS could be achieved, including the time aspects, an experiment has been scheduled over the Last two years, using a part of the Inmarsat II F-2 payload and specially designed ground stations based on 10 channels GPS receivers. This paper presents a review of the results obtained during the continental phase of the CE-GPS experiment with two stations in France, along with some experimental results obtained during the transatlantic phase (three stations in France, French Guyana, and South Africa). It describes the synchronization of the monitoring clocks using the GPS Common-view or the C- to L-Band transponder of the Inmarsat satellite, with an estimated accuracy better than 10 ns (1 sigma).

Uhrich, Pierre J. M.↗

Thunderstorm detection and warning system atmospheric potential monitor

An new type of electric field instrumentation was developed for lighting prediction at KSC. Currently, it is being installed at several government laboratories and is being made available to the public. It has important advantages over the previous method for measuring electric fields with motor driven field mills: (1) it has no moving parts and requires little maintenance compared to rotating machinery; (2) it is unaffected by rain, snow, sand, or insects, all of which can influence field mills; and (3) the lightweight sensor can be mounted easily on a tall mast. By mounting the instrumentation on a tall mast the instrumentation is placed above much of the blanket of point discharge ions that are emitted from objects on the ground during thunderstorms. This space charge limits the ability of any ground based electric field sensor to accurately measure cloud electric fields which produce lightning. The elevated mounting was demonstrated to significantly improve monitoring of thunderstorm electric fields. This instrumentation measures the atmospheric potential relative to earth at a corona needle sensor on top of a mast which normally is mounted on a tower or roof. The needle is kept in corona at all times by a low power high voltage power supply. This produces a small cloud of ions around the needle allowing a current to flow. Measurement of the current provides the atmospheric potential. The potential divided by the height of the needle above the ground is proportional to the average electric field between the needle and earth. The potential on top of a tall pole or above a rooftop is more representative of the intensity of cloud electrification than electric field measurements made at ground level. Photographs that depict the computer terminal, video display of a two sensor system, and the individual components installed on a tower are presented.

Source record↗

An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

Spruce, Joseph P.↗

Monitoring of Thermal Protection Systems Using Robust Self-Organizing Optical Fiber Sensing Networks

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, and an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during re-entry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry

Structural Health Monitoring↗

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗

Optical surface refurbishment in space environment

The potential use of the vacuum environment of space to clean contaminated mirror surfaces or generate Al mirror surfaces with high reflectance in the 80-200-nm region is discussed and illustrated with diagrams and graphs, reviewing previous studies and current experiment proposals. Consideration is given to (1) applying the atomic oxygen plasma environment of LEO to clean coated mirrors and (2) depositing freshly evaporated Al onto a mirror surface in vacuum, providing relatively long periods of high EUV reflectance before oxidation of the surface degrades performance: such a procedure could be performed as a maintenance measure or even incorporated into the design of a space observatory. A free-flying experiment is described which would produce and maintain an Al surface with controlled exposure to OH, H2O, and O2; demonstrate directed-beam Al deposition onto a simulated telescope/spectrometer surface; monitor instrument reflectance/sensitivity over time; and demonstrate in situ refurbishment of the degraded surface.

Heaney, James B.↗

State modeling and pass automation in spacecraft control

The integrated monitoring and control commercial off-the-shelf system (IMACCS), which demonstrates the feasibility of automating spacecraft monitoring and control activities through the use of state modeling, is described together with its use. The use of the system for the control and ground support of the solar, anomalous and magnetic particle explorer (SAMPEX) spacecraft is considered. A key component of IMACCS is the Altair mission control system which implements finite state modeling as an element of its expert system capability. Using the finite state modeling and state transition capabilities of the Altair mission control system, IMACCS features automated monitoring, routine pass support, anomaly resolution and emergency 'lights on again' response. Automatic orbit determination and the production of typical flight dynamics products exists. These functionalities are described.

Klein, J.↗

Monitoring Phenology as Indicator for Timing of Nutrient Inputs in Northern Gulf Watersheds

Nutrient over-enrichment defined by the U.S. Environmental Protection Agency as the anthropogenic addition of nutrients, in addition to any natural processes, causing adverse effects or impairments to the beneficial uses of a water body has been identified as one of the most significant environmental problems facing sensitive estuaries and coastal waters. Understanding the timing of nutrient inputs into those waters through remote sensing observables helps define monitoring and mitigation strategies. Remotely sensed data products can trace both forcings and effects of the nutrient system from landscape to estuary. This project is focused on extracting nutrient information from the landscape. The timing of nutrients entering coastal waters from the land boundary is greatly influenced by hydrologic processes, but can also be affected by the timing of nutrient additions across the landscape through natural or anthropogenic means. Non-point source nutrient additions to watersheds are often associated with specific seasonal cycles, such as decomposition of organic materials in fall and winter or addition of fertilizers to crop lands in the spring. These seasonal cycles or phenology may in turn be observed through the use of satellite sensors. Characterization of the phenology of various land cover types may be of particular interest in Gulf of Mexico estuarine systems with relatively short pathways between intensively managed systems and the land/estuarine boundary. The objective of this study is to demonstrate the capability of monitoring phenology of specific classes of land, such as agriculture and managed timberlands, at a refined watershed level. The extraction of phenological information from the Moderate Resolution Imaging Spectroradiometer (MODIS) data record is accomplished using analytical tools developed for NASA at Stennis Space Center: the Time Series Product Tool and the Phenological Parameters Estimation Tool. MODIS reflectance data (product MOD09) were used to compute the Normalized Difference Vegetation Index, which is sensitive to changes in vegetation canopies. The project team is working directly with the Mississippi Department of Environmental Quality to understand end-user requirements for this type of information product. Initial focus areas are identification of time frames for pre-plant fertilizer applications (prior to start of season), side-dress fertilizer applications (during rapid green-up), and periods of plant decomposition (during and after senescence). Prototypical maps of phenological stages related to these time frames have been generated for watersheds in the northern Gulf of Mexico. Where feasible, these maps have been compared to existing in situ nutrient monitoring data, but the in situ data is temporally sparse (monthly frequency or less), which makes interpretation challenging. Future work will include integrating effects of rainfall and seeking couplings with estuarine remote sensing.

Ross, Kenton W.↗

Monitoring of Thermal Protection Systems and MMOD using Robust Self-Organizing Optical Fiber Sensing Networks

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.

Fiber Optic Sensors↗

Automated management of power systems

APSM (Automated Power System Management) is a technology readiness program underway to develop, evaluate, and demonstrate various techniques involved in power system monitoring, as well as computational and control functions. The demonstration breadboard consists of the Viking Orbiter '75 power subassembly breadboard modified to incorporate dedicated microprocessors and digital interface circuits, as well as test support equipment for both spacecraft and ground computer simulation, fault simulation, and data acquisition.

Imamura, M. S.↗

Analysis of CO Transport from Australia Fires and Its Impact to Ozone, Water Vapor and Clouds Using CrIS Single-Field-of-View Sounder Products and Other Remote Sensing and MERRA-2 Reanalysis Data

Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles, and the long-range transport of the smoke plumes poses great impact to climate change, such as altering the Antarctic ozone (O3) hole. Spaceborne observations from satellites have been proven successful in monitoring CO from wildfires in the past decade and can be used to examine the associated CO transport. The primary remote sensing data used in this study is the Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from the Cross-track Infrared Sounder (CrIS) on SNPP, a new product that will be generated at NASA and released to the public in a few months. SiFSAP has a high spatial resolution of ~14 km and includes atmospheric profiles of temperature, water vapor, CO, O3, as well as cloud products, and as the SiFSAP algorithm performs both day- and night-time retrievals, it provides an additional observation for night-time in comparison to the day-time-only solar polar satellite instruments such as MOPPIT, OMPS, and TROPOMI. Most recent significant improvements in the quality of this product plus its good spatial resolution (better than most global weather and climate models) enable us to conduct process-oriented analysis of CO transport, and the variation of water vapor, O3 and clouds (optical depth, effective radius and cloud height) within and around the fire plumes. The wind fields from MERRA-2 reanalysis will be used to help characterize the transport. Other remote sensing data, such as CO from AIRS, MOPPIT and TROPOMI, O3 from OMPS and TROPOMI, as well as the UV aerosol index from OMI and OMPS, will be used and compared with SiFSAP sounder products. Cross-validation of CO and O3 from these different sensors with the corresponding MERRA-2 products will also be carried out. Along the plume transport path, some enhancement of O3 and correlation between fire aerosol, cloud optical depth and water vapor have been found but need further investigation. Using the transport of fire plumes over the Southern Pacific Ocean as a unique testbed, this study will demonstrate the trace species monitoring capability of current satellite observations, in particular, for CO and O3, and hopefully, it will provide some insight on the impacts on fire emissions on air quality and climate.

Xiaozhen (Shawn) Xiong↗

An Overview of Spacecraft Aerosols: Sources, Dynamics, and Knowledge Gaps

NASA has prioritized development of airborne particulate monitoring systems and mitigation strategies for future Lunar, Martian, and deep-space exploration missions. Airborne particles, also called aerosols, can cause human health problems ranging from mild respiratory discomfort to more severe disease. NASA’s suspended cabin particle and Lunar dust concentration requirements are motivated by protecting crew health and comfort during spaceflight, especially as mission durations lengthen and become increasingly ground-independent. Spacecraft cabin aerosols can originate from a variety of sources, including skin flakes, fibers from clothes and other materials, mechanical wear from equipment, and personal care products (e.g., antiperspirant). As NASA plans future expeditions to the Moon and Mars, Lunar and planetary dust compose an additional, under-characterized source for airborne particles. In addition to these known sources, recent studies on ISS cabin aerosols also revealed particles with unknown origins and poorly understood formation mechanisms, including some that may be formed by oxidative and/or heterogeneous chemical processes. The aerosol monitors payload, to be launched February 2025, will focus on understanding these unknown sources and processes, as well as demonstrating novel technologies for particulate monitoring to be infused in future space flight programs. In this presentation, we will present our knowledge of spacecraft cabin aerosols to date, summarizing aerosol measurement experiments from Shuttle through ISS. Cabin aerosol sources, known and unknown, will be summarized, and knowledge gaps for future long-duration space exploration missions will be discussed.

Claire Fortenberry↗