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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 127 records · Page 7

Detecting Faults In Helicopter Gearboxes By The MVIM Method

Multivalued influence-matrix (MVIM) method potential utility as theoretical basis of proposed automated monitoring systems detecting faults in helicopter gearboxes. Applied to recognize patterns in vibration measurements. Fault-recognition system required to operate continuously while helicopter airborne, analyzing measurements of vibrations for signs of trouble to provide real-time warning of any dangerous or potentially dangerous fault like cracked case or fractured gear tooth. System also required not to give false alarms to prevent unnecessary emergency landings.

Chin, Hsinyung↗

Optoelectronic Particle-Fallout Sensor

Portable optoelectronic system monitors fallout of small particles (dust and fibers) onto surface at given location during extended time. Data on accumulated fallout downloaded from system to computer for display and analysis. Typical display is plot of signal proportional to amount of accumulated fallout as function of time and read to determine when contamination occurs. In many cases, possible to establish correlations between accumulations of particles and activities in vicinity. Also capable of signaling alarm in event contamination by fallout exceeds specified level. System made very inexpensively and used to monitor accumulation of dust and fibers associated with motion of air in variety of environments. Phenomena monitored indirectly by use of system might include circulation of air in buildings, and human and animal activity. Also serves as auxiliary intrusion monitor (though probably not real-time alarm) in sealed room because motion of intruder inevitably stirs up some dust.

Ihlefeld, Curtis↗

ISHM Decision Analysis Tool: Operations Concept

The state-of-the-practice Shuttle caution and warning system warns the crew of conditions that may create a hazard to orbiter operations and/or crew. Depending on the severity of the alarm, the crew is alerted with a combination of sirens, tones, annunciator lights, or fault messages. The combination of anomalies (and hence alarms) indicates the problem. Even with much training, determining what problem a particular combination represents is not trivial. In many situations, an automated diagnosis system can help the crew more easily determine an underlying root cause. Due to limitations of diagnosis systems,however, it is not always possible to explain a set of alarms with a single root cause. Rather, the system generates a set of hypotheses that the crew can select from. The ISHM Decision Analysis Tool (IDAT) assists with this task. It presents the crew relevant information that could help them resolve the ambiguity of multiple root causes and determine a method for mitigating the problem. IDAT follows graphical user interface design guidelines and incorporates a decision analysis system. I describe both of these aspects.

Source record↗

Fire protection for launch facilities using machine vision fire detection

Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.

Schwartz, Douglas B.↗

Self-contained breathing apparatus

A self-contained breathing apparatus with automatic redundant fluid pressure controls and a facemask mounted low pressure whistle alarm is described. The first stage of the system includes pair of pressure regulators connected in parallel with different outlet pressures, both of which reduce the pressure of the stored supply gas to pressures compatible with the second stage breathing demand regulator. A primary regulator in the first stage delivers a low output pressure to the demand regulator. In the event of a failure closed condition of the primary regulator an automatic transfer valve switches on the backup regulator. A warning that the supply pressure has been depleted is also provided by a supply pressure actuated transfer valve which transfers the output of the first stage pressure regulators from the primary to the backup regulator. The alarm is activated in either the failure closed condition or if the supply pressure is reduced to a dangerously low level.

Sullivan, J. L.↗

Knowledge acquisition and interface design for learning on demand systems

The rapid changes in our world precipitated by technology have created new problems and new challenges for education and training. A knowledge 'explosion' is occurring as our society moves toward a service oriented economy that relies on information as the major resource. Complex computer systems are beginning to dominate the workplace, causing alarming growth and change in many fields. The rapidly changing nature of the workplace, especially in fields related to information technology, requires that our knowledge be updated constantly. This characteristic of modern society poses seemingly unsolvable instructional problems involving coverage and obsolescence. The sheer amount of information to be learned is rapidly increasing, while at the same time some information becomes obsolete in light of new information. Education, therefore, must become a lifelong process that features learning of new material and skills as needed in relation to the job to be done. Because of the problems cited above, the current model of learning in advance may no longer be feasible in our high-technology world. In many cases, learning in advance is impossible because there are simply too many things to learn. In addition, learning in advance can be time consuming, and often results in decontextualized knowledge that does not readily transfer to the work environment. The large and growing discrepancy between the amount of potentially relevant knowledge available and the amount a person can know and remember makes learning on demand an important alternative to current instructional practices. Learning on demand takes place whenever an individual must learn something new in order to perform a task or make a decision. Learning on demand is a promising approach for addressing the problems of coverage and obsolescence because learning is contextualized and integrated into the task environment rather than being relegated to a separate phase that precedes work. Learning on demand allows learners to see for themselves the usefulness of new knowledge for actual problem situations, thereby increasing the motivation for learning new information. Finally, learning on demand makes new information relevant to the task at hand, leading to more informed decision making, better quality products, and improved performance.

Nelson, Wayne A.↗

Principal Components Analysis of Triaxial Vibration Data From Helicopter Transmissions

Research on the nature of the vibration data collected from helicopter transmissions during flight experiments has led to several crucial observations believed to be responsible for the high rates of false alarms and missed detections in aircraft vibration monitoring systems. This work focuses on one such finding, namely, the need to consider additional sources of information about system vibrations. In this light, helicopter transmission vibration data, collected using triaxial accelerometers, were explored in three different directions, analyzed for content, and then combined using Principal Components Analysis (PCA) to analyze changes in directionality. In this paper, the PCA transformation is applied to 176 test conditions/data sets collected from an OH58C helicopter to derive the overall experiment-wide covariance matrix and its principal eigenvectors. The experiment-wide eigenvectors. are then projected onto the individual test conditions to evaluate changes and similarities in their directionality based on the various experimental factors. The paper will present the foundations of the proposed approach, addressing the question of whether experiment-wide eigenvectors accurately model the vibration modes in individual test conditions. The results will further determine the value of using directionality and triaxial accelerometers for vibration monitoring and anomaly detection.

Tumer, Irem Y.↗

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.↗

Time Analyzer for Time Synchronization and Monitor of the Deep Space Network

A software package has been developed to measure, monitor, and archive the performance of timing signals distributed in the NASA Deep Space Network. Timing signals are generated from a central master clock and distributed to over 100 users at distances up to 30 kilometers. The time offset due to internal distribution delays and time jitter with respect to the central master clock are critical for successful spacecraft navigation, radio science, and very long baseline interferometry (VLBI) applications. The instrument controller and operator interface software is written in LabView and runs on the Linux operating system. The software controls a commercial multiplexer to switch 120 separate timing signals to measure offset and jitter with a time-interval counter referenced to the master clock. The offset of each channel is displayed in histogram form, and "out of specification" alarms are sent to a central complex monitor and control system. At any time, the measurement cycle of 120 signals can be interrupted for diagnostic tests on an individual channel. The instrument also routinely monitors and archives the long-term stability of all frequency standards or any other 1-pps source compared against the master clock. All data is stored and made available for

Cole, Steven↗

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

lightning jump↗

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection↗

Likelihood alarm displays

In a likelihood alarm display (LAD) information about event likelihood is computed by an automated monitoring system and encoded into an alerting signal for the human operator. Operator performance within a dual-task paradigm was evaluated with two LADs: a color-coded visual alarm and a linguistically coded synthetic speech alarm. The operator's primary task was one of tracking; the secondary task was to monitor a four-element numerical display and determine whether the data arose from a 'signal' or 'no-signal' condition. A simulated 'intelligent' monitoring system alerted the operator to the likelihood of a signal. The results indicated that (1) automated monitoring systems can improve performance on primary and secondary tasks; (2) LADs can improve the allocation of attention among tasks and provide information integrated into operator decisions; and (3) LADs do not necessarily add to the operator's attentional load.

Sorkin, Robert D.↗

Inferring Gear Damage from Oil-Debris and Vibration Data

A system for real-time detection of surface-fatigue-pitting damage to gears for use in a helicopter transmission is based on fuzzy-logic used to fuse data from sensors that measure oil-borne debris, referred to as "oil debris" in the article, and vibration signatures. A system to detect helicopter-transmission gear damage is beneficial because the power train of a helicopter is essential for propulsion, lift, and maneuvering, hence, the integrity of the transmission is critical to helicopter safety. To enable detection of an impending transmission failure, an ideal diagnostic system should provide real-time monitoring of the "health" of the transmission, be capable of a high level of reliable detection (with minimization of false alarms), and provide human users with clear information on the health of the system without making it necessary for them to interpret large amounts of sensor data.

Dempsey, Paula↗

Proposed fast-response oxygen monitoring and control system for the Langley 8-foot high-temperature tunnel

A fast-response oxygen monitoring and control system, based on a Y2O3-stabilized ZrO2 sensor, was developed and tested in the laboratory. The system is capable of maintaining oxygen concentration in the CH4-O2-air combustion product gases at 20.9 + or - 1.0 percent. If the oxygen concentration in the exhaust stream differs from that in normal air by 25 percent or more, an alarm signal is provided for automatic tunnel shutdown. The overall prototype system response time was reduced from about 1 sec in the original configuration to about 0.2 sec. The basis of operation and the results of laboratory tests of the system are described.

Singh, J. J.↗

An Overview of ANN Application in the Power Industry

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

artificial neural networks ANN electric power syst↗

Biomedical technology transfer. Applications of NASA science and technology

Ongoing projects described address: (1) intracranial pressure monitoring; (2) versatile portable speech prosthesis; (3) cardiovascular magnetic measurements; (4) improved EMG biotelemetry for pediatrics; (5) ultrasonic kidney stone disintegration; (6) pediatric roentgen densitometry; (7) X-ray spatial frequency multiplexing; (8) mechanical impedance determination of bone strength; (9) visual-to-tactile mobility aid for the blind; (10) Purkinje image eyetracker and stabilized photocoalqulator; (11) neurological applications of NASA-SRI eyetracker; (12) ICU synthesized speech alarm; (13) NANOPHOR: microelectrophoresis instrument; (14) WRISTCOM: tactile communication system for the deaf-blind; (15) medical applications of NASA liquid-circulating garments; and (16) hip prosthesis with biotelemetry. Potential transfer projects include a person-portable versatile speech prosthesis, a critical care transport sytem, a clinical information system for cardiology, a programmable biofeedback orthosis for scoliosis a pediatric long-bone reconstruction, and spinal immobilization apparatus.

Harrison, D. C.↗

Search strategy effects on PN acquisition performance

The present paper focusses on 'random' and 'expanding window' PN acquisition search strategies and analytically develops the PN acquisition time statistics as functions of salient system parameters such as prediction SNR, detection and false alarm probabilities and a priori information on epoch location. The significance of this analysis is its general applicability to arbitrary postdetection processing schemes. Computed performance results account for the above salient parameters, wherein sequential detection is employed in conjunction with random and selected expanding window search strategies.

Weinberg, A.↗

Fuel Cell Power Plant Initiative: Solid Oxide Fuel Cell/Logistics Fuel Processor 27 kWe Power System Demonstration for ARPA - Volume 1

This report describes the successful testing of a 27 kWe Solid Oxide Fuel Cell (SOFC) generator fueled by natural gas and/or a fuel gas produced by a brassboard logistics fuel preprocessor (LFP). The test period began on May 24, 1995 and ended on February 26, 1996 with the successful completion of all program requirements and objectives. During this time period, this power system produced 118.2 MWh of electric power. No degradation of the generator's performance was measured after 5582 accumulated hours of operation on these fuels: local natural gas - 3261 hours, jet fuel reformate gas - 766 hours, and diesel fuel reformate gas - 1555 hours. This SOFC generator was thermally cycled from full operating temperature to room temperature and back to operating temperature six times, because of failures of support system components and the occasional loss of test site power, without measurable cell degradation. Numerous outages of the LFP did not interrupt the generator's operation because the fuel control system quickly switched to local natural gas when an alarm indicated that the LFP reformate fuel supply had been interrupted. The report presents the measured electrical performance of the generator on all three fuel types and notes the small differences due to fuel type. Operational difficulties due to component failures are well documented even though they did not affect the overall excellent performance of this SOFC power generator. The final two appendices describe in detail the LFP design and the operating history of the tested brassboard LFP.

Veyo, S.E.↗