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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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The IGS has successfully produced precise GPS and GLONASS transmitter parameters, coordinates of IGS tracking stations, Earth rotation parameters, and atmospheric parameters. In this paper we discuss the concepts of integrity monitoring, system monitoring, and performance assessment, all in the context of IGS products. We report on a recent survey of IGS product users, and propose an integrity strategy for the IGS.
NASA Dryden presents an improved and automated site-specific algorithm for heat-stress approximation using standard atmospheric measurements routinely obtained from the Edwards Air Force Base weather detachment. Heat stress, which is the net heat load a worker may be exposed to, is officially measured using a thermal-environment monitoring system to calculate the wet-bulb globe temperature (WBGT). This instrument uses three independent thermometers to measure wet-bulb, dry-bulb, and the black-globe temperatures. By using these improvements, a more realistic WBGT estimation value can now be produced. This is extremely useful for researchers and other employees who are working on outdoor projects that are distant from the areas that the Web system monitors. Most importantly, the improved WBGT estimations will make outdoor work sites safer by reducing the likelihood of heat stress.
—Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today’s synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems.
System monitors expired breath patterns simultaneously from four small animals after they have been injected with carbon-14 substrates. It has revealed significant quantitative differences in oxidation patterns of glucose following such mild treatments of rats as a change in diet or environment.
The control monitor unit (CMU) uses configurable software technology for real-time mission command and control, telemetry processing, simulation, data acquisition, data archiving, and ground operations automation. The base technology is currently planned for the following control and monitor systems: portable Space Station checkout systems; ecological life support systems; Space Station logistics carrier system; and the ground system of the Delta Clipper (SX-2) in the Single-Stage Rocket Technology program. The CMU makes extensive use of commercial technology to increase capability and reduce development and life-cycle costs. The concepts and technology are being developed by McDonnell Douglas Space and Defense Systems for the Real-Time Systems Laboratory at NASA's Kennedy Space Center under the Payload Ground Operations Contract. A second function of the Real-Time Systems Laboratory is development and utilization of advanced software development practices.
An autonomous monitoring system for monitoring for bioagents. A collector gathers the air, water, soil, or substance being monitored. A sample preparation means for preparing a sample is operatively connected to the collector. A detector for detecting the bioagents in the sample is operatively connected to the sample preparation means. One embodiment of the present invention includes confirmation means for confirming the bioagents in the sample.
Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.
System continuously monitors radio transmissions stored in memory. If spectrum deviates beyond present limits, alarm is tripped and spectrum is transferred to long-term storage for later analysis. Monitor can be useful in ensuring proper power level and spectral quality and in finding cause of failure. It might also be used to monitor radio-frequency interference or power levels of citizen's-band transmitters.
This research project is designed to apply artificial intelligence technology including expert systems, dynamic interface of neural networks, and hypertext to construct an expert system developer. The developer environment is specifically suited to building expert systems which monitor the performance of ground support equipment for propulsion systems and testing facilities. The expert system developer, through the use of a graphics interface and a rule network, will be transparent to the user during rule constructing and data scanning of the knowledge base. The project will result in a software system that allows its user to build specific monitoring type expert systems which monitor various equipments used for propulsion systems or ground testing facilities and accrues system performance information in a dynamic knowledge base.
A computer-based monitoring system and monitoring method implemented in computer software for detecting, estimating, and reporting the condition states, their changes, and anomalies for many assets. The assets are of same type, are operated over a period of time, and outfitted with data collection systems. The proposed monitoring method accounts for variability of working conditions for each asset by using regression model that characterizes asset performance. The assets are of the same type but not identical. The proposed monitoring method accounts for asset-to-asset variability; it also accounts for drifts and trends in the asset condition and data. The proposed monitoring system can perform distributed processing of massive amounts of historical data without discarding any useful information where moving all the asset data into one central computing system might be infeasible. The overall processing is includes distributed preprocessing data records from each asset to produce compressed data.
The design and the prototype for the expert system for the Hubble Space Telescope's electrical power system are discussed. This prototype demonstrated the capability to use real time data from a 32k telemetry stream and to perform operational health and safety status monitoring, detect trends such as battery degradation, and detect anomalies such as solar array failures. This prototype, along with the pointing control system and data management system expert systems, forms the initial Telemetry Analysis for Lockheed Operated Spacecraft (TALOS) capability.
This report presents the work completed under the DOE iM4 project for the development of a methane emission monitoring system for detection, location, and quantification of methane in oil and gas industries. The task was divided into four main areas including: 1) Sensors and Input, 2) Centralized Cloud Information Center, 3) Algorithms, and 4) Testing and Validation. Task 1 focused on researching and developing an understanding of the current, or soon to be, available methane sensing technologies. Task 2 consisted of developing the architecture, selecting hardware, software and elements for the methane monitoring system. Task 3 focused on the algorithms used for the complex inverse model of going from measured methane signatures to the detection, localization, and quantification of sources that are desired. Finally, Task 4 focused on the methods of testing and validating the operation of the system. Attention was also given to the development method and cost breakdown of the system.
System for monitoring lightning strikes utilizes optical data link between lightning sensor and recording instruments thus making data link immune to electrical interference induced in wires by huge burst of energy in lightning strikes. It also protects people and equipment at data receiving end from electrical shock.
The problem of designing a computerized experiment monitoring system for use in a space station or elsewhere is examined. It is shown that the essential challenge of such a system - attaining a reasonable expected running time - can be attacked using the concept of focus of attention and by exploiting parallelism. The use of the Contract Net Protocol for the latter purpose is discussed. The use of ideas from information science to help focus a programs's efforts on those computations likely to bring results is addressed, and the incorporation of those ideas into a design in order to aid the system in deciding upon the best course of action is considered.
The performance of photovoltaic systems must be monitored accurately to ensure profitable long-term operation. The most important signals to be measured—irradiance and temperature, as well as power, current and voltage on both DC and AC sides of the system—contain rapid fluctuations that are not observable by typical monitoring systems. Nevertheless these fluctuations can affect the accuracy of the data that are stored. This report closely examines the main signals in one operating PV system, which were recorded at 2000 samples per second. It analyzes the characteristics and causes of the rapid fluctuations that are found, such as line-frequency harmonics, perturbations from anti-islanding detection, MPPT searching action and others. The operation of PV monitoring systems is then simulated using a wide range of sampling intervals, archive intervals and filtering options to assess how these factors influence data accuracy. Finally several potential sources of error are discussed with real-world examples.
Optimum system mechanizations for advanced manned spacecraft are considered. Several studies have proposed automation of the onboard system management task, with functions such as system status monitoring, configuration management, and redundancy management being accomplished under computer control. An experimental system was used in the laboratory to investigate hardware and software requirements for accomplishing these onboard system management functions. A performance monitor system is proposed for the space shuttle. This system provides support to the flight crew in the management of all onboard systems but does not perform critical switching functions during the flight phase.
Exploration missions will carry crews far beyond the relatively safe environs of cis-lunar space. Such trips will have little or no opportunity for resupply or rapid aborts and will be of a duration that far exceeds our experience to date. The challenges this imposes on the requirements of systems that monitor the life support and provide food and shelter for the crew are the focus of much research within the Human Research Program. Making all of these technologies robust and reliable enough for multi-year missions with little or no ability to run for home calls for a thorough understanding of the risks and impacts of failure. The way we currently monitor for microbial contamination of water, air, and surfaces, by sampling and growing cultures on nutrient media, must be reconsidered for exploration missions which have limited capacity for consumables. Likewise, the shelf life of food must be increased so that the nutrients required to keep the crewmembers healthy do not degrade over the life of the mission. Improved formulations, preservation, packaging, and storage technologies are all being investigated for ways slow this process or replace stowed food with key food items grown fresh in situ. Ensuring that the mass and volume of a spacecraft are used to maximum efficiency calls for infusing human factors into the design from its inception to increase efficiency, improve performance, and retain robustness toward operational realities. Integrating the human system with the spacecraft systems is the focus of many lines of investigation.
We discuss the application of Generalized Parity Relations to two experimental flexible space structures, the NASA Langley Mini-Mast and Marshall Space Flight Center ACES mast. We concentrate on the generation of residuals and make no attempt to implement the Decision Function. It should be clear from the examples that are presented whether it would be possible to detect the failure of a specific component. We derive the equations from Generalized Parity Relations. Two special cases are treated: namely, Single Sensor Parity Relations (SSPR) and Double Sensor Parity Relations (DSPR). Generalized Parity Relations for actuators are also derived. The NASA Langley Mini-Mast and the application of SSPR and DSPR to a set of displacement sensors located at the tip of the Mini-Mast are discussed. The performance of a reduced order model that includes the first five models of the mast is compared to a set of parity relations that was identified on a set of input-output data. Both time domain and frequency domain comparisons are made. The effect of the sampling period and model order on the performance of the Residual Generators are also discussed. Failure detection experiments where the sensor set consisted of two gyros and an accelerometer are presented. The effects of model order and sampling frequency are again illustrated. The detection of actuator failures is discussed. We use Generalized Parity Relations to monitor control system component failures on the ACES mast. An overview is given of the Failure Detection Filter and experimental results are discussed. Conclusions and directions for future research are given.