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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Performance consequences of automation-induced 'complacency'

The effect of variations in the reliability of an automated monitoring system on human operator detection of automation failures was examined in two experiments. For four 30-min sessions, 40 subjects performed an IBM PC-based flight simulation that included manual tracking and fuel-management tasks, as well as a system-monitoring task that was under automation control. Automation reliability - the percentage of system malfunctions detected by the automation routine - either remained constant at a low or high level over time or alternated every 10 min from low to high. Operator detection of automation failures was substantially worse for constant-reliability than for variable-reliability automation after about 20 min under automation control, indicating that the former condition induced 'complacency'. When system monitoring was the only task, detection was very efficient and was unaffected by variations in automation reliability. The results provide the first empirical evidence of the performance consequences of automation-induced 'complacency'. We relate findings to operator attitudes toward automation and discuss implications for cockpit automation design.

Parasuraman, Raja↗
NASA NTRS2007

Advanced Systems for Monitoring Underwater Sounds

The term "Passive Acoustic Monitoring System" (PAMS) describes a developmental sensing-and-data-acquisition system for recording underwater sounds. The sounds (more precisely, digitized and preprocessed versions from acoustic transducers) are subsequently analyzed by a combination of data processing and interpretation to identify and/or, in some cases, to locate the sources of those sounds. PAMS was originally designed to locate the sources such as fish of species that one knows or seeks to identify. The PAMS unit could also be used to locate other sources, for example, marine life, human divers, and/or vessels. The underlying principles of passive acoustic sensing and analyzing acoustic-signal data in conjunction with temperature and salinity data are not new and not unique to PAMS. Part of the uniqueness of the PAMS design is that it is the first deep-sea instrumentation design to provide a capability for studying soniferous marine animals (especially fish) over the wide depth range described below. The uniqueness of PAMS also lies partly in a synergistic combination of advanced sensing, packaging, and data-processing design features with features adapted from proven marine instrumentation systems. This combination affords a versatility that enables adaptation to a variety of undersea missions using a variety of sensors. The interpretation of acoustic data can include visual inspection of power-spectrum plots for identification of spectral signatures of known biological species or artificial sources. Alternatively or in addition, data analysis could include determination of relative times of arrival of signals at different acoustic sensors arrayed at known locations. From these times of arrival, locations of acoustic sources (and errors in those locations) can be estimated. Estimates of relative locations of sources and sensors can be refined through analysis of the attenuation of sound in the intervening water in combination with water-temperature and salinity data acquired by instrumentation systems other than PAMS. A PAMS is packaged as a battery-powered unit, mated with external sensors, that can operate in the ocean at any depth from 2 m to 1 km. A PAMS includes a pressure housing, a deep-sea battery, a hydrophone (which is one of the mating external sensors), and an external monitor and keyboard box. In addition to acoustic transducers, external sensors can include temperature probes and, potentially, underwater cameras. The pressure housing contains a computer that includes a hard drive, DC-to- DC power converters, a post-amplifier board, a sound card, and a universal serial bus (USB) 4-port hub.

Lane, Michael↗
NASA NTRS2002

An infrared system for monitoring Drosophila motility during microgravity

Presently, the precise mechanisms of the aging process are unknown. Examination and comprehension of the aging process in other species could lead to significant advances in the understanding of human aging. Drosophila melanogaster (fruit fly), commonly used for aging studies, is a widely studied organism in terms of behavior, development, and genetics. Previous microgravity experiments have shown a significant decrease in the life span of young male Drosophila after microgravity exposure. This decrease in lifespan may be related to locomotor activity, a convenient measure of overall physiological performance. This study describes the design and performance of a Drosophila Infrared Motility Monitoring System (DIMMS). The DIMMS uses a unique design of two infrared (IR) beams per fly to measure the locomotor activity of 240 flies. Locomotor activity is measured in terms of number of IR crossings per unit time, instantaneous velocity, and continuous velocity. Ground-based results using the DIMMS equipment agree well with previous values for Drosophila locomotor velocity. DIMMS is an improvement over equipment previously used due to its ability to continuously monitor locomotor activity throughout short-duration microgravity exposure. DIMMS is also lightweight, compact, and power efficient. DIMMS has been flight tested onboard NASA's KC-135 reduced gravity research aircraft and a Nike-Orion sounding rocket.

unmanned↗
NASA NTRS1996

Remote Monitor Alarm System

A remote monitor alarm system monitors discrete alarm and analog power supply voltage conditions at remotely located communications terminal equipment. A central monitoring unit (CMU) is connected via serial data links to each of a plurality of remote terminal units (RTUS) that monitor the alarm and power supply conditions of the remote terminal equipment. Each RTU can monitor and store condition information of both discrete alarm points and analog power supply voltage points in its associated communications terminal equipment. The stored alarm information is periodically transmitted to the CMU in response to sequential polling of the RTUS. The number of monitored alarm inputs and permissible voltage ranges for the analog inputs can be remotely configured at the CMU and downloaded into programmable memory at each RTU. The CMU includes a video display, a hard disk memory, a line printer and an audio alarm for communicating and storing the alarm information received from each RTU.

Stute, Robert A.↗
NASA NTRS2001

A Fully Redundant On-Line Mass Spectrometer System Used to Monitor Cryogenic Fuel Leaks on the Space Shuttle

An on-line gas monitoring system was developed to replace the older systems used to monitor for cryogenic leaks on the Space Shuttles before launch. The system uses a mass spectrometer to monitor multiple locations in the process, which allows the system to monitor all gas constituents of interest in a nearly simultaneous manner. The system is fully redundant and meets all requirements for ground support equipment (GSE). This includes ruggedness to withstand launch on the Mobile Launcher Platform (MLP), ease of operation, and minimal operator intervention. The system can be fully automated so that an operator is notified when an unusual situation or fault is detected. User inputs are through personal computer using mouse and keyboard commands. The graphical user interface is very intuitive and easy to operate. The system has successfully supported four launches to date. It is currently being permanently installed as the primary system monitoring the Space Shuttles during ground processing and launch operations. Time and cost savings will be substantial over the current systems when it is fully implemented in the field. Tests were performed to demonstrate the performance of the system. Low limits-of-detection coupled with small drift make the system a major enhancement over the current systems. Though this system is currently optimized for detecting cryogenic leaks, many other gas constituents could be monitored using the Hazardous Gas Detection System (HGDS) 2000.

Griffin, Timothy P.↗
NASA NTRS2022

Integrating FRET with Copilot: Automated Translation of Natural Language Requirements to Runtime Monitors

Runtime verification (RV) enables monitoring systems at runtime, to detect property violations early and limit their potential consequences. To provide the level of assurance required for ultra-critical systems, monitor specifications must faithfully reflect the original mission requirements, which are often written in ambiguous natural language. This paper presents an end-to-end framework to capture requirements in structured natural language and generate monitors that capture their semantics faithfully. We leverage NASA’s Formal Requirement Elicitation Tool (FRET), and the RV system Copilot. We extend FRET with mechanisms to capture additional information needed to generate monitors, and introduce OGMA, a new tool to bridge the gap between FRET and Copilot. With this framework, users can write requirements in an intuitive format and obtain real-time C monitors suitable for use in embedded systems. Our tool chain is available as open source.

FRET↗
NASA NTRS2002

A Fully Redundant On-Line Mass Spectrometer System Used to Monitor Cryogenic Fuel Leaks on the Space Shuttle

An on-line gas monitoring system was developed to replace the older systems used to monitor for cryogenic leaks on the Space Shuttles before launch. The system uses a mass spectrometer to monitor multiple locations in the process, which allows the system to monitor all gas constituents of interest in a nearly simultaneous manner. The system is fully redundant and meets all requirements for ground support equipment (GSE). This includes ruggedness to withstand launch on the Mobile Launcher Platform (MLP), ease of operation, and minimal operator intervention. The system can be fully automated so that an operator is notified when an unusual situation or fault is detected. User inputs are through personal computer using mouse and keyboard commands. The graphical user for detecting cryogenic leaks, many other gas constituents could be monitored using the Hazardous Gas Detection System (HGDS) 2000.

Griffin, Timothy P.↗
NASA NTRS1985

Design of an expert-system flight status monitor

The present technology used to monitor systems in flight tests is not advanced enough for the modern avionics in high performance aircraft. Research is being conducted at NASA's Dryden Flight Research Facility to design an expert system to monitor test flights. The expert system is to automatically detect any problems in the flight control system (FCS), interpret the problem from the information contained in its knowledge base, inform the systems engineer, and recommend solutions. The data is to be downlinked from the aircraft to the control room. The expert system will lessen the responsibilities of the engineers by providing them with fast, expert advice. Time is the most critical factor in flight testing and the expert system will be able to quickly recognize discrepancies and provide corrections. A demonstration of the expert system, not operating in real time, has already been tested.

Regenie, V. A.↗
NASA NTRS2005

Integrity monitoring of IGS products

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.

GPS↗
NASA NTRS2007

Improved Heat-Stress Algorithm

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.

Teets, Edward H., Jr.↗
NASA NTRS1973

Computer system for monitoring radiorepirometry data

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.

Feller, D. D.↗
NASA NTRS1994

Configurable technology development for reusable control and monitor ground systems

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.

Uhrlaub, David R.↗
NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

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.

Iverson, David L.↗
NASA NTRS1978

Automatic radio-transmission monitor

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.

Bernstein, A. J.↗
NASA NTRS1991

Engineering monitoring expert system's developer

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.

Lo, Ching F.↗
NASA NTRS2015

System and Method for Monitoring Distributed Asset Data

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.

Gorinevsky, Dimitry↗