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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

A flight expert system for on-board fault monitoring and diagnosis

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

Ali, Moonis↗
NASA NTRS1987

An evaluation of a real-time fault diagnosis expert system for aircraft applications

A fault monitoring and diagnosis expert system called Faultfinder was conceived and developed to detect and diagnose in-flight failures in an aircraft. Faultfinder is an automated intelligent aid whose purpose is to assist the flight crew in fault monitoring, fault diagnosis, and recovery planning. The present implementation of this concept performs monitoring and diagnosis for a generic aircraft's propulsion and hydraulic subsystems. This implementation is capable of detecting and diagnosing failures of known and unknown (i.e., unforseeable) type in a real-time environment. Faultfinder uses both rule-based and model-based reasoning strategies which operate on causal, temporal, and qualitative information. A preliminary evaluation is made of the diagnostic concepts implemented in Faultfinder. The evaluation used actual aircraft accident and incident cases which were simulated to assess the effectiveness of Faultfinder in detecting and diagnosing failures. Results of this evaluation, together with the description of the current Faultfinder implementation, are presented.

Schutte, Paul C.↗
NASA NTRS1989

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗
NASA NTRS1989

Space Shuttle Main Engine component assembly, assignment, and scheduling expert system

The SSME's Component Assembly and Life Management Expert System (CALMES) assists the engine assembly and scheduling process, ensuring that these activities utilize available resources with the greatest possible efficiency. On the basis of parts inventories and a proposed flight schedule, CALMES (1) determined how components may be optimally assembled from the parts inventory, (2) assigns components to flights, (3) schedules component testing, and (4) schedules component assembly. A graph-theoretical optimal matching algorithm, based on a modified simplex method, is applied to the major functions required by the SSME component assembly and scheduling processes.

Dietz, W. E.↗
NASA NTRS1991

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

Anastasiadis, Stergios↗
NASA NTRS1991

Neural network based expert system for compressor stall monitoring

This research is designed to apply a new information processing technology, artificial neural networks, to monitoring compressor stall. The outputs of neural networks support the dynamic knowledge data base of an expert system. This is the open-loop mode to avoid compressor stall. The integration of a control system with neural networks is the closed-loop mode in stall avoidance. The feasibility of the concept has been demonstrated for the compressor of 16-foot transonic/supersonic propulsion wind tunnels. The construction of a prototpye expert system has been initiated.

Lo, Ching F.↗
NASA NTRS1984

A representational basis for the development of a distributed expert system for Space Shuttle flight control

A new representation of malfunction procedure logic which permits the automation of these procedures using Boolean normal forms is presented. This representation is discussed in the context of the development of an expert system for space shuttle flight control including software and hardware implementation modes, and a distributed architecture. The roles and responsibility of the flight control team as well as previous work toward the development of expert systems for flight control support at Johnson Space Center are discussed. The notion of malfunction procedures as graphs is introduced as well as the concept of hardware-equivalence.

Helly, J. J., Jr.↗
NASA NTRS1991

Real-time expert system and neural network for the classification of remotely sensed data

The paper examines software techniques for classifying remotely sensed data such that the number of computational steps and the amount of resources are bounded. The combination of both neural network and expert system methodology for classifying these data based on land use/land cover categories is examined. The method involves pipelining images through a neural net for initial classification and then through the expert system which resolves the ambiguous classifications. As with any pipeline, every component must have approximately equivalent run-times or otherwise a bottleneck will occur. If real-time is a requirement, each of the components must execute within a bounded number of steps. Attention is focused on the real-time system technique, which is argued to prevent a bottleneck for this data classification application.

Short, Nicholas, Jr.↗
NASA NTRS1991

NMESys: An expert system for network fault detection

The problem of network management is becoming an increasingly difficult and challenging task. It is very common today to find heterogeneous networks consisting of many different types of computers, operating systems, and protocols. The complexity of implementing a network with this many components is difficult enough, while the maintenance of such a network is an even larger problem. A prototype network management expert system, NMESys, implemented in the C Language Integrated Production System (CLIPS). NMESys concentrates on solving some of the critical problems encountered in managing a large network. The major goal of NMESys is to provide a network operator with an expert system tool to quickly and accurately detect hard failures, potential failures, and to minimize or eliminate user down time in a large network.

Nelson, Peter C.↗
NASA NTRS1990

Dynamic array processing for computationally intensive expert systems in CLIPS

This paper puts forth an architecture for implementing a loop for advanced data structure of arrays in CLIPS. An attempt is made to use multi-field variables in such an architecture to process a set of data during the decision making cycle. Also, current limitations on the expert system shells are discussed in brief in this paper. The resulting architecture is designed to circumvent the current limitations set by the expert system shell and also by the operating environment. Such advanced data structures are needed for tightly coupling symbolic and numeric computation modules.

Athavale, N. N.↗
NASA NTRS1988

Using AGNESS (A Generalized Network-based Expert System Shell) for matching images

The image correspondence problem is considered the most difficult step in both stereo and motion analysis. Stereo vision is useful in determining the 3-D positions of points on visible surface in a scene. Motion analysis is useful in determining the spatial and temporal relationships of objects in an environment. Besides stereo and motion analysis, there is the image correspondence problem. Most of this work is based on point or local area properties of the observed gray level values in 2-D images. A global and general approach to this problem is described by using a knowledge-based system. The knowledge it uses consists of both physical properties and spatial relationships of the edges and regions extracted from the given images. The physical component depends on features of the edge or region) in isolation. The spatial component involves the set of edges and regions adjacent to a given edge (or region) of the first image and the set of edges and regions adjacent to each potentially matching edge (or region) of the second image; thus the spatial context of each edge or region is considered. A computational network is used to represent this knowledge, it allows the computation of the likelihood of matching two edges or regions with logical and heuristic operators. An expert system shell called AGNESS (A Generalized Network-based Expert System Shell) is used to build a prototype system.

Pong, Ting-Chuen↗
NASA NTRS1988

An expert system for satellite and instrument data anomaly and fault isolation

A prototype Generic Payload Operations Control System (GPOCC) is being developed at the NASA Jet Propulsion Laboratory to provide a low-cost command and control processing center for science instruments and small payloads. The GPOCC supports the difficult transition from integration and test to flight operations. The prototype will incorporate four expert systems to perform telemetry, command, and mission planning functions as well as telecommunications scheduling. The first of these expert systems to be developed will perform telemetry data analysis and fault isolation, as well as propose corrective action. This Data Analysis Module (DAM) will monitor telemetry data and perform continual data monitoring and trend analysis based on a knowledge base and historic data archived on an optical disk storage device. The system maintains a continuous knowledge database of past system performance characteristics. The goal of the Data Analysis Module is to achieve consistent, dependable and validatable performance, to demonstrate thorough, reliable and fast reasoning, and to reduce the concentration demanded of flight analysis personnel.

Busse, Carl↗
NASA NTRS1985

Prototype fault isolation expert system for spacecraft control

A program which illustrates how an expert system might perform fault handling for a satellite propulsion subsystem is discussed. The program runs on a VAX 11/780 under VMS with a VT100 interface and is written in FRANZ/LISP. The program presents a series of menus to the user. Once the user selects from the menu, the program simulates the behavior of the hydrazine propulsion system under the fault condition, detects the presence of the fault, and then determines what set of actions to perform in implementing the fault workaround.

Truszkowski, Walt↗
NASA NTRS1987

Optical expert systems

A general approach to using spatial light modulators in expert systems and in related AI methods is discussed. The information capacity of such system can far exceed the capacity of the spatial light modulator itself.

Szu, Harold H.↗
NASA NTRS1986

An expert system for ground support of the Hubble space telescope

The Hubble Space Telescope is an orbiting optical observatory due to be launched by the Space Shuttle in late 1987. It is a complex, multi-instrument observatory whose resources will be available to the world-wide astronomical community. The 'Transformation' system is a hybrid system which utilizes a rule-based expert system to convert scientific proposals into pre-optimized linked hierarchies of spacecraft activities. These activities are generated in a format that can be directly scheduled by the planning and scheduling component of the Space Telescope ground support system. The Transformation system will be described in detail in this paper, with particular attention given to the rule base.

Rosenthal, Don↗
NASA NTRS1991

A knowledge-based expert system for inferring vegetation characteristics

A prototype knowledge-based expert system VEG is presented that focuses on extracting spectral hemispherical reflectance using any combination of nadir and/or directional reflectance data as input. The system is designed to facilitate expansion to handle other inferences regarding vegetation properties such as total hemispherical reflectance, leaf area index, percent ground cover, phosynthetic capacity, and biomass. This approach is more robust and accurate than conventional extraction techniques previously developed.

Kimes, Daniel S.↗
NASA NTRS1990

An expert system to advise astronauts during experiments: The protocol manager module

Perhaps the scarcest resource for manned flight experiments - on Spacelab or on the Space Station Freedom - will continue to be crew time. To maximize the efficiency of the crew and to make use of their abilities to work as scientist collaborators as well as equipment operators, normally requires more training in a wide variety of disciplines than is practical. The successful application of on-board expert systems, as envisioned by the Principal Investigator in a Box program, should alleviate the training bottleneck and provide the astronaut with the guidance and coaching needed to permit him or her to operate an experiment according to the desires and knowledge of the PI, despite changes in conditions. The Protocol Manager module of the system is discussed. The Protocol Manager receives experiment data that has been summarized and categorized by the other modules. The Protocol Manager acts on the data in real-time, by employing expert system techniques. Its recommendations are based on heuristics provided by the Principal Investigator in charge of the experiment. This prototype was developed on a Macintosh II by employing CLIPS, a forward-chaining rule-based system, and HyperCard as an object-oriented user interface builder.

Haymann-Haber, Guido↗
NASA NTRS1988

Knowledge-based operation and management of communications systems

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Heggestad, Harold M.↗