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At least 253 records · Page 14

A prototype expert system in OPS5 for data error detection

A prototype expert system was developed in the OPS5 language to perform error checking on data which spacecraft builders/users supply to NASA GSFC for processing on the Communications Link Analysis and Simulation System (CLASS) computer. This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules and at present runs on an IBM PC in the OPS5+ software package from Artelligence, Inc. In its operational phase, TRAPS will run in the Oak Ridge Production Language (ORPL) on the CLASS computer (a Perkin-Elmer 3244 supermini). ORPL, an implementation of OPS5 by the Oak Ridge National Laboratory in MULTOFORTH on a Hewlett-Packard 9836 desktop computer, is now being ported to SS-FORTH on the CLASS computer. This paper discusses the expert system problem domain, development approach, tools, results and future plans stemming from the TRAPS project.

Rash, James↗

An application of object-oriented knowledge representation to engineering expert systems

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

D S Logie↗

Linking medical records to an expert system

This presentation will be done using the IMR-Entry (Intelligent Medical Record Entry) system. IMR-Entry is a software program developed as a front-end to our diagnostic consultant software MEDAS (Medical Emergency Decision Assistance System). MEDAS (the Medical Emergency Diagnostic Assistance System) is a diagnostic consultant system using a multimembership Bayesian design for its inference engine and relational database technology for its knowledge base maintenance. Research on MEDAS began at the University of Southern California and the Institute of Critical Care in the mid 1970's with support from NASA and NSF. The MEDAS project moved to Chicago in 1982; its current progress is due to collaboration between Illinois Institute of Technology, The Chicago Medical School, Lake Forest College and NASA at KSC. Since the purpose of an expert system is to derive a hypothesis, its communication vocabulary is limited to features used by its knowledge base. The development of a comprehensive problem based medical record entry system which could handshake with an expert system while creating an electronic medical record at the same time was studied. IMR-E is a computer based patient record that serves as a front end to the expert system MEDAS. IMR-E is a graphically oriented comprehensive medical record. The programs major components are demonstrated.

Naeymi-Rad, Frank↗

Thermal Expert System (TEXSYS): Systems automony demonstration project, volume 1. Overview

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS test bed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Glass, B. J.↗

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Glass, B. J.↗

An expert system executive for automated assembly of large space truss structures

Langley Research Center developed a unique test bed for investigating the practical problems associated with the assembly of large space truss structures using robotic manipulators. The test bed is the result of an interdisciplinary effort that encompasses the full spectrum of assembly problems - from the design of mechanisms to the development of software. The automated structures assembly test bed and its operation are described, the expert system executive and its development are detailed, and the planned system evolution is discussed. Emphasis is on the expert system implementation of the program executive. The executive program must direct and reliably perform complex assembly tasks with the flexibility to recover from realistic system errors. The employment of an expert system permits information that pertains to the operation of the system to be encapsulated concisely within a knowledge base. This consolidation substantially reduced code, increased flexibility, eased software upgrades, and realized a savings in software maintenance costs.

Allen, Cheryl L.↗

TOPEX/Poseidon precision orbit determination production and expert system

TOPEX/Poseidon (T/P) is a joint mission between NASA and the Centre National d'Etudes Spatiales (CNES), the French Space Agency. The TOPEX/Poseidon Precision Orbit Determination Production System (PODPS) was developed at Goddard Space Flight Center (NASA/GSFC) to produce the absolute orbital reference required to support the fundamental ocean science goals of this satellite altimeter mission within NASA. The orbital trajectory for T/P is required to have a RMS accuracy of 13 centimeters in its radial component. This requirement is based on the effective use of the satellite altimetry for the isolation of absolute long-wavelength ocean topography important for monitoring global changes in the ocean circulation system. This orbit modeling requirement is at an unprecedented accuracy level for this type of satellite. In order to routinely produce and evaluate these orbits, GSFC has developed a production and supporting expert system. The PODPS is a menu driven system allowing routine importation and processing of tracking data for orbit determination, and an evaluation of the quality of the orbit so produced through a progressive series of tests. Phase 1 of the expert system grades the orbit and displays test results. Later phases undergoing implementation, will prescribe corrective actions when unsatisfactory results are seen. This paper describes the design and implementation of this orbit determination production system and the basis for its orbit accuracy assessment within the expert system.

Putney, Barbara↗

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Wang, Lui↗

The Pacor 2 expert system: A case-based reasoning approach to troubleshooting

The Packet Processor 2 (Pacor 2) Data Capture Facility (DCF) acquires, captures, and performs level-zero processing of packet telemetry for spaceflight missions that adhere to communication services recommendations established by the Consultative Committee for Space Data Systems (CCSDS). A major goal of this project is to reduce life-cycle costs. One way to achieve this goal is to increase automation. Through automation, using expert systems, and other technologies, staffing requirements will remain static, which will enable the same number of analysts to support more missions. Analysts provide packet telemetry data evaluation and analysis services for all data received. Data that passes this evaluation is forwarded to the Data Distribution Facility (DDF) and released to scientists. Through troubleshooting, data that fails this evaluation is dumped and analyzed to determine if its quality can be improved before it is released. This paper describes a proof-of-concept prototype that troubleshoots data quality problems. The Pacor 2 expert system prototype uses the case-based reasoning (CBR) approach to development, an alternative to a rule-based approach. Because Pacor 2 is not operational, the prototype has been developed using cases that describe existing troubleshooting experience from currently operating missions. Through CBR, this experience will be available to analysts when Pacor 2 becomes operational. As Pacor 2 unique experience is gained, analysts will update the case base. In essence, analysts are training the system as they learn. Once the system has learned the cases most likely to recur, it can serve as an aide to inexperienced analysts, a refresher to experienced analysts for infrequently occurring problems, or a training tool for new analysts. The Expert System Development Methodology (ESDM) is being used to guide development.

Sary, Charisse↗

Expert system shell to reason on large amounts of data

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

Giuffrida, Gionanni↗

Development of an expert system for power quality advisement using CLIPS 6.0

Proliferation of power electronic devices has brought in its wake both deterioration in and demand for quality power supply from the utilities. The power quality problems become apparent when the user's equipment or systems maloperate or fail. Since power quality concerns arise from a wide variety of sources and the problem fixes are better achieved from the expertise of field engineers, development of an expert system for power quality advisement seems to be a very attractive and cost-effective solution for utility applications. An expert system thus developed gives an understanding of the adverse effects of power quality related problems on the system and could help in finding remedial solutions. The paper reports the design of a power quality advisement expert system being developed using CLIPS 6.0. A brief outline of the power quality concerns is first presented. A description of the knowledge base is next given and details of actual implementation include screen output from the program.

Chandrasekaran, A.↗

A CLIPS-based expert system for the evaluation and selection of robots

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

Nour, Mohamed A.↗

EDNA: Expert fault digraph analysis using CLIPS

Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

Dixit, Vishweshwar V.↗

An expert system to manage the operation of the Space Shuttle's fuel cell cryogenic reactant tanks

This paper describes a rule-based expert system to manage the operation of the Space Shuttle's cryogenic fuel system. Rules are based on standard fuel tank operating procedures described in the EECOM Console Handbook. The problem of configuring the operation of the Space Shuttle's fuel tanks is well-bounded and well defined. Moreover, the solution of this problem can be encoded in a knowledge-based system. Therefore, a rule-based expert system is the appropriate paradigm. Furthermore, the expert system could be used in coordination with power system simulation software to design operating procedures for specific missions.

Murphey, Amy Y.↗

A comparison of CLIPS- and LISP-based approaches to the development of a real-time expert system

This paper describes an ongoing expert system development effort started in 1988 which is evaluating both CLIPS- and LISP- based approaches. The expert system is being developed to a project schedule and is planned for flight on Space Shuttle Mission SLS-2 in 1992. The expert system will help astronauts do the best possible science for a vestibular physiology experiment already scheduled for that mission. The system gathers and reduces data from the experiment, flags 'interesting' results, and proposes changes in the experiment both to exploit the in-flight observations and to stay within the time allowed by Mission Control for the experiment. These tasks must all be performed in real time. Two Apple Macintosh computers are used. The CLIPS- and LISP- based environments are layered above the Macintosh computer Operating System. The 'CLIPS-based' environment includes CLIPS and HyperCard. The LlSP-based environment includes Common LISP, Parmenides (a frame system), and FRuleKit (a rule system). Important evaluation factors include ease of programming, performance against real-time requirements, usability by an astronaut, robustness, and ease of maintenance. Current results on the factors of ease of programming, performance against real-time requirements, and ease of maintenance are discussed.

Frainier, R.↗

Expert system for scheduling simulation lab sessions

Implementation and results of an expert system used for scheduling session requests for the Systems Engineering Simulator (SES) laboratory at the NASA Johnson Space Center (JSC) are discussed. Weekly session requests are received from astronaut crew trainers, procedures developers, engineering assessment personnel, software developers, and various others who wish to access the computers, scene generators, and other simulation equipment available to them in the SES lab. The expert system under discussion is comprised of a data acquisition portion - two Pascal programs run on a personal computer - and a CLIPS program installed on a minicomputer. A brief introduction to the SES lab and its scheduling background is given. A general overview of the system is provided, followed by a detailed description of the constraint-reduction process and of the scheduler itself. Results from a ten-week trial period using this approach are discussed. Finally, a summary of the expert system's strengths and shortcomings are provided.

Lund, Chet↗

Development of an instructional expert system for hole drilling processes

An expert system which captures the expertise of workshop technicians in the drilling domain was developed. The expert system is aimed at novice technicians who know how to operate the machines but have not acquired the decision making skills that are gained with experience. This paper describes the domain background and the stages of development of the expert system.

Al-Mutawa, Souhaila↗

Howard University Energy Expert Systems Institute Summer Program (EESI)

Howard University, under the auspices of the Center for Energy Systems and Controls runs the Energy Expert Systems Institute (EESI) summer outreach program for high school/pre-college minority students. The main objectives are to introduce precollege minority students to research in the power industry using modern state-of-the-art technology such as Expert Systems, Fuzzy Logic and Artificial Neural Networks; to involve minority students in space power management, systems and failure diagnosis; to generate interest in career options in electrical engineering; and to experience problem-solving in a teamwork environment consisting of faculty, senior research associates and graduate students. For five weeks the students are exposed not only to the exciting experience of college life, but also to the inspiring field of engineering, especially electrical engineering. The program consists of lectures in the fundamentals of engineering, mathematics, communication skills and computer skills. The projects are divided into mini and major. Topics for the 1995 mini projects were Expert Systems for the Electric Bus and Breast Cancer Detection. Topics on the major projects include Hybrid Electric Vehicle, Solar Dynamics and Distribution Automation. On the final day, designated as 'EESI Day' the students did oral presentations of their projects and prizes were awarded to the best group. The program began in the summer of 1993. The reaction from the students has been very positive. The program also arranges field trips to special places of interest such as the NASA Goddard Space Center.

Momoh, James A.↗