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NASA NTRS1993

An integrated knowledge system for the Space Shuttle hazardous gas detection system

A computer-based integrated Knowledge-Based System, the Intelligent Hypertext Manual (IHM), was developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at NASA Marshall Space Flight Center (MSFC). The IHM stores HGDS related knowledge and presents it in an interactive and intuitive manner. This manual is a combination of hypertext and an expert system which store experts' knowledge and experience in hazardous gas detection and analysis. The IHM's purpose is to provide HGDS personnel with the capabilities of: locating applicable documentation related to procedures, constraints, and previous fault histories; assisting in the training of personnel; enhancing the interpretation of real time data; and recognizing and identifying possible faults in the Space Shuttle sub-systems related to hazardous gas detection.

Lo, Ching F.↗

NASA NTRS1992

Expert system-based mineral mapping using AVIRIS

Integrated analysis of imaging spectrometer data and field spectral measurements were used in conjunction with conventional geologic field mapping to characterize bedrock and surficial geology at the northern end of Death Valley, California and Nevada. A knowledge-based expert system was used to automatically produce image maps from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data showing the principal surface mineralogy. The imaging spectrometer data show the spatial distribution of spectrally distinct minerals occurring both as primary rock-forming minerals and as alteration and weathering products. Field spectral measurements were used to verify the mineral maps and field mapping was used to extend the remote sensing results. Geographically referenced image-maps produced from these data form new base maps from which to develop improved understanding of the processes of deposition and erosion affecting the present land surface. The 'northern Grapevine Mountains' (NGM) study area was reported on in numerous papers. This area is an unnamed northwestward extension of the range. Most of the research here has concentrated on mapping of Jurassic-age plutons and associated hydrothermal alteration, however, the nature and scope of these studies is much broader, pertaining to the geologic history and development of the entire Death Valley region. AVIRIS data for the NGM site were obtained during May 1989. Additional AVIRIS data were acquired during September 1989 as part of the Geologic Remote Sensing Field Experiment (GRSFE). The area covered by these data overlaps slightly with the May 1989 data. Three and one-half AVIRIS scenes total were analyzed.

Kruse, Fred A.↗

NASA NTRS1992

Fuzzy and neural control

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Berenji, Hamid R.↗

NASA NTRS1993

Expanding the KATE toolbox

KATE (Knowledge-based Autonomous Test Engineer) is a model-based software system developed in the Artificial Intelligence Laboratory at the Kennedy Space Center for monitoring, fault detection, and control of launch vehicles and ground support systems. In order to bring KATE to the level of performance, functionality, and integratability needed for firing room applications, efforts are underway to implement KATE in the C++ programming language using an X-windows interface. Two programs which were designed and added to the collection of tools which comprise the KATE toolbox are described. The first tool, called the schematic viewer, gives the KATE user the capability to view digitized schematic drawings in the KATE environment. The second tool, called the model editor, gives the KATE model builder a tool for creating and editing knowledge base files. Design and implementation issues having to do with these two tools are discussed. It will be useful to anyone maintaining or extending either the schematic viewer or the model editor.

Thomas, Stan J.↗

NASA NTRS1992

A knowledge based system for scientific data visualization

A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

Senay, Hikmet↗

NASA NTRS1993

Influence of a new generation of operations support systems on current spacecraft operations philosophy: The users feedback

Current trends in the spacecraft mission operations area (spacecraft & mission complexity, project duration, required flexibility are requiring a breakthrough for what concerns philosophy, organization, and support tools. A major evolution is related to space operations 'informationalization', i.e adding to existing operations support & data processing systems a new generation of tools based on advanced information technologies (object-oriented programming, artificial intelligence, data bases, hypertext) that automate, at least partially, operations tasks that used be performed manually (mission & project planning/scheduling, operations procedures elaboration & execution, data analysis & failure diagnosis). All the major facets of this 'informationalization' are addressed at MATRA MARCONI SPACE, operational applications were fielded and generic products are becoming available. These various applications have generated a significant feedback from the users (at ESA, CNES, ARIANESPACE, MATRA MARCONI SPACE), which is now allowing us to precisely measure how the deployment of this new generation of tools, that we called OPSWARE, can 'reengineer' current spacecraft mission operations philosophy, how it can make space operations faster, better, and cheaper. This paper can be considered as an update of the keynote address 'Knowledge-Based Systems for Spacecraft Control' presented during the first 'Ground Data Systems for Spacecraft Control' conference in Darmstadt, June 1990, with a special emphasis on these last two years users feedback.

Darroy, Jean Michel↗

NASA NTRS1993

Situation management in the Link Monitor and Control Operator Assistant (LMCOA)

This paper describes a knowledge-based system called the Situation Manager that was developed for the Link Monitor and Control Operator Assistant (LMCOA) at the Jet Propulsion Laboratory. This system was developed in response to a number of deficiencies that were identified in an earlier version of the LMCOA: the need to close the control loop between sending a directive and knowing when its execution is complete (versus just closing the communications loop), the need to recognize an anomaly and alert the operator when a directive is rejected or a link device fails, and the need to suggest ways to work around an anomaly, provided that it is recognizable. In response to these needs, the Situation Manager has been designed to provide the LMCOA with three basic capabilities: situation assessment, anomaly diagnosis, and recovery from commonly occurring problems.

Hill, Randall W., Jr.↗

NASA NTRS1990

System control module diagnostic Expert Assistant

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

Flores, Luis M.↗

NASA NTRS1990

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.↗

NASA NTRS1990

ISLE: Intelligent Selection of Loop Electronics. A CLIPS/C++/INGRES integrated application

The Intelligent Selection of Loop Electronics (ISLE) system is an integrated knowledge-based system that is used to configure, evaluate, and rank possible network carrier equipment known as Digital Loop Carrier (DLC), which will be used to meet the demands of forecasted telephone services. Determining the best carrier systems and carrier architectures, while minimizing the cost, meeting corporate policies and addressing area service demands, has become a formidable task. Network planners and engineers use the ISLE system to assist them in this task of selecting and configuring the appropriate loop electronics equipment for future telephone services. The ISLE application is an integrated system consisting of a knowledge base, implemented in CLIPS (a planner application), C++, and an object database created from existing INGRES database information. The embedibility, performance, and portability of CLIPS provided us with a tool with which to capture, clarify, and refine corporate knowledge and distribute this knowledge within a larger functional system to network planners and engineers throughout U S WEST.

Fischer, Lynn↗

NASA NTRS1990

HyperCLIPS: A HyperCard interface to CLIPS

HyperCLIPS combines the intuitive, interactive user interface of the Apple Macintosh(TM) with the powerful symbolic computation of an expert system interpreter. HyperCard(TM) is an excellent environment for quickly developing the front end of an application with buttons, dialogs, and pictures, while the CLIPS interpreter provides a powerful inference engine for complex problem solving and analysis. By integrating HyperCard and CLIPS the advantages and uses of both packages are made available for a wide range of uses: rapid prototyping of knowledge-based expert systems, interactive simulations of physical systems, and intelligent control of hypertext processes, to name a few. Interfacing HyperCard and CLIPS is natural. HyperCard was designed to be extended through the use of external commands (XCMDs), and CLIPS was designed to be embedded through the use of the I/O router facilities and callable interface routines. With the exception of some technical difficulties which will be discussed later, HyperCLIPS implements this interface in a straight forward manner, using the facilities provided. An XCMD called 'ClipsX' was added to HyperCard to give access to the CLIPS routines: clear, load, reset, and run. And an I/O router was added to CLIPS to handle the communication of data between CLIPS and HyperCard.

Pickering, Brad↗

NASA NTRS1990

UFC advisor: An AI-based system for the automatic test environment

The Air Logistics Command within the Air Force is responsible for maintaining a wide variety of aircraft fleets and weapon systems. To maintain these fleets and systems requires specialized test equipment that provides data concerning the behavior of a particular device. The test equipment is used to 'poke and prod' the device to determine its functionality. The data represent voltages, pressures, torques, temperatures, etc. and are called testpoints. These testpoints can be defined numerically as being in or out of limits/tolerance. Some test equipment is termed 'automatic' because it is computer-controlled. Due to the fact that effective maintenance in the test arena requires a significant amount of expertise, it is an ideal area for the application of knowledge-based system technology. Such a system would take testpoint data, identify values out-of-limits, and determine potential underlying problems based on what is out-of-limits and how far. This paper discusses the application of this technology to a device called the Unified Fuel Control (UFC) which is maintained in this manner.

Lincoln, David T.↗

NASA NTRS1989

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗

NASA NTRS1992

Proceedings of the Workshop on Change of Representation and Problem Reformulation

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Lowry, Michael R.↗

NASA NTRS1985

Development of an Expert System for Representing Procedural Knowledge

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Georgeff, Michael P.↗

NASA NTRS1990

Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

McManus, John W.↗

NASA NTRS1992

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMaid)

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Rogers, James L.↗

NASA NTRS1989

Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

McManus, John W.↗