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At least 865 records · Page 48

All sources NASA NTRS DOE OSTI

NASA NTRS1987

An easy-to-use diagnostic system development shell

The Diagnostic System Development Shell (DSDS), an expert system development shell for diagnostic systems, is described. The major objective of building the DSDS is to create a very easy to use and friendly environment for knowledge engineers and end-users. The DSDS is written in OPS5 and CommonLisp. It runs on a VAX/VMS system. A set of domain independent, generalized rules is built in the DSDS, so the users need not be concerned about building the rules. The facts are explicitly represented in a unified format. A powerful check facility which helps the user to check the errors in the created knowledge bases is provided. A judgement facility and other useful facilities are also available. A diagnostic system based on the DSDS system is question driven and can call or be called by other knowledge based systems written in OPS5 and CommonLisp. A prototype diagnostic system for diagnosing a Philips constant potential X-ray system has been built using the DSDS.

Tsai, L. C.↗

NASA NTRS1987

Technology requirements for telerobotic satellite servicing in space

Telerobotic servicer technology requirements were identified for typical on-orbit servicing operations, including: automation requirements and automated system utilization in typical servicing missions; key automation technologies used for servicing; evolution concepts; technology development timetable; and servicing technology drivers. Teleoperation, robotics, and artificial intelligence are needed in the servicing missions investigated. Analysis shows that teleoperation will be used more widely than fully robotic systems, at least during the early space station years because of the diversity and unpredictability of many servicing tasks which call for the human operator's skills, resourcefulness, and decision-making ability. There will be heavy dependence on a sophisticated, flexible, readily accessible, high-speed and high-capacity data management system which can provide the expert system support required in diagnosing, troubleshooting, decision making, task scheduling, and mission planning.

Meissinger, Hans F.↗

NASA NTRS1988

Application of intelligent systems to wind tunnel test facilities

An approach to the application of intelligent-systems technology to the wind tunnel facilities at NASA Ames Research Center is outlined. To help fulfill the long-range goals of improving data quality and increasing personnel efficiency and management effectiveness, three major areas of intelligent systems application are recommended. The available state-of-the-art technology for developing the proposed systems is reviewed including the application of commercial software packages. The initial tasks and effort to develop these systems are recommended. A prototype expert system for selection of internal strain-gage balances has been built and is presented herein as an example model for the future systems.

Lo, Ching F.↗

NASA NTRS1988

Automatic acquisition of domain and procedural knowledge

The design concept and performance of AKAS, an automated knowledge-acquisition system for the development of expert systems, are discussed. AKAS was developed using the FLES knowledge base for the electrical system of the B-737 aircraft and employs a 'learn by being told' strategy. The system comprises four basic modules, a system administration module, a natural-language concept-comprehension module, a knowledge-classification/extraction module, and a knowledge-incorporation module; details of the module architectures are explored.

Ferber, H. J.↗

NASA NTRS1989

The fault monitoring and diagnosis knowledge-based system for space power systems: AMPERES, phase 1

The objective is to develop a real time fault monitoring and diagnosis knowledge-based system (KBS) for space power systems which can save costly operational manpower and can achieve more reliable space power system operation. The proposed KBS was developed using the Autonomously Managed Power System (AMPS) test facility currently installed at NASA Marshall Space Flight Center (MSFC), but the basic approach taken for this project could be applicable for other space power systems. The proposed KBS is entitled Autonomously Managed Power-System Extendible Real-time Expert System (AMPERES). In Phase 1 the emphasis was put on the design of the overall KBS, the identification of the basic research required, the initial performance of the research, and the development of a prototype KBS. In Phase 2, emphasis is put on the completion of the research initiated in Phase 1, and the enhancement of the prototype KBS developed in Phase 1. This enhancement is intended to achieve a working real time KBS incorporated with the NASA space power system test facilities. Three major research areas were identified and progress was made in each area. These areas are real time data acquisition and its supporting data structure; sensor value validations; development of inference scheme for effective fault monitoring and diagnosis, and its supporting knowledge representation scheme.

Lee, S. C.↗

NASA NTRS1990

KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

Han, Chia Yung↗

NASA NTRS1990

Operations management system

The objective of an operations management system is to provide an orderly and efficient method to operate and maintain aerospace vehicles. Concepts are described for an operations management system and the key technologies are highlighted which will be required if this capability is brought to fruition. Without this automation and decision aiding capability, the growing complexity of avionics will result in an unmanageable workload for the operator, ultimately threatening mission success or survivability of the aircraft or space system. The key technologies include expert system application to operational tasks such as replanning, equipment diagnostics and checkout, global system management, and advanced man machine interfaces. The economical development of operations management systems, which are largely software, will require advancements in other technological areas such as software engineering and computer hardware.

Brandli, A. E.↗

NASA NTRS1991

A failure management prototype: DR/Rx

This failure management prototype performs failure diagnosis and recovery management of hierarchical, distributed systems. The prototype, which evolved from a series of previous prototypes following a spiral model for development, focuses on two functions: (1) the diagnostic reasoner (DR) performs integrated failure diagnosis in distributed systems; and (2) the recovery expert (Rx) develops plans to recover from the failure. Issues related to expert system prototype design and the previous history of this prototype are discussed. The architecture of the current prototype is described in terms of the knowledge representation and functionality of its components.

Hammen, David G.↗

NASA NTRS1992

Numerical, analytical, experimental study of fluid dynamic forces in seals

NASA/Lewis Research Center is sponsoring a program for providing computer codes for analyzing and designing turbomachinery seals for future aerospace and engine systems. The program is made up of three principal components: (1) the development of advanced three dimensional (3-D) computational fluid dynamics codes, (2) the production of simpler two dimensional (2-D) industrial codes, and (3) the development of a knowledge based system (KBS) that contains an expert system to assist in seal selection and design. The first task has been to concentrate on cylindrical geometries with straight, tapered, and stepped bores. Improvements have been made by adoption of a colocated grid formulation, incorporation of higher order, time accurate schemes for transient analysis and high order discretization schemes for spatial derivatives. This report describes the mathematical formulations and presents a variety of 2-D results, including labyrinth and brush seal flows. Extensions of 3-D are presently in progress.

Shapiro, William↗

NASA NTRS1992

HST Servicing Mission Planning and Replanning Tool

An overview is presented of the Hubble Space Telescope (HST) Service Mission Planning and Replanning Tool (SM/PART) and the approach that was employed to develop the system. SM/PART is an AI expert system utilized by NASA to rapidly build complex timelines and command plans to control HST activities. HST servicing missions are Space Shuttle/Orbiter missions expected to occur every three to five years to rendezvous with the HST in orbit and replace, upgrade, or repair HST components. SM/PART runs on a UNIX-based workstation and is implemented in the C language with a Motif-based graphical user interface.

Johnson, J.↗

NASA NTRS1990

The Table of Distribution and Allowances (TDA) system analyzer

TDA documents determine the personnel strengths for each Army installation. They reflect the number of people required to accomplish a certain mission by various characteristics. U.S. Army Training and Doctrine Command (TRADOC) analysts continuously scrutinize these documents to ensure that they comply with provided guidance. Part of this guidance has been used to develop a set of manual rules. Analysts apply these rules to the TDA to eliminate positions, downgrade positions, or reduce position strength. However, this process is very time consuming. ln addition, human involvement introduces inconsistencies and errors that are difficult to detect later. This paper explains how I represented these rules using the 'C' Language Production System (CLIPS) to develop an expert system that is applied consistently and comprehensively for all TRADOC installations. The TDA System Analyzer reduces the review process from about five days to just twenty minutes; giving the user more time to analyze the results and thereby make better decisions. Furthermore, the user is assured that the rules are applied uniformly to every TDA document. This paper also explains the integration of the TDA System Analyzer into TRADOC's On-Line TDA System. Providing the analyst an extra utility module that can be accessed from a familiar environment.

Mack, John F.↗

NASA NTRS1997

Artificial Intelligence and Spacecraft Power Systems

This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

Dugel-Whitehead, Norma R.↗

NASA NTRS2005

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Patterson-Hine, Ann↗

NASA NTRS2010

Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

Kumar, Sujay V.↗

NASA NTRS1993

An Intelligent computer-aided tutoring system for diagnosing anomalies of spacecraft in operation

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Rolincik, Mark↗

NASA NTRS1991

An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.

Quinn, Todd M.↗

NASA NTRS1987

A general architecture for intelligent training systems

A preliminary design of a general architecture for autonomous intelligent training systems was developed. The architecture integrates expert system technology with teaching/training methodologies to permit the production of systems suitable for use by NASA, other government agencies, industry, and academia in the training of personnel for the performance of complex, mission-critical tasks. The proposed architecture consists of five elements: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The design of this architecture was guided and its efficacy tested through the development of a system for use by Mission Control Center Flight Dynamics Officers in training to perform Payload-Assist Module Deploys from the orbiter.

Loftin, R. Bowen↗

NASA NTRS1996

Static and Completion Analysis for Planning Knowledge Base Development and Verification

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

anaylsis techniques↗