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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Intelligent fault management for the Space Station active thermal control system

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Hill, Tim↗
NASA NTRS1990

CLIPS interface development tools and their application

A package of C-based PC user interface development functions has been developed and integrated into CLIPS. The primary function is ASK which provides a means to ask the user questions via multiple choice menus or the keyboard and then returns the user response to CLIPS. A parameter-like structure supplies information for the interface. Another function, SHOW, provides a means to paginate and display text. A third function, TITLE, formats and displays title screens. A similar set of C-based functions that are more general and thus will run on UNIX and machines have also been developed. Seven expert system applications were transformed from commercial development environments into CLIPS and utilize ASK, SHOW, and TITLE. Development of numerous new expert system applications using CLIPS and these interface functions has started. These functions greatly reduce the time required to build interfaces for CLIPS applications.

Engel, Bernard A.↗
NASA NTRS1988

Knowledge-based network operations

An expert system for enhancing the operability of the ground communication element of the Jet Propulsion Laboratory's Deep Space Network is described. The system performs network fault management, configuration management, and performance management in real time. Extracted management information serves as input to the expert system and is used to update a management information data base. The monitor and control activities involve dividing software for each processor into layers which are each modeled as a finite state machine.

Wu, Chuan-Lin↗
NASA NTRS1989

Classification of data patterns using an autoassociative neural network topology

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Dietz, W. E.↗
NASA NTRS1990

Inductive knowledge acquisition experience with commercial tools for space shuttle main engine testing

Since 1984, an effort has been underway at Rocketdyne, manufacturer of the Space Shuttle Main Engine (SSME), to automate much of the analysis procedure conducted after engine test firings. Previously published articles at national and international conferences have contained the context of and justification for this effort. Here, progress is reported in building the full system, including the extensions of integrating large databases with the system, known as Scotty. Inductive knowledge acquisition has proven itself to be a key factor in the success of Scotty. The combination of a powerful inductive expert system building tool (ExTran), a relational data base management system (Reliance), and software engineering principles and Computer-Assisted Software Engineering (CASE) tools makes for a practical, useful and state-of-the-art application of an expert system.

Modesitt, Kenneth L.↗
NASA NTRS1987

Mixed-initiative control of intelligent systems

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data.

Borchardt, G. C.↗
NASA NTRS1992

Min and max are the only continuous ampersand-, V-operations for finite logics

Experts usually express their degrees of belief in their statements by the words of a natural language (like 'maybe', 'perhaps', etc.). If an expert system contains the degrees of beliefs t(A) and t(B) that correspond to the statements A and B, and a user asks this expert system whether 'A&B' is true, then it is necessary to come up with a reasonable estimate for the degree of belief of A&B. The operation that processes t(A) and t(B) into such an estimate t(A&B) is called an &-operation. Many different &-operations have been proposed. Which of them to choose? This can be (in principle) done by interviewing experts and eliciting a &-operation from them, but such a process is very time-consuming and therefore, not always possible. So, usually, to choose a &-operation, the finite set of actually possible degrees of belief is extended to an infinite set (e.g., to an interval (0,1)), define an operation there, and then restrict this operation to the finite set. Only this original finite set is considered. It is shown that a reasonable assumption that an &-operation is continuous (i.e., that gradual change in t(A) and t(B) must lead to a gradual change in t(A&B)), uniquely determines min as an &-operation. Likewise, max is the only continuous V-operation. These results are in good accordance with the experimental analysis of 'and' and 'or' in human beliefs.

Kreinovich, Vladik↗
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 NTRS1999

Principal Investigator-in-a-Box

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Young, Laurence R.↗
NASA NTRS1988

Center for Advanced Space Propulsion (CASP)

With a mission to initiate and conduct advanced propulsion research in partnership with industry, and a goal to strengthen U.S. national capability in propulsion technology, the Center for Advanced Space Propulsion (CASP) is the only NASA Center for Commercial Development of Space (CCDS) which focuses on propulsion and associated technologies. Meetings with industrial partners and NASA Headquarters personnel provided an assessment of the constraints placed on, and opportunities afforded commercialization projects. Proprietary information, data rights, and patent rights were some of the areas where well defined information is crucial to project success and follow-on efforts. There were five initial CASP projects. At the end of the first year there are six active, two of which are approaching the ground test phase in their development. Progress in the current six projects has met all milestones and is detailed. Working closely with the industrial counterparts it was found that the endeavors in expert systems development, computational fluid dynamics, fluid management in microgravity, and electric propulsion were well received. One project with the Saturn Corporation which dealt with expert systems application in the assembly process, was placed on hold pending further direction from Saturn. The Contamination Measurment and Analysis project was not implemented since CASP was unable to identify an industrial participant. Additional propulsion and related projects were investigated during the year. A subcontract was let to a small business, MicroCraft, Inc., to study rocket engine certification standards. The study produced valuable results; however, based on a number of factors it was decided not to pursue this project further.

Source record↗
NASA NTRS1993

Advancing satellite operations with intelligent graphical monitoring systems

For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

Hughes, Peter M.↗
NASA NTRS1990

Artificial intelligence techniques for ground test monitoring of rocket engines

An expert system is being developed which can detect anomalies in Space Shuttle Main Engine (SSME) sensor data significantly earlier than the redline algorithm currently in use. The training of such an expert system focuses on two approaches which are based on low frequency and high frequency analyses of sensor data. Both approaches are being tested on data from SSME tests and their results compared with the findings of NASA and Rocketdyne experts. Prototype implementations have detected the presence of anomalies earlier than the redline algorithms that are in use currently. It therefore appears that these approaches have the potential of detecting anomalies early eneough to shut down the engine or take other corrective action before severe damage to the engine occurs.

Ali, Moonis↗
NASA NTRS1989

DAWN (Design Assistant Workstation) for advanced physical-chemical life support systems

This paper reports the results of a project supported by the National Aeronautics and Space Administration, Office of Aeronautics and Space Technology (NASA-OAST) under the Advanced Life Support Development Program. It is an initial attempt to integrate artificial intelligence techniques (via expert systems) with conventional quantitative modeling tools for advanced physical-chemical life support systems. The addition of artificial intelligence techniques will assist the designer in the definition and simulation of loosely/well-defined life support processes/problems as well as assist in the capture of design knowledge, both quantitative and qualitative. Expert system and conventional modeling tools are integrated to provide a design workstation that assists the engineer/scientist in creating, evaluating, documenting and optimizing physical-chemical life support systems for short-term and extended duration missions.

Rudokas, Mary R.↗
NASA NTRS1991

Automated power management and control

A comprehensive automation design is being developed for Space Station Freedom's electric power system. A joint effort between NASA's Office of Aeronautics and Exploration Technology and NASA's Office of Space Station Freedom, it strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. The initial station operation will use ground-based dispatches to perform the necessary command and control tasks. These tasks constitute planning and decision-making activities that strive to eliminate unplanned outages. We perceive an opportunity to help these dispatchers make fast and consistent on-line decisions by automating three key tasks: failure detection and diagnosis, resource scheduling, and security analysis. Expert systems will be used for the diagnostics and for the security analysis; conventional algorithms will be used for the resource scheduling.

Dolce, James L.↗
NASA NTRS1990

A knowledge-based approach to configuration layout, justification, and documentation

The design, development, and implementation is described of a prototype expert system which could aid designers and system engineers in the placement of racks aboard modules on Space Station Freedom. This type of problem is relevant to any program with multiple constraints and requirements demanding solutions which minimize usage of limited resources. This process is generally performed by a single, highly experienced engineer who integrates all the diverse mission requirements and limitations, and develops an overall technical solution which meets program and system requirements with minimal cost, weight, volume, power, etc. This system architect performs an intellectual integration process in which the underlying design rationale is often not fully documented. This is a situation which lends itself to an expert system solution for enhanced consistency, thoroughness, documentation, and change assessment capabilities.

Craig, F. G.↗
NASA NTRS1991

A Knowledge-Based Approach to Configuration Layout, Justification, and Documentation

The design, development, and implementation of a prototype expert system which could aid designers and system engineers in the placement of racks aboard modules on the Space Station Freedom are described. This type of problem is relevant to any program with multiple constraints and requirements demanding solutions which minimize usage of limited resources. This process is generally performed by a single, highly experienced engineer who integrates all the diverse mission requirements and limitations, and develops an overall technical solution which meets program and system requirements with minimal cost, weight, volume, power, etc. This system architect performs an intellectual integration process in which the underlying design rationale is often not fully documented. This is a situation which lends itself to an expert system solution for enhanced consistency, thoroughness, documentation, and change assessment capabilities.

Craig, F. G.↗
NASA NTRS1990

An object oriented generic controller using CLIPS

In today's applications, the need for the division of code and data has focused on the growth of object oriented programming. This philosophy gives software engineers greater control over the environment of an application. Yet the use of object oriented design does not exclude the need for greater understanding by the application of what the controller is doing. Such understanding is only possible by using expert systems. Providing a controller that is capable of controlling an object by using rule-based expertise would expedite the use of both object oriented design and expert knowledge of the dynamic of an environment in modern controllers. This project presents a model of a controller that uses the CLIPS expert system and objects in C++ to create a generic controller. The polymorphic abilities of C++ allow for the design of a generic component stored in individual data files. Accompanying the component is a set of rules written in CLIPS which provide the following: the control of individual components, the input of sensory data from components and the ability to find the status of a given component. Along with the data describing the application, a set of inference rules written in CLIPS allows the application to make use of sensory facts and status and control abilities. As a demonstration of this ability, the control of the environment of a house is provided. This demonstration includes the data files describing the rooms and their contents as far as devices, windows and doors. The rules used for the home consist of the flow of people in the house and the control of devices by the home owner.

Nivens, Cody R.↗
NASA NTRS1983

Manned spaceflight activity planning with knowledge-based systems

An on-board expert system, capable of assisting with crew-activity planning and platform-status monitoring, could provide unprecedented autonomy to the crew of a permanently manned space station. To demonstrate this concept's feasibility, an existing knowledge-based system is adapted to support Space Shuttle crew-activity timeline planning. Proposed timeline changes are to be checked for compliance with crew capabilities and mission operating guidelines, so that a nonexpert can be guided through a successful plan modification. Early lessons that have been learned about the scope of the adaptation needed to achieve this objective are presented.

Mogilensky, J.↗