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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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Welding force monitored in process. Electronic force gage uses strain gage on deformable member. Oscilloscope trace of welding force photographed and compared with standard trace during calibration and troubleshooting of resistance welding equipment. Adaptable to small scale resistance welding in electronics industry.
Provisions for back-up operations for the satellite freeze forecast system are discussed including software and hardware maintenance and DS/1000-1V linkage; troubleshooting; and digitized radar usage. The documentation developed; dissemination of data products via television and the IFAS computer network; data base management; predictive models; the installation of and progress towards the operational status of key stations; and digital data acquisition are also considered. The d addition of dew point temperature into the P-model is outlined.
An experimental tool for the investigation of human problem-solving behavior is introduced. Production Levels and Network Troubleshooting (PLANT) is a computer-based process-control task which may be used to provide opportunities for subjects to control a dynamic system and diagnose, repair, and compensate for system failures. The task is described in detail, and experiments which have been conducted using PLANT are briefly discussed.
The Lox Expert System (LES) is the first attempt to build a realtime expert system capable of simulating the thought processes of NASA system engineers, with regard to fluids systems analysis and troubleshooting. An overview of the hardware and software describes the techniques used, and possible applications to other process control systems. LES is now in the advanced development stage, with a full implementation planned for late 1985.
The Synchronous Data Analyzer gives its user an independent source for checking the validity of raw MDDF and LTAS data. Its ability to produce real-time displays comprised of decoded parameters as well as its ability to capture several frames for non-real-time display makes it a valuable tool for monitoring and troubleshooting applications involving these data formats. Its composition of portable firmware and mostly commercial hardware makes it a low cost, easily fabricated product.
Results are described from a project to build a prototype expert system for automated fault isolation and correction of a regenerative CO2 removal device that is typical of functions of the air revitalization group in the Space Station environmental control and life support system (ECLSS). The software was developed using one of the powerful commercial knowledge engineering environments. The goal of the project was to evaluate the feasibility of using a software development environment to rapidly design, construct, test, and change expert system software. The use of expert systems to enhance automatic controllers and the use of information on device design and on device troubleshooting and repair procedures in developing expert systems are discussed.
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.
In the past few years many flight control systems have been implemented as full-authority, full-time digital systems. The digital design has allowed flight control systems to make use of many enhanced elements that are generally considered too complex to implement in an analog system. Examples of these elements are redundant information exchanged between channels to allow for continued operation after multiple failures and multiple variable gain schedules to optimize control of the aircraft throughout its flight envelope and in all flight modes. The introduction of the digital system for flight control also created the problem of obtaining information from the system in an understandable and useful format. This paper presents how the X-29A was dealt with during its operations at NASA Ames-Dryden Flight Research Facility. A brief description of the X-29A control system, a discussion of the tools developed to aid in daily operations, and the troubleshooting of the aircraft are included.
This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.
The authors present a technique for structural abstraction applicable to the domain of pressurized hydraulic systems. Valves, when closed, functionally isolate clusters of components; when opened, neighboring clusters are merged. A cluster can only be in the one of two qualitative states-stable, where pressures are equal throughout and no flow occurs, or unstable, where flow from high-pressure source(s) to low-pressure sink(s) occurs. Reasoning in terms of clusters is shown to facilitate the generation and explanation of plans for operating and troubleshooting hydraulic systems.
An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987).
The NASA Lewis Research Center has developed and implemented a time-efficient methodology for dynamically balancing turbomachinery shafting. This methodology minimizes costly facility downtime by using a balancing arbor (mandrel) that simulates the turbomachinery (rig) shafting. The need for precision dynamic balancing of turbomachinery shafting and for a dynamic balancing methodology is discussed in detail. Additionally, the inherent problems (and their causes and effects) associated with unbalanced turbomachinery shafting as a function of increasing shaft rotational speeds are discussed. Included are the design criteria concerning rotor weight differentials for rotors made of different materials that have similar parameters and shafting. The balancing methodology for applications where rotor replaceability is a requirement is also covered. This report is intended for use as a reference when designing, fabricating, and troubleshooting turbomachinery shafting.
The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.
Calibration devices for the Forward Scattering Spectrometer Probe (FSSP) and the Optical Array Probe (OAP) were developed. The device used with the FSSP is a rotating pinhole calibrator. It utilizes light diffracted by a pinhole of a known diameter to simulate scattered light from a water droplet. This device can be used to calibrate the FSSP, measure the FSSP's optical collection angles and for instrument alignment and troubleshooting. The device used with the OAP is a rotating reticle calibrator. Chrome disks of a known diameter on the reticle are used for calibration of the OAP and for determining the OAP's response to out-of-focus particles in the probe volume.
The goal of the Astronaut Science Advisor (ASA) project is to improve the scientific return of experiments performed in space by providing astronaut experimenters with an 'intelligent assistant' that encapsulates much of the domain- and experiment-related knowledge commanded by the Principal Investigator (PI) on the ground. By using expert systems technology and the availability of flight-qualified personal computers, it is possible to encode the requisite knowledge and make it available to astronauts as they perform experiments in space. The system performs four major functions: diagnosis and troubleshooting of experiment apparatus, data collection, protocol management, and detection of interesting data. The experiment used for development of the system measures human adaptation to weightlessness in the context of the neurovestibular system. This so-called 'Rotating Dome' experiment was flown on the recent Spacelab Life Sciences One (SLS-1) Mission. This mission was used as an opportunity to test some of the system's functionality. Experiment data was downlinked from the orbiter, and the system then captured the data and analyzed it in real time. The system kept track of the time being used by the experiment, recognized occurrences of interesting data, summarized data statistically and generated potential new protocols that could be used to optimize the course of the experiment.
Principal Investigator (PI) in a box is a computer system designed to help optimize the scientific results of experiments that are performed in space. The system will assist the astronaut experimenters in the collection and analysis of experimental data, recognition and pursuit of 'interesting' results, optimal use of the time allocated to the experiment, and troubleshooting of the experiment apparatus. This document discusses the problems that motivate development of 'PI-in-a-box', and presents a high- level system overview and a detailed description of each of the modules that comprise the current version of the system.
An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.
Fault isolation and sensor placement are vital for monitoring and diagnosis. A sensor conveys information about a system's state that guides troubleshooting if problems arise. We are using machine learning methods to uncover behavioral patterns over snapshots of system simulations that will aid fault isolation and sensor placement, with an eye towards minimality, fault coverage, and noise tolerance.