4,738 research outputs found
Enabling electronic prognostics using thermal data
Prognostics is a process of assessing the extent of deviation or degradation
of a product from its expected normal operating condition, and then, based on
continuous monitoring, predicting the future reliability of the product. By
being able to determine when a product will fail, procedures can be developed
to provide advanced warning of failures, optimize maintenance, reduce life
cycle costs, and improve the design, qualification and logistical support of
fielded and future systems. In the case of electronics, the reliability is
often influenced by thermal loads, in the form of steady-state temperatures,
power cycles, temperature gradients, ramp rates, and dwell times. If one can
continuously monitor the thermal loads, in-situ, this data can be used in
conjunction with precursor reasoning algorithms and stress-and-damage models to
enable prognostics. This paper discusses approaches to enable electronic
prognostics and provides a case study of prognostics using thermal data.Comment: Submitted on behalf of TIMA Editions
(http://irevues.inist.fr/tima-editions
The nature and evaluation of commercial expert system building tools, revision 1
This memorandum reviews the factors that constitute an Expert System Building Tool (ESBT) and evaluates current tools in terms of these factors. Evaluation of these tools is based on their structure and their alternative forms of knowledge representation, inference mechanisms and developer end-user interfaces. Next, functional capabilities, such as diagnosis and design, are related to alternative forms of mechanization. The characteristics and capabilities of existing commercial tools are then reviewed in terms of these criteria
Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph
Police SWAT teams and Military Special Forces face mounting pressure and
challenges from adversaries that can only be resolved by way of ever more
sophisticated inputs into tactical operations. Lethal Autonomy provides
constrained military/security forces with a viable option, but only if
implementation has got proper empirically supported foundations. Autonomous
weapon systems can be designed and developed to conduct ground, air and naval
operations. This monograph offers some insights into the challenges of
developing legal, reliable and ethical forms of autonomous weapons, that
address the gap between Police or Law Enforcement and Military operations that
is growing exponentially small. National adversaries are today in many
instances hybrid threats, that manifest criminal and military traits, these
often require deployment of hybrid-capability autonomous weapons imbued with
the capability to taken on both Military and/or Security objectives. The
Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of
Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that
required military response and police investigations against a fighting cell of
the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade
Operational efficiency subpanel advanced mission control
Herein, the term mission control will be taken quite broadly to include both ground and space based operations as well as the information infrastructure necessary to support such operations. Three major technology areas related to advanced mission control are examined: (1) Intelligent Assistance for Ground-Based Mission Controllers and Space-Based Crews; (2) Autonomous Onboard Monitoring, Control and Fault Detection Isolation and Reconfiguration; and (3) Dynamic Corporate Memory Acquired, Maintained, and Utilized During the Entire Vehicle Life Cycle. The current state of the art space operations are surveyed both within NASA and externally for each of the three technology areas and major objectives are discussed from a user point of view for technology development. Ongoing NASA and other governmental programs are described. An analysis of major research issues and current holes in the program are provided. Several recommendations are presented for enhancing the technology development and insertion process to create advanced mission control environments
The 1990 progress report and future plans
This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers
Space Station Freedom automation and robotics: An assessment of the potential for increased productivity
This report presents the results of a study performed in support of the Space Station Freedom Advanced Development Program, under the sponsorship of the Space Station Engineering (Code MT), Office of Space Flight. The study consisted of the collection, compilation, and analysis of lessons learned, crew time requirements, and other factors influencing the application of advanced automation and robotics, with emphasis on potential improvements in productivity. The lessons learned data collected were based primarily on Skylab, Spacelab, and other Space Shuttle experiences, consisting principally of interviews with current and former crew members and other NASA personnel with relevant experience. The objectives of this report are to present a summary of this data and its analysis, and to present conclusions regarding promising areas for the application of advanced automation and robotics technology to the Space Station Freedom and the potential benefits in terms of increased productivity. In this study, primary emphasis was placed on advanced automation technology because of its fairly extensive utilization within private industry including the aerospace sector. In contrast, other than the Remote Manipulator System (RMS), there has been relatively limited experience with advanced robotics technology applicable to the Space Station. This report should be used as a guide and is not intended to be used as a substitute for official Astronaut Office crew positions on specific issues
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
Attitude Determination and Control System (ADCS) and Maintenance and Diagnostic System (MDS): A maintenance and diagnostic system for Space Station Freedom
The Maintenance and Diagnostic System (MDS) that is being developed at Honeywell to enhance the Fault Detection Isolation and Recovery system (FDIR) for the Attitude Determination and Control System on Space Station Freedom is described. The MDS demonstrates ways that AI-based techniques can be used to improve the maintainability and safety of the Station by helping to resolve fault anomalies that cannot be fully determined by built-in-test, by providing predictive maintenance capabilities, and by providing expert maintenance assistance. The MDS will address the problems associated with reasoning about dynamic, continuous information versus only about static data, the concerns of porting software based on AI techniques to embedded targets, and the difficulties associated with real-time response. An initial prototype was built of the MDS. The prototype executes on Sun and IBM PS/2 hardware and is implemented in the Common Lisp; further work will evaluate its functionality and develop mechanisms to port the code to Ada
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