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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Expert systems for adaptive control of large space structures

It is expected that space systems for the future will evolve to structures of unprecedented size with associated extreme control requirements. A method is necessary that is sufficiently general to initiate stable control of a vehicle and subsequently learn the true nature of the structure. It is suggested that a suitable constructed expert system (ES) would be capable of learning by appending observations to a knowledge base. To verify that an ES can control a large space structure, numerical simulations of a simple structure subjected to periodic vibrations and the performance of a classical controllers were performed. The ES was then exercised to show its ability to truthfully mimic nominal control and to demonstrate its superiority to the classical controller, given sensor failures. An ES generating software package, The Intelligent Machine Model, was employed. It uses the pattern matching technique. Results of this program are discussed.

Gartrell, Charles F.↗
NASA NTRS1990

Space communications scheduler: A rule-based approach to adaptive deadline scheduling

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

Straguzzi, Nicholas↗
NASA NTRS1990

Parallelism in backward-chained expert systems - Experimental results

There are many applications which may be done by an expert system in real time, if the system is capable of real-time response. The LISP and PROLOG-based expert systems have typically been too slow for real-time response. This has led to an effort to use other languages, the development of fast pattern matching techniques and other methods of improving the speed of expert systems. Another approach to developing faster expert systems is to make use of the emerging parallel processing computer technology. A further use for parallelism is to allow reasonable response time for large knowledge bases. The size of knowledge bases may become as large as 20,000 chunks of knowledge (and more) in the near future in medical and space applications. This paper describes the use of parallel processing in the EMYCIN backward chained rule-based model.

Hall, Lawrence O.↗
NASA NTRS1994

Vision based object pose estimation for mobile robots

Mobile robot navigation using visual sensors requires that a robot be able to detect landmarks and obtain pose information from a camera image. This paper presents a vision system for finding man-made markers of known size and calculating the pose of these markers. The algorithm detects and identifies the markers using a weighted pattern matching template. Geometric constraints are then used to calculate the position of the markers relative to the robot. The selection of geometric constraints comes from the typical pose of most man-made signs, such as the sign standing vertical and the dimensions of known size. This system has been tested successfully on a wide range of real images. Marker detection is reliable, even in cluttered environments, and under certain marker orientations, estimation of the orientation has proven accurate to within 2 degrees, and distance estimation to within 0.3 meters.

Wu, Annie↗
NASA NTRS1994

Microwave vision for robots

Microwave Vision (MV), a concept originally developed in 1985, could play a significant role in the solution to robotic vision problems. Originally our Microwave Vision concept was based on a pattern matching approach employing computer based stored replica correlation processing. Artificial Neural Network (ANN) processor technology offers an attractive alternative to the correlation processing approach, namely the ability to learn and to adapt to changing environments. This paper describes the Microwave Vision concept, some initial ANN-MV experiments, and the design of an ANN-MV system that has led to a second patent disclosure in the robotic vision field.

Lewandowski, Leon↗
NASA NTRS1992

Measurement of two-dimensional fluid flow by digital correlation of scattered light

Digital correlation is a pattern matching procedure. This procedure has recently been used in two-dimensional fluid flow measurements. Two images of a seeded fluid are taken and the intensity distribution of a small window in the first image is matched in the second image using a statistical correlation method. A series of structure functions have been implemented to improve the accuracy and reliability of the correlation method and new algorithms have been developed to reduce the time required for the correlation computations.

Matthys, Donald R.↗
NASA NTRS1990

Building engineering expert systems in CLIPS

This paper is intended for CLIPS developers with a working knowledge of expert systems and the CLIPS syntax. It discusses Rete pattern matching and rule-fact interaction, explains several development and debug techniques, and gives advice on compiling CLIPS and knowledge bases. The techniques apply to CLIPS versions 4.2 and 4.3, especially in the PC/DOS environment. Two examples developed by the author are analyzed and compared.

Porter, Ken↗
NASA NTRS1990

Fault-tolerant, embedded CLIPS applications

The enhancements to CLIPS4.3 presented in this paper provide an embedded CLIPS application with the ability to continue operation with minimal to no loss of information in the event of a hardware or a software failure. Given an arbitrary failure, the CLIPS application's environment (fact-list, agenda, and pattern matching network) will be reconstructed to the point at which the failure was experienced. The environment reconstruction is based on state files to which the application periodically checks environment information (fact-list and agenda). The routine for checkpointing the state of the application is as efficient as possible so that the overhead introduced to normal execution of the application is minimal. The only assumptions made by the CLIPS application are that it is running under an operating system that guarantees it access to uncorrupt state files and that the application will be automatically restarted should it terminate abnormally.

Hicks, Jaye↗
NASA NTRS1990

CLIPS: A tool for corn disease diagnostic system and an aid to neural network for automated knowledge acquisition

This paper describes the building of a corn disease diagnostic expert system using CLIPS, and the development of a neural expert system using the fact representation method of CLIPS for automated knowledge acquisition. The CLIPS corn expert system diagnoses 21 diseases from 52 symptoms and signs with certainty factors. CLIPS has several unique features. It allows the facts in rules to be broken down to object-attribute-value (OAV) triples, allows rule-grouping, and fires rules based on pattern-matching. These features combined with the chained inference engine result to a natural user query system and speedy execution. In order to develop a method for automated knowledge acquisition, an Artificial Neural Expert System (ANES) is developed by a direct mapping from the CLIPS system. The ANES corn expert system uses the same OAV triples in the CLIPS system for its facts. The LHS and RHS facts of the CLIPS rules are mapped into the input and output layers of the ANES, respectively; and the inference engine of the rules is imbedded in the hidden layer. The fact representation by OAC triples gives a natural grouping of the rules. These features allow the ANES system to automate rule-generation, and make it efficient to execute and easy to expand for a large and complex domain.

Wu, Cathy↗
NASA NTRS1990

CLIPS meets the connection machine: Or how to create a parallel production system

Production systems usually present unacceptable run-times when faced with applications requiring tens of thousands to millions of facts. Many efforts have focused on the use of parallelism as a way to increase overall system performance. While these efforts have increased pattern matching and rule evaluation rates, they have only indirectly dealt with the problems faced by fact burdened applications. We have implemented PPS, a version of CLIPS running on the Connection Machine, to directly address the problems faced by these applications. This paper will describe our system, discuss its implementation, and present results.

Geyer, Steve↗
NASA NTRS1989

SSME fault monitoring and diagnosis expert system

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Ali, Moonis↗
NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies 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. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗
NASA NTRS1997

Automated navigation assessment for earth survey sensors using island targets

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Patt, Frederick S.↗
NASA NTRS1997

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Patt, F. S.↗
NASA NTRS1993

Seminar Software

The Society for Computer Simulation International is a professional technical society that distributes information on methodology techniques and uses of computer simulation. The society uses NETS, a NASA-developed program, to assist seminar participants in learning to use neural networks for computer simulation. NETS is a software system modeled after the human brain; it is designed to help scientists exploring artificial intelligence to solve pattern matching problems. Examples from NETS are presented to seminar participants, who can then manipulate, alter or enhance them for their own applications.

Source record↗
NASA NTRS1989

Expert System Software

C Language Integrated Production System (CLIPS) is a software shell for developing expert systems is designed to allow research and development of artificial intelligence on conventional computers. Originally developed by Johnson Space Center, it enables highly efficient pattern matching. A collection of conditions and actions to be taken if the conditions are met is built into a rule network. Additional pertinent facts are matched to the rule network. Using the program, E.I. DuPont de Nemours & Co. is monitoring chemical production machines; California Polytechnic State University is investigating artificial intelligence in computer aided design; Mentor Graphics has built a new Circuit Synthesis system, and Brooke and Brooke, a law firm, can determine which facts from a file are most important.

Source record↗
NASA NTRS2000

Ventilation-perfusion matching in long-term microgravity

We studied the ventilation-perfusion matching pattern in normal gravity (1 G) and short- and long-duration microgravity (microG) using the cardiogenic oscillations in the sulfur hexaflouride (SF(6)) and CO(2) concentration signals during the phase III portion of vital capacity single-breath washout experiments. The signal power of the cardiogenic concentration variations was assessed by spectral analysis, and the phase angle between the oscillations of the two simultaneously expired gases was obtained through cross-correlation. For CO(2), a significant reduction of cardiogenic power was observed in microG, with respect to 1 G, but the reduction was smaller and more variable in the case of SF(6). A shift from an in-phase condition in 1 G to an out-of-phase condition was found for both short- and long-duration microG. We conclude that, although the distribution of ventilation and perfusion becomes more homogeneous in microG, significant inhomogeneities persist and that areas of high perfusion become associated with areas of relatively lower ventilation. In addition, these modifications seem to remain constant during long-term exposure to microG.

Mir Project↗