77,424 research outputs found

    Monitoring Agents for Assisting NASA Engineers with Shuttle Ground Processing

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    The Spaceport Processing Systems Branch at NASA Kennedy Space Center has designed, developed, and deployed a rule-based agent to monitor the Space Shuttle's ground processing telemetry stream. The NASA Engineering Shuttle Telemetry Agent increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when user defined conditions are satisfied. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the agent's rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules within this domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This chapter discusses the rule-based telemetry agent used for Space Shuttle ground processing. We present the problem domain along with design and development considerations such as information modeling, knowledge capture, and the deployment of the product. We also present ongoing work with other condition monitoring agents

    Expert System for UNIX System Reliability and Availability Enhancement

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    Highly reliable and available systems are critical to the airline industry. However, most off-the-shelf computer operating systems and hardware do not have built-in fault tolerant mechanisms, the UNIX workstation is one example. In this research effort, we have developed a rule-based Expert System (ES) to monitor, command, and control a UNIX workstation system with hot-standby redundancy. The ES on each workstation acts as an on-line system administrator to diagnose, report, correct, and prevent certain types of hardware and software failures. If a primary station is approaching failure, the ES coordinates the switch-over to a hot-standby secondary workstation. The goal is to discover and solve certain fatal problems early enough to prevent complete system failure from occurring and therefore to enhance system reliability and availability. Test results show that the ES can diagnose all targeted faulty scenarios and take desired actions in a consistent manner regardless of the sequence of the faults. The ES can perform designated system administration tasks about ten times faster than an experienced human operator. Compared with a single workstation system, our hot-standby redundancy system downtime is predicted to be reduced by more than 50 percent by using the ES to command and control the system

    Representation and matching of knowledge to design digital systems

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    A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described

    Performance comparison between PID and fuzzy logic controller in position control system of dc servomotor

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    The objective of this paper is to compare the time specification performance between conventional controller and artificial intelligence controller in position control system of a DC motor. This will include design and development of a GUI software using Microsoft Visual Basic 6.0 for position control system experiment. The scope of this research is to apply direct digital control technique in position control system. Two types of controller namely PID and fuzzy logic controller will be used to control the output response. An interactive software will be developed to visualize and analyze the system. This project consists of hardware equipment and software design. The hardware parts involve in interfacing MS150 Modular servo System and Data Acquisition System with a personal computer. The software part includes programming real-time software using Microsoft Visual Basic 6.0. Finally, the software will be integrated with hardware to produce a GUI position control system

    Process-Based Design and Integration of Wireless Sensor Network Applications

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    Abstract Wireless Sensor and Actuator Networks (WSNs) are distributed sensor and actuator networks that monitor and control real-world phenomena, enabling the integration of the physical with the virtual world. They are used in domains like building automation, control systems, remote healthcare, etc., which are all highly process-driven. Today, tools and insights of Business Process Modeling (BPM) are not used to model WSN logic, as BPM focuses mostly on the coordination of people and IT systems and neglects the integration of embedded IT. WSN development still requires significant special-purpose, low-level, and manual coding of process logic. By exploiting similarities between WSN applications and business processes, this work aims to create a holistic system enabling the modeling and execution of executable processes that integrate, coordinate, and control WSNs. Concretely, we present a WSNspecific extension for Business Process Modeling Notation (BPMN) and a compiler that transforms the extended BPMN models into WSN-specific code to distribute process execution over both a WSN and a standard business process engine. The developed tool-chain allows modeling of an independent control loop for the WSN.

    Parallel processing and expert systems

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    Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited

    Parallel processing and expert systems

    Get PDF
    Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited
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