Design of a Knowledge-Based Fault Detection and Diagnosis System,

Abstract

This paper presents a design of a knowledge-based fault detection and diagnosis (FDD) component intended to function as part of an intelligent processor (agent) in a distributed problem solving system. This component will permit the system to monitor its own behavior, detect an abnormal system rate, and identify the fault that caused it. Once the fault is identified, the system can repair it or reconfigure itself, thus improving its performance. The heart of the FDD component is a model of the system it is monitoring. This model represents the correct behavior of the system and the criteria for detecting deviations from this behavior. Thus it integrates information necessary for detection and diagnosis into a uniform structure. Detection is accomplished by monitoring the system state and detecting situations which violate the predefined expectations. Diagnosis is accomplished by constructing a representation of the current system state and determining the earliest points of departure from the expected behavior as represented by the correct system model. These points constitute the identified faults. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 20, 1984
Accession Number
ADA148859

Entities

People

  • E. Hudlicka
  • V. Lesser

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Detection
  • Acoustic Detectors
  • Artificial Intelligence
  • Complex Systems
  • Consistency
  • Databases
  • Detection
  • Detectors
  • Environment
  • Errors
  • Fault Tolerance
  • Hierarchies
  • Hypotheses
  • Intelligent Agents
  • Load Distribution
  • Vehicles

Fields of Study

  • Engineering

Readers

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  • Software Engineering.