Hybrid Modeling and Diagnosis in the Real World: A Case Study

Abstract

Applying model-based diagnosis techniques to systems that exhibit hybrid behavior presents an interesting set of challenges that mostly revolve around interactions of the continuous and discrete components of the system. In many real world systems, the overall physical plant is inherently continuous, but system control is performed by a supervisory controller that imposes discrete switching behaviors by reconfiguring the system components, or switching controllers. In this paper, we present a case study of an aircraft fuel system, and discuss methodologies for building system models for online tracking of system behavior and performing fault isolation and identification. Empirical studies are performed on detection and isolation for a set of pump and pipe failures.

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Document Details

Document Type
Technical Report
Publication Date
May 04, 2002
Accession Number
ADP012687

Entities

People

  • Gabor Karsai
  • Gautam Biswas
  • Sriram Narasimhan
  • Tim Bowman
  • Tivadar Szemethy

Organizations

  • Vanderbilt University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Applied Mathematics
  • Case Studies
  • Complex Systems
  • Computational Complexity
  • Computer Programs
  • Control Systems
  • Control Systems Engineering
  • Detection
  • Detectors
  • Equations
  • Equations Of State
  • Experimental Data
  • Failure Mode And Effect Analysis
  • Fuel Systems
  • Hybrid Systems

Fields of Study

  • Computer science
  • Engineering

Readers

  • Integrated Circuit Design and Technology.
  • Neural Network Machine Learning.
  • Systems Analysis and Design