Model-Based Monitoring of Piecewise Continuous Behaviors using Dynamic Uncertainty Space Partitioning

Abstract

Monitoring gains importance for many technical systems such as robots, production lines or anti lock brakes. A monitoring system for technical systems must be able to deal with incomplete knowledge of the supervised system, to process noisy observations and to react within predefined time windows. This paper presents a new approach to monitoring technical systems based on imprecise models. Our approach repeatedly partitions the uncertainty space of an imprecise model and checks the derived model's state for consistency with the measurements. Inconsistent partitions are then refuted resulting in a smaller uncertainty space and a faster failure detection. This paper further focuses on the extension of our basic approach to monitoring systems that exhibit both continuous and discrete behaviors. Our monitoring system has been implemented using COTS components and has been demonstrated in online monitoring of a non-trivial heating system.

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Document Details

Document Type
Technical Report
Publication Date
May 04, 2002
Accession Number
ADP012706

Entities

People

  • Bernhard Rinner
  • Ulrich Weiss

Organizations

  • University of Graz

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Computer Simulations
  • Consistency
  • Damage Detection
  • Detection
  • Differential Equations
  • Equations
  • Heating
  • Heating Elements
  • Identification
  • Intervals
  • Linear Systems
  • Measurement
  • Monitoring
  • Simulations
  • Thermal Conductivity

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space