Object-Oriented Dynamic Bayesian Network-Templates for Modelling Mechatronic Systems

Abstract

The object-oriented paradigm is a new but proven technology for modelling mechatronics, i.e., multidisciplinary modelling. For many reasons the object-oriented approach is very much desirable also for qualitative models in system design, diagnosis or verification. Bayesian networks are a very robust technology for qualitative probabilistic modelling. In this paper we present a first approach in using the Bayesian networks modelling technique with the quantitative object-oriented method. Analogous to Modelica, an object-oriented modelling language, we constructed a Bayesian network library for modelling hydraulic systems. These Bayesian networks are called Object Oriented Dynamic Bayes Nets (OODBNs). Our method is easily transferable to any other physical domain or logic. In this contribution our motivation and the construction steps are described. Simulation results for a sample hydraulic system are given.

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Document Details

Document Type
Technical Report
Publication Date
May 04, 2002
Accession Number
ADP012707

Entities

People

  • Harald Renninger
  • Hermann Von Hasseln

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Bayesian Networks
  • Computational Science
  • Computer Programs
  • Control Systems Engineering
  • Differential Equations
  • Engineering
  • Equations
  • Flow
  • Information Science
  • Language
  • Libraries
  • Models
  • Probability
  • Probability Distributions
  • Simulations

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference