A Toolbox for Analysis and Design of Model Based Diagnosis Systems for Large Scale Models
To facilitate the use of advanced fault diagnosis analysis and design
techniques to industrial sized systems, there is a need for computer
support. This paper describes a Matlab toolbox and evaluates the
software on a challenging industrial problem, air-path diagnosis in an
automotive engine. The toolbox includes tools for analysis and design
of model based diagnosis systems for large-scale differential
algebraic models. The software package supports a complete tool-chain
from modeling a system to generating C-code for residual
generators. Major design steps supported by the tool are modeling,
fault diagnosability analysis, sensor selection, residual generator
analysis, test selection, and code generation. Structural methods
based on efficient graph theoretical algorithms are used in several
steps. In the automotive diagnosis example, a diagnosis system is
generated and evaluated using measurement data, both in fault-free
operation and with faults injected in the control-loop. The results
clearly show the benefit of the toolbox in a model-based design of a
diagnosis system. Latest version of the toolbox can be downloaded at
faultdiagnosistoolbox.github.io.
Erik Frisk, Mattias Krysander and Daniel Jung
2017
Informationsansvarig: webmaster
Senast uppdaterad: 2021-11-10