A multi-model method to fault detection and diagnosis: Bayesian solution. An introductory treatise
✍ Scribed by Luděk Berec
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 167 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0890-6327
No coin nor oath required. For personal study only.
✦ Synopsis
In the paper, a method for solving fault detection and diagnosis problems in sampled-data stochastic systems is presented. As a main methodology tool the Bayesian view on uncertainty is exploited. The method can be classified as of a multi-model type. It requires to supply mathematical models of the system dynamics, each describing the situation when a particualr fault separately acts on the system or when the system behaves normally (i.e. as desired). At the stage of research, discrete-time stochastic causal input-output non-parametrized models are supported.
As discrete-time courses, model of the actual system behaviour is recursively estimated and a decision on the actually acting fault is given. The presented method solves both the fault detection and diagnosis tasks simultaneously. Three illustrative examples show the method in action, possibly demonstrating a range of its applications.