Hierarchical model‐based diagnosis applied to spacecraft

Abstract

Purpose

To improve accuracy and efficiency of multi‐fault recognition and localization for large‐scale system such as satellite.

Design/methodology/approach

First, fault propagations of a system are modeled by a digraph, which composes of nodes and arcs. Each arc is associated with information about propagation probability and propagation strength. Then, based on consistency‐based theory and semantic theory of abstractions, hierarchical diagnosis model of a system is built. Finally, according to a two‐way hierarchical diagnosis strategy, two incorporated algorithms are adopted which are the Lagrangian relaxation algorithm and the “method of propagation strength”.

Findings

Hierarchical model can greatly improve efficiency of diagnosis compared with un‐hierarchical one. The combined qualitative and quantitative knowledge can improve fault resolution.

Research limitations/implications

The propagation probability and propagation strength must been known.

Practical implications

The method shows its superiority when it is applied to complex system such as spacecraft.

Originality/value

A novel hierarchical framework for large‐scale system multi‐fault diagnosis, which include some new ideas and algorithm is put forward.

Citation

Ruoming, A., Xingwei, J. and Zhengji, S. (2005), "Hierarchical model‐based diagnosis applied to spacecraft", Aircraft Engineering and Aerospace Technology, Vol. 77 No. 4, pp. 302-306. https://doi.org/10.1108/00022660510606376