Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis

DOI

10.1080/18756891.2016.1175808How to use a DOI?

Keywords

Fault diagnosis; interval-valued belief structures; Dempster-Shafer evidence theory; evidence updating; alarm monitoring

Abstract

Information fusion methods based on Dempster-Shafer evidence theory (DST) have been widely used in fault diagnosis. In DST-based methods, the monitoring information collected from sensors is modeled as multiple pieces of diagnosis evidence in the form of basic belief assignment (BBA), and Dempster’s rule is then used to combine these BBAs to obtain the fused BBA for diagnosis decision making. However, the belief structure with crisp single-valued belief degrees in BBA may be too coarse to truthfully represent detailed fault information. Moreover, Dempster’s rule only uses a static combination process, which is unsuitable for dynamically fusing information collected at different time steps. In order to address these issues, the paper proposes a dynamic diagnosis method based on interval-valued evidential updating. First of all, the diagnosis evidence is constructed as an interval-valued belief structure (IBS), which provides a more informative scheme than BBA to model fault information. Secondly, the proposed evidential updating strategy can generate updated IBS as global diagnosis evidence by updating the previous evidence with the new incoming evidence recursively. Thirdly, the reliability and sensitivity indices are designed to evaluate and compare the performance of the proposed updating strategy with other commonly used strategies. Finally, the effectiveness of the proposed evidential updating strategy is demonstrated through some typical fault experiments of a machine rotor.

Copyright

© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis

Open Access

This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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TY  - JOUR
AU  - Xiaobin Xu
AU  - Zhen Zhang
AU  - Dongling Xu
AU  - Yuwang Chen
PY  - 2016
DA  - 2016/06/01
TI  - Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis
JO  - International Journal of Computational Intelligence Systems
SP  - 396
EP  - 415
VL  - 9
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1175808
DO  - 10.1080/18756891.2016.1175808
ID  - Xu2016
ER  -