To read the full version of this content please select one of the options below:

An efficient FDIR strategy on nonlinear processes of self-validating multifunctional sensors

Jingli Yang (Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China)
Zhen Sun (Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China)
Yinsheng Chen (Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 19 June 2017

Abstract

Purpose

This paper aims to enhance the reliability of self-validating multifunctional sensors.

Design/methodology/approach

An effective fault detection, isolation and data recovery (FDIR) strategy by using kernel principal component analysis (KPCA) coupled with gray bootstrap and fault reconstruction methods.

Findings

The proposed FDIR strategy is able to the address fault detection, isolation and data recovery problem of self-validating multifunctional sensors efficiently.

Originality/value

A KPCA-based model which can overcome the limitation of existing linear-based models is used to achieve the fault detection task. By using gray bootstrap method, the position of all faulty sensitive units can be calculated even under the multiple faults situation. A reconstruction-based contribution method is adopted to evaluate the amplitudes of the fault signals, and the fault-free output of the faulty sensitive units can be used to replace the fault output.

Keywords

Acknowledgements

This work is supported by the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 2017014). The authors would like to thank the editors and the reviewers for their helpful comments.

Citation

Yang, J., Sun, Z. and Chen, Y. (2017), "An efficient FDIR strategy on nonlinear processes of self-validating multifunctional sensors", Sensor Review, Vol. 37 No. 3, pp. 223-236. https://doi.org/10.1108/SR-08-2016-0138

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited