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Distributed model-based nonlinear sensor fault diagnosis in wireless sensor networks.
- Source :
-
Mechanical Systems & Signal Processing . Jan2016, Vol. 66/67, p470-484. 15p. - Publication Year :
- 2016
-
Abstract
- Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies nonlinear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is presented for detecting common non-linearity faults without using reference sensors. The study introduces a model-based fault diagnosis framework that is implemented within a pair of wireless sensors. The detection of sensor nonlinearities is shown to be equivalent to solving the largest empty rectangle (LER) problem, given a set of features extracted from an analysis of sensor outputs. A low-complexity algorithm that gives an approximate solution to the LER problem is proposed for embedment in resource constrained wireless sensors. By solving the LER problem, sensors corrupted by non-linearity faults can be isolated and identified. Extensive analysis evaluates the performance of the proposed algorithm through simulation. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08883270
- Volume :
- 66/67
- Database :
- Academic Search Index
- Journal :
- Mechanical Systems & Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 108824136
- Full Text :
- https://doi.org/10.1016/j.ymssp.2015.05.011