Title: Sensor fault detection in nonlinear system using threshold estimation

Authors: Nora Kacimi; Said Grouni; Youcef Soufi; Samir Ladjouzi; Mohamed Seghir Boucherit

Addresses: Process Control Laboratory, National Polytechnic School, BP 182, El-Harrach, Alger, Algeria ' LAA, Laboratory of Applied Automatic, University of Boumerdes, 35000, Boumerdes, Algeria ' Department of Electrical Engineering, Faculty of Sciences and Technology, University of Tebessa, Route de Constantine, 12002, Tebessa, Algeria ' LAA, Laboratory of Applied Automatic, University of Boumerdes, 35000, Boumerdes, Algeria ' Process Control Laboratory, National Polytechnic School, BP 182, El-Harrach, Alger, Algeria

Abstract: In this paper, an advanced study of fault diagnosis using real data signal system. This study is online and fast application for fault diagnosis sensors. The diagnosis involves two steps respectively: fault detection and fault localisation. An online fault detection approach for an experimental three tanks system is developed. This approach is based on real time signal and statistical analysis. We used the standard deviation and the mean value of several independent experimental repeated in the normal state and under the same conditions for estimating the threshold of fault detection. Then, the acquisition of signal data test in real time is used to validate this threshold estimation. Also, in this research work, a proposed technique of fault detection is implemented and validated experimentally in prototype of three tanks laboratory.

Keywords: fault detection; statistical analysis; adaptive threshold; fault sensor; three tanks system.

DOI: 10.1504/IJDSSS.2017.090281

International Journal of Digital Signals and Smart Systems, 2017 Vol.1 No.4, pp.336 - 347

Received: 13 Apr 2017
Accepted: 22 Jun 2017
Published online: 08 Mar 2018 *

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