Int. J. of Digital Signals and Smart Systems   »   2017 Vol.1, No.4

 

 

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.2017.10011017

 

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

 

Submission date: 10 Apr 2017
Date of acceptance: 22 Jun 2017
Available online: 09 Feb 2018

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article