Fault Detection and Isolation in Industrial Systems Based on Spectral Analysis Diagnosis

Ahmed Hafaifa, Mouloud Guemana, Attia Daoudi

Electrical Engineering Field, Faculty of Science and Technology, University of Djelfa DZ, Djelfa, Algeria.
Faculty of Science and Technology, University of Medea, Medea, Algeria.

DOI: 10.4236/ica.2013.41006                

Abstract

The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis diagram of time-frequency, in order to make this approach exploitable in the proposed supervision strategy with decision making module. The obtained results, show clearly how to guarantee a reliable and sure exploitation in industrial system, thus allowing better performances at the time of its exploitation on the supervision strategy.

Keywords

Diagnosis; Spectral Analyzes; Faults Detection and Isolation; Condition Monitoring

Conflicts of Interest

The authors declare no conflicts of interest.

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