TITLE:
Fault Detection and Isolation in Industrial Systems Based on Spectral Analysis Diagnosis
AUTHORS:
Ahmed Hafaifa, Mouloud Guemana, Attia Daoudi
KEYWORDS:
Diagnosis; Spectral Analyzes; Faults Detection and Isolation; Condition Monitoring
JOURNAL NAME:
Intelligent Control and Automation,
Vol.4 No.1,
February
6,
2013
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.