Abstract
The paper illustrates the design and the implementation of a Fault Detection and Isolation (FDI) system to a rotary machine like a multishaft centrifugal compressor. A model-free approach, that is, the Principal Component Analysis (PCA), has been employed to solve the fault detection issue. For the fault isolation purpose structured residuals have been adopted while an adaptive threshold has been designed in order to detect and to isolate the faults. To prove the goodness of the proposed FDI system, historical data of a nitrogen centrifugal compressor employed in a refinery plant are considered. Tests results show that detection and isolation of single as well as multiple faults are successfully achieved.
Highlights
In oil and gas plants many processes such as refinery, natural gas extraction/compression, energy production, and gasification, involve the use of rotary machines like centrifugal pumps, turbines, and centrifugal compressors
Dealing with other rotary machines, various works can be found in the literature to diagnose possible faults on centrifugal compressor: in [9] the authors suggest using the time series analysis with neural network to realize a fault diagnosis system for monitoring a centrifugal compressor; in [10] the monitoring of the bearing temperature employed in a centrifugal compressor has been achieved
A Fault Diagnosis system for the detection and the isolation of expected faults of a rotary machine based on the Principle Components Analysis technique has been developed
Summary
In oil and gas plants many processes such as refinery, natural gas extraction/compression, energy production, and gasification, involve the use of rotary machines like centrifugal pumps, turbines, and centrifugal compressors. Dealing with other rotary machines, various works can be found in the literature to diagnose possible faults on centrifugal compressor: in [9] the authors suggest using the time series analysis with neural network to realize a fault diagnosis system for monitoring a centrifugal compressor; in [10] the monitoring of the bearing temperature employed in a centrifugal compressor has been achieved. Other authors suggested using a PCA technique for industrial plant applications: in [16] the authors use the PCA to detect possible faults on Tennessee Eastman (TE) Process while Bezergianni and Kalogianni in [17] propose the PCA approach on a hydrotreating process.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
