Fault Detection and Severity Analysis of Servo Valves Using Recurrence Quantification Analysis

Mohsen Samadani, Cedrick A. Kitio Kwuimy, and C. Nataraj
Submission Type: 
Full Paper
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phmc_14_050.pdf1.76 MBSeptember 19, 2014 - 8:54am

This paper presents the application of recurrence plots (RPs)
and recurrence quantification analysis (RQA) in model-based
diagnostics of nonlinear systems. A detailed nonlinear mathematical
model of a servo electro-hydraulic system has been
used to demonstrate the procedure. Two faults have been
considered associated with the servo valve including the increased
friction between spool and sleeve and the degradation
of the permanent magnet of the valve armature. The
faults have been simulated in the system by the variation of
the corresponding parameters in the model and the effect of
these faults on the RPs and RQA parameters has been investigated.
A regression-based artificial neural network has
been finally developed and trained using the RQA parameters
to estimate the original values of the faulty parameters and
identify the severity of the faults in the system.

Publication Year: 
2014
Publication Volume: 
5
Publication Control Number: 
050
Page Count: 
10
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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