DocumentCode :
2726250
Title :
A .NET framework for an integrated fault diagnosis and failure prognosis architecture
Author :
Chen, Chaochao ; Brown, Douglas ; Sconyers, Chris ; Vachtsevanos, George ; Zhang, Bin ; Orchard, Marcos E.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2010
fDate :
13-16 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a .NET framework as the integrating software platform linking all constituent modules of the fault diagnosis and failure prognosis architecture. The inherent characteristics of the .NET framework provide the proposed system with a generic architecture for fault diagnosis and failure prognosis for a variety of applications. Functioning as data processing, feature extraction, fault diagnosis and failure prognosis, the corresponding modules in the system are built as .NET components that are developed separately and independently in any of the .NET languages. With the use of Bayesian estimation theory, a generic particle-filtering-based framework is integrated in the system for fault diagnosis and failure prognosis. The system is tested in two different applications - bearing spalling fault diagnosis and failure prognosis and brushless DC motor turn-to-turn winding fault diagnosis. The results suggest that the system is capable of meeting performance requirements specified by both the developer and the user for a variety of engineering systems.
Keywords :
Bayes methods; brushless DC motors; estimation theory; fault diagnosis; machine bearings; network operating systems; particle filtering (numerical methods); software architecture; .NET language; Bayesian estimation theory; bearing spalling fault diagnosis; brushless DC motor turn to turn winding fault diagnosis; data processing; failure prognosis architecture; feature extraction; generic particle filter; integrated fault diagnosis; Computer architecture; Fault diagnosis; Feature extraction; Graphical user interfaces; Real time systems; Software; Windings; .NET framework; Fault diagnosis; failure prognosis; particle filtering; software architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
AUTOTESTCON, 2010 IEEE
Conference_Location :
Orlando, FL
ISSN :
1088-7725
Print_ISBN :
978-1-4244-7960-3
Type :
conf
DOI :
10.1109/AUTEST.2010.5613626
Filename :
5613626
Link To Document :
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