Title :
Application of Information Fusion Techniques on Fault Detection and Diagnosis
Author :
Li, Bin ; Zhang, Weiguo
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an
Abstract :
In order to improve the reliability of fault detection and diagnosis (FDD) for material test machine, it is important to make full use of the information from being test material knowledge and material measurements. This paper presents an application of information fusion in FDD. In the proposed method, the fusion adopts multiple FDD strategies aiming at angle signals and torque signals etc. of the system, then the results of these strategies are fused. Through regression analysis on the fused data, the information fusion techniques are showed to be practical and effective
Keywords :
fault diagnosis; regression analysis; sensor fusion; test equipment; angle signal; fault detection reliability; fault diagnosis reliability; information fusion; material measurement; material test machine; regression analysis; test material knowledge; torque signal; Automatic testing; Automation; Automotive materials; Educational institutions; Fault detection; Fault diagnosis; Intelligent sensors; Materials testing; Regression analysis; System testing; fault detection and diagnosis (FDD); information fusion; regression analysis;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714150
