DocumentCode :
1791901
Title :
Application of weighted gray target theory in health status assessment of electromechanical actuating system
Author :
Xiaoben Lei ; Rong Qi ; Shuwei Li ; Jie Yang ; Dongsheng Zhang
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´an, China
fYear :
2014
fDate :
3-6 Aug. 2014
Firstpage :
408
Lastpage :
412
Abstract :
Aiming at the evaluate problem of electrical actuating system health status, a method based on grey target theory is proposed for the health status assessment of electromechanical actuating system. The fault condition index model is built by using grey target theory, and a quantitative classification problem of the health status is solved by using wavelet packet-grey neural network in the condition of no standard model. At the same time, considering the weight problem of different frequency bands, using grey contribution degree to improve the grey target algorithm, a weighted algorithm based on grey target level is proposed. Simulation results show that grey target theory can evaluate the health status of electromechanical actuating system effectively.
Keywords :
condition monitoring; control engineering computing; electromagnetic actuators; grey systems; neural nets; electrical actuating system health status; electromechanical actuating system; fault condition index model; grey contribution degree; grey target algorithm; grey target level; grey target theory; health status assessment; health status evaluation; quantitative classification problem; wavelet packet-grey neural network; weighted algorithm; weighted gray target theory; Circuit faults; Educational institutions; Indexes; Neural networks; Predictive models; Standards; Wavelet packets; electromechanical actuating system; grey contribution degree; health status; weighted gray target theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4799-3978-7
Type :
conf
DOI :
10.1109/ICMA.2014.6885732
Filename :
6885732
Link To Document :
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