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Author Wu, Li-Feng ♦ Zheng, Yu ♦ Guan, Yong ♦ Wang, Guo-Hui ♦ Li, Xiao-Juan
Source World Health Organization (WHO)-Global Index Medicus
Content type Text
Publisher Multidisciplinary Digital Publishing Institute
File Format HTM / HTML
Language English
Difficulty Level Medium
Subject Domain (in DDC) Technology ♦ Medicine & health
Abstract Highly reliable embedded systems have been widely applied in the fields of aerospace, nuclear power, high-speed rail, etc., which are related to security and economic development. The reliability of the power supply directly influences the security of the embedded system, and has been the research focus of numerous electronic information and energy studies. The degradation of power modules occupies a dominant position among the key factors affecting the power supply reliability. How to dynamically determine the degradation state and forecast the remaining useful life of working power modules is critical. Therefore, an online non-intrusive method of obtaining the degradation state of MOSFETs based on the Volterra series is proposed. It uses the self-driving signal of MOSFETs as a non-intrusive incentive, and extracts the degradation characteristics of MOSFETs by the frequency-domain kernel of the Volterra series. Experimental results show that the identification achieved by the method agrees well with the theoretical analysis.
Description Country affiliation: China
Author Affiliation: Wu LF ( College of Information Engineering, Capital Normal University, Beijing 100048, China. wooleef@gmail.com.); Zheng Y ( College of Information Engineering, Capital Normal University, Beijing 100048, China. zhengyu.hello@163.com.); Guan Y ( College of Information Engineering, Capital Normal University, Beijing 100048, China. gxy169@sina.com.); Wang GH ( College of Information Engineering, Capital Normal University, Beijing 100048, China. wgh_boy@126.com.); Li XJ ( College of Information Engineering, Capital Normal University, Beijing 100048, China. lixj@mail.cnu.edu.cn.)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Reading ♦ Research ♦ Self Learning
Interactivity Type Expositive
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-01-10
Publisher Place Switzerland
e-ISSN 14248220
Journal Sensors
Volume Number 14
Issue Number 1


Source: WHO-Global Index Medicus