Fault Prognostics of Micro-Electro-Mechanical Systems Using Particle Filtering^*

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• 作者：Haithem Skima^* ; ^{haithem.skima@femto-st.fr} ; Kamal Medjaher^** ; ^{kamal.medjaher@enit.fr} ; Christophe Varnier^* ; ^{christophe.varnier@femto-st.fr} ; Eugen Dedu^* ; ^{eugen.dedu@femto-st.fr} ; Julien Bourgeois^* ; ^{julien.bourgeois@femto-st.fr} ; Noureddine Zerhouni^* ; ^{noureddine.zerhouni@femto-st.fr}
• 关键词：Prognostics ; health management ; micro-electro-mechanical system ; fault prognostics ; remaining useful life ; particle filter
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：28
• 页码：226-231
• 全文大小：818 K
• 卷排序：49

文摘

This paper presents a hybrid prognostics approach for Micro-Electro-Mechanical Systems (MEMS). The approach relies on two phases: an offline phase for the MEMS and its degradation modeling, and an online phase for its fault prognostics. The proposed approach is applied to a MEMS device consisting in an electro-thermally actuated valve. In the offline phase, an experimental platform is built to validate the obtained nominal behavior model of the targeted MEMS and to get its degradation model. This model represents the drifts in a MEMS physical parameter, which is its compliance. In the online phase, a particle filter algorithm is used to perform online parameters estimation of the derived degradation model and calculate the MEMS remaining useful life. The obtained prognostic results show the effectiveness of the proposed approach.