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Keywords = multi-parameter fusion health index (MFHI)

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21 pages, 7644 KB  
Article
State Estimation and Remaining Useful Life Prediction of PMSTM Based on a Combination of SIR and HSMM
by Guishuang Tian, Shaoping Wang, Jian Shi and Yajing Qiao
Sustainability 2022, 14(24), 16810; https://doi.org/10.3390/su142416810 - 14 Dec 2022
Cited by 1 | Viewed by 2885
Abstract
The permanent magnet synchronous traction motor (PMSTM) is the core equipment of urban rail transit. If a PMSTM fails, it will cause serious economic losses and casualties. It is essential to estimate the current health state and predict remaining useful life (RUL) for [...] Read more.
The permanent magnet synchronous traction motor (PMSTM) is the core equipment of urban rail transit. If a PMSTM fails, it will cause serious economic losses and casualties. It is essential to estimate the current health state and predict remaining useful life (RUL) for PMSTMs. Directly obtaining the internal representation of a PMSTM is known to be difficult, and PMSTMs have long service lives. In order to address these drawbacks, a combination of SIR and HSMM based state estimation and RUL prediction method is introduced with the multi-parameter fusion health index (MFHI) as the performance indicator. The proposed method’s advantages over the conventional HSMM method were verified through simulation research and examples. The results show that the proposed state estimation method has small error distribution results, and the RUL prediction method can obtain accurate results. The findings of this study demonstrate that the proposed method may serve as a new and effective technique to estimate a PMSTM’s health state and RUL. Full article
(This article belongs to the Special Issue Industry 4.0 Technologies for Sustainable Asset Life Cycle Management)
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