Dynamic-Projection-Integrated Particle-Filtering-Based Identification of Friction Characteristic Curve for Train Wheelset on Slipping Fault Condition

This paper proposes a dynamic-projection-integrated particle-filtering-based identification strategy for the friction characteristic curve of a train wheelset under the slipping fault condition. This strategy aims to achieve the identification of the fault friction characteristic curve (FFCC) in the...

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Bibliographic Details
Main Authors: Shicai Yin, Tao Peng, Chao Yang, Chunhua Yang, Weihua Gui, Ling Liu
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Lubricants
Subjects:
Online Access:https://www.mdpi.com/2075-4442/12/2/38
Description
Summary:This paper proposes a dynamic-projection-integrated particle-filtering-based identification strategy for the friction characteristic curve of a train wheelset under the slipping fault condition. This strategy aims to achieve the identification of the fault friction characteristic curve (FFCC) in the early slipping fault stage. First, a multi-dimensional integrated particle-filtering (MDIPF)-based parameters correction method is proposed. The MDIPF constructs an error particle state transition model encompassing multi-dimensional parameters, which integrates inter-particle correlation to facilitate error fusion during the state transition process. Then, a dynamic projection domain (DPD)-based particle refinement method is proposed. The DPD constructed the contraction factors to dynamically fine-tune the particle projection domain. Finally, a multi-level evaluation-based identification method for the FFCC is proposed. And the dynamic-projection-integrated particle-filtering-based identification strategy is validated, which can actualize the rapid and accurate identification of the FFCC.
ISSN:2075-4442