Underdetermined Source Separation of Bearing Faults Based on Optimized Intrinsic Characteristic-Scale Decomposition and Local Non-Negative Matrix Factorization

Underdetermined Source Separation of Bearing Faults Based on Optimized Intrinsic Characteristic-Scale Decomposition and Local Non-Negative Matrix Factorization

Since roller bearing is one of the most vulnerable components, bearing faults usually occur in an unprepared situation with multiple faults, and the quantity of sensors is limited in the real-time working environment, resulting in an underdetermined blind source separation (UBSS) problem to extract...

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Bibliographic Details
Main Authors: Yansong Hao, Liuyang Song, Mengyang Wang, Lingli Cui, Huaqing Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Local non-negative matrix factorization
underdetermined blind source separation
optimized intrinsic characteristic-scale decomposition
Online Access:https://ieeexplore.ieee.org/document/8610086/

Internet

https://ieeexplore.ieee.org/document/8610086/

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