A novel bearing fault diagnosis approach using the Gaussian mixture model and the weighted principal component analysis

Author:

Chaleshtori Amir EshaghiORCID,Aghaie AbdollahORCID

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference42 articles.

1. Adaptive k-sparsity-based weighted lasso for bearing fault detection;Sun;IEEE Sens J,2022

2. Adaptive sparse representation-based minimum entropy deconvolution for bearing fault detection;Sun;IEEE Trans Instrum Meas,2022

3. Data fusion techniques for fault diagnosis of industrial machines: a survey;Eshaghi Chaleshtori;Comput Sci Eng,2022

4. A physics-informed feature weighting method for bearing fault diagnostics;Lu;Mech Syst Signal Process,2023

5. Online bearing fault diagnosis using numerical simulation models and machine learning classifications;Wang;Reliab Eng Syst Saf,2023

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