Weighted K-NN Classification Method of Bearings Fault Diagnosis With Multi-Dimensional Sensitive Features
Research on the intelligent fault diagnosis method of rolling bearing based on laboratory data has made some achievements. However, due to the change of working conditions and the lack of historical data of the same equipment in the actual diagnosis, some methods mostly have problems such as poor ge...
Main Authors: | Qingfeng Wang, Shuai Wang, Bingkun Wei, Wenwu Chen, Yufei Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9380240/ |
Similar Items
-
Comparison of Frontal-Temporal Channels in Epilepsy Seizure Prediction Based on EEMD-ReliefF and DNN
by: Aníbal Romney, et al.
Published: (2020-09-01) -
Monopolar Grounding Fault Location Method of DC Distribution Network Based on Improved ReliefF and Weighted Random Forest
by: Yan Xu, et al.
Published: (2022-10-01) -
Multilabel Feature Selection Using Mutual Information and ML-ReliefF for Multilabel Classification
by: Enhui Shi, et al.
Published: (2020-01-01) -
Induction Motor Fault Classification Based on ROC Curve and t-SNE
by: Chun-Yao Lee, et al.
Published: (2021-01-01) -
A Novel Decentralized Weighted ReliefF-PCA Method for Fault Detection
by: Yinghua Yang, et al.
Published: (2019-01-01)