Fault Diagnosis Model for Bearings under Multiple Operating Conditions Based on Feature Parameterization Weighting
Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
As a core component of automobile transmission, rolling bearings play a main role in the safety and reliability of vehicles. Existing diagnostic models often treat all features equally after feature extraction, without effectively distinguishing the importance of fault features, resulting in low accuracy and poor robustness in bearing fault diagnosis. To address this issue, a fault diagnosis model for bearings under multiple operating conditions based on feature parameterization weighting is proposed. The model utilizes a feature parameterization weighting module to categorize faults into two classes based on differences in means and implements different feature processing methods. The experimental results validate that the proposed feature parameterization weighting module effectively improves the diagnostic accuracy of the model by 8.95%. In terms of noise resistance, on two multi-condition datasets, the proposed diagnostic model achieves diagnostic accuracy of 98.79% and 98.36%. The diagnostic accuracy is improved by 15.7% and 22.48%, which indicates that the model has strong anti-noise ability.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Fault Diagnosis Model for Bearings under Multiple Operating Conditions Based on Feature Parameterization Weighting
- Date Crossref
- 31/05/2024
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
-
China Electronic Product Reliability and Environmental Test Institute pays non établi dans la noticeStructure de recherche
-
Ministry of Industry and Information Technology pays non établi dans la noticeOrganisme public
-
Beijing Jiaotong University pays non établi dans la noticeUniversité ou école supérieure
-
China Electronic Product Reliability and Environmental Testing Research Institute pays non établi dans la noticeStructure de recherche
-
Science and Technology on Reliability Physics and Application of Electronic Component Laboratory pays non établi dans la noticeStructure de recherche
-
School of Electrical Engineering pays non établi dans la noticeUniversité ou école supérieure
China Electronic Product Reliability and Environmental Test Institute, Ministry of Industry and Information Technology et Beijing Jiaotong University, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.