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Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory

机译：基于混合分类器集合方法的轴承故障诊断及改进的Dempster-Shafer理论

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Yanxue Wang; Fang Liu; Aihua Zhu;
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1. Fault recognition using an ensemble classifier based on Dempster-Shafer Theory [J] . Pattern Recognition: The Journal of the Pattern Recognition Society . 2020,第期

机译：基于Dempster-Shafer理论的集合分类器的故障识别
2. A multi-step progressive fault diagnosis method for rolling element bearing based on energy entropy theory and hybrid ensemble auto-encoder [J] . Jiang Wei, Zhou Jianzhong, Liu Han, ISA Transactions . 2019,第期

机译：基于能量熵理论和混合集合自动编码器的滚动元件轴承多步逐行故障诊断方法
3. Classifier fusion of vibration and acoustic signals for fault diagnosis and classification of planetary gears based on Dempster-Shafer evidence theory [J] . Meghdad Khazaee, Hojat Ahmadi, Mahmoud Omid, Proceedings of the Institution of Mechanical Engineers, Part E. Journal of Process Mechanical Engineering . 2014,第1期

机译：基于Dempster-Shafer证据理论的振动和声学信号分类器融合，用于行星齿轮的故障诊断和分类
4. A method of multi-classifier combination based on Dempster-Shafer evidence theory and the application in the fault diagnosis [C] . Feng Lv, Ni Du, Hai-Lian Du International Conference on Mechatronics and Intelligent Materials . 2012

机译：基于Dempster-Shafer证据理论的多分类器组合方法及其在故障诊断中的应用
5. A Deep Belief Network Based Approach for Bearing Fault Diagnosis [D] . Akkad, Khaled Mohammad A. 2016

机译：基于轴承故障诊断的深度信仰网络
6. Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory [O] . Yanxue Wang, Fang Liu, Aihua Zhu 2019

机译：基于混合分类器集成和改进的Dempster-Shafer理论的轴承故障诊断
7. A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier [O] . Shenghan Zhou, Silin Qian, Wenbing Chang, 2018

机译：一种基于加权置换熵的新型轴承多故障诊断方法和改进的SVM合奏分类器

Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory

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