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Rolling Element Bearing Fault Diagnosis Based on Deep Belief Network and Principal Component Analysis

机译：基于深度信仰网络和主成分分析的滚动元件轴承故障诊断

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Guangxing Niu; Bin Zhang; Paul Ziehl; Frank Ferrese; Michael Golda;
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1. Multi-fault diagnosis of rolling bearing using fuzzy entropy of empirical mode decomposition, principal component analysis, and SOM neural network [J] . Zair Mohamed, Rahmoune Chemseddine, Benazzouz Djamel Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science . 2019,第9期

机译：经验模糊熵，主要成分分析和SOM神经网络模糊熵的多故障诊断滚动轴承
2. Rolling bearing fault diagnosis based on intelligent optimized self-adaptive deep belief network [J] . Measurement Science & Technology . 2020,第5期

机译：基于智能优化自适应深度信仰网络的滚动轴承故障诊断
3. Fault diagnosis method of rolling bearing based on deep belief network [J] . Shang Zhiwu, Liao Xiangxiang, Geng Rui, Journal of Mechanical Science and Technology . 2018,第11期

机译：基于深度信仰网络的滚动轴承故障诊断方法
4. Fault Diagnosis Based on Principal Component Analysis and Support Vector Machine for Rolling Element Bearings [C] . Zhicai Zhou, Dongfeng Liu, Xinfa Shi ISKE 2012 . 2014

机译：基于主成分分析的故障诊断和滚动元件轴承的支持向量机
5. Analysis of rolling element bearing faults in rotating machinery: Experiments, modeling, fault detection and diagnosis. [D] . Adams, Michael Louis. 2001

机译：旋转机械中滚动轴承故障的分析：实验，建模，故障检测和诊断。
6. Rolling-Element Bearing Fault Diagnosis Using Improved LeNet-5 Network [O] . Lanjun Wan, Yiwei Chen, Hongyang Li, 2020

机译：使用改进的LeNet-5网络的滚动轴承故障诊断
7. Input Feature Mappings-Based Deep Residual Networks for Fault Diagnosis of Rolling Element Bearing With Complicated Dataset [O] . Liangsheng Hou, Ruizheng Jiang, Yanghui Tan, 2020

机译：基于输入特征映射的滚动元件轴承故障诊断的深度残余网络

Rolling Element Bearing Fault Diagnosis Based on Deep Belief Network and Principal Component Analysis

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