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Feature Extraction Using Sparse Kernel Non-Negative Matrix Factorization for Rolling Element Bearing Diagnosis

机译：采用稀疏核非负矩阵因子的特征提取用于滚动元件轴承诊断

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Lin Liang; Xingyun Ding; Fei Liu; Yuanming Chen; Haobin Wen;
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年度 2021
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1. Feature extraction for rolling element bearing fault diagnosis utilizing generalized S transform and two-dimensional non-negative matrix factorization [J] . Li B., Zhang P.-L., Liu D.-S., Journal of Sound and Vibration . 2011,第10期

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2. Fault diagnosis of rolling element bearing compound faults based on sparse no-negative matrix factorization-support vector data description [J] . Wang Hongchao Journal of vibration and control: JVC . 2018,第2期

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3. A weak fault feature extraction of rolling element bearing based on attenuated cosine dictionaries and sparse feature sign search [J] . Zhou Haoxuan, Li Hua, Liu Tao, ISA Transactions . 2020,第期

机译：基于衰减余弦词典和稀疏特征标志搜索的滚动元件轴承弱故障特征提取
4. Simultaneous PET Image Reconstruction and Feature Extraction Method using Non-negative, Smooth, and Sparse Matrix Factorization [C] . Kazuya Kawai, Hidekata Hontani, Tatsuya Yokota, Asia-Pacific Signal and Information Processing Association Annual Summit and Conference . 2018

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5. A fault diagnosis system for rotary machinery supported by rolling element bearings. [D] . Hasanzadeh Ghafari, Shahab. 2007

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7. The Feature Extraction and Recognition of Phone Image Based on Robust Sparse Non-Negative Matrix Factorization [O] . Enjun Yu, Qingwei Ye, Yue Wu 2014

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Feature Extraction Using Sparse Kernel Non-Negative Matrix Factorization for Rolling Element Bearing Diagnosis

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