机译:基于半监督核边缘Fisher分析的特征提取及其在轴承故障诊断中的应用
State Key Laboratory for Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China ,School of Mechanical Science and Engineering Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China;
State Key Laboratory for Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China ,School of Mechanical Science and Engineering Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China;
State Key Laboratory for Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China ,School of Mechanical Science and Engineering Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China;
Fault diagnosis; Semi-supervised kernel Marginal Fisher; analysis; Feature extraction; Dimensionality reduction; Manifold learning;
机译:改进的核边界Fisher分析在特征提取中的应用及其在轴承故障诊断中的应用
机译:基于经验模态分解和核函数的轴承故障诊断深度特征提取方法
机译:基于核函数和自动编码器的轴承故障诊断深度特征提取增强方法
机译:基于正则核心边缘Fisher分析的滚动轴承智能故障诊断方法
机译:小波分析的特征提取及其在机械故障诊断中的应用。
机译:基于视觉传感器数据的新型半监督特征提取方法及其在汽车装配故障诊断中的应用
机译:基于经验模式分解和内核函数的轴承故障诊断深度特征提取方法