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国外文献 > 1.轴承 > 7. 智能方法与计算

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  • 1 2-Steps Approach for Both Rotor and Bearing Faults Identification in Rotating Machines Using Measured Vibration Responses
       利用测得的振动响应识别旋转机械转子和轴承故障的两步法
  • 2 3D Multibody Simulation of Realistic Rolling Bearing Defects for Fault Classifier Development
       用于故障分类器开发的逼真滚动轴承缺陷三维多体仿真
  • 3 A Batch-normalized Deep Neural Networks and its application in bearing fault diagnosis
       批归一化深度神经网络及其在轴承故障诊断中的应用
  • 4 A Bearing Fault Diagnosis Method Based on Branch Convolution Neural Network
       基于分支卷积神经网络的轴承故障诊断方法
  • 5 A Bearing Fault Diagnosis Method Based on L1 Regularization Transfer Learning and LSTM Deep Learning
       基于L1正则化迁移学习与LSTM深度学习的轴承故障诊断方法
  • 6 A Bearing Fault Diagnosis Method Based on Multimodal Attention Feature Fusion
       基于多模态注意力特征融合的轴承故障诊断方法
  • 7 A BEARING FAULT DIAGNOSIS METHOD BASED ON VGG SENET-BIGRU GLOBAL ATTENTION
       基于VGG SENET-BIGRU全局注意力的轴承故障诊断方法
  • 8 A Bearing Fault Diagnosis Method with Unsupervised Deep Adaptive Network
       基于无监督深度自适应网络的轴承故障诊断方法
  • 9 A BROAD TRANSFER LEARNING ALGORITHM FOR CLASSIFICATION OF BEARING FAULTS
       轴承故障分类的广义转移学习算法
  • 10 A Capsule Network with Deep Convolution Generative Adversarial Network Model for Rolling Bearing Fault Diagnosis
       基于深度卷积生成对抗网络的胶囊网络滚动轴承故障诊断模型
  • 11 A Channel Attention based Large Kernel Convolutional Neural Network for Bearing Fault Diagnosis
       基于通道注意力的大核卷积神经网络用于轴承故障诊断
  • 12 A Channel Attention based Large Kernel Convolutional Neural Network for Bearing Fault Diagnosis
       基于通道注意力的大核卷积神经网络用于轴承故障诊断
  • 13 A class-level matching unsupervised transfer learning network for rolling bearing fault diagnosis under various working conditions
       一种适用于不同工况下滚动轴承故障诊断的类级匹配无监督迁移学习网络
  • 14 A CNN-based Method for Multisensor and Multiscale Fault Diagnosis of Marine Electric Thruster Bearings under Noise Conditions
       基于CNN的多传感器与多尺度噪声条件下船舶电动推进器轴承故障诊断方法
  • 15 A comparative Analysis of 1D Convolutional Neural Networks for Bearing Fault Diagnosis
       一维卷积神经网络在轴承故障诊断中的比较分析
  • 16 A Comparative Study Between Bayesian Filters and Autoencoder Networks for Bearing RUL Prediction
       贝叶斯滤波器与自编码器网络在轴承剩余使用寿命预测中的比较研究
  • 17 A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features
       基于Kullback-Leibler发散选择特征的核-支持向量机在滚动轴承故障分类中的比较研究
  • 18 A comparative study of tribological and mechanical properties of composite polymer coatings on bearing steel
       复合聚合物涂层在轴承钢上的摩擦学与力学性能比较研究
  • 19 A Comparison of Deep Transfer Learning Methods on Bearing Fault Detection
       深度迁移学习方法在轴承故障检测中的比较
  • 20 A convolutional neural network based degradation indicator construction and health prognosis using bidirectional long short-term memory network for rolling bearings
       基于卷积神经网络的滚动轴承劣化指标构建与健康预测：采用双向长短期记忆网络
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