基于改进CNN-GRU网络的多源传感器故障诊断方法

Engineering

• Convolutional Neural Network 100%
• Sensor Data 100%
• Fault Diagnosis 100%
• Simulation Result 25%
• Recurrent Neural Network 25%
• Estimated Value 25%
• Loss Function 25%
• Spatial Characteristic 25%
• Network Training 25%

Chemical Engineering

• Neural Network 100%
• Auxiliaries 25%
• Recurrent Neural Network 25%

Physics

• Convolutional Neural Network 100%
• Neural Network 25%