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Information Fusion-Based Meta-Learning for Few-Shot Fault Diagnosis Under Different Working Conditions
In this article, a novel method called Information Fusion-based Meta-Learning (IFML) is explored for fault diagnosis with few-shot problems under different working conditions.
Tingli Xie, Xufeng Huang, Seung-Kyum Choi
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Multi-Sensor Data Fusion for Rotating Machinery Fault Diagnosis Using Residual Convolutional Neural Network
Diagnosis of mechanical faults in the manufacturing systems is critical for ensuring safety and saving cost. With the development of …
Tingli Xie, Xufeng Huang, Seung-Kyum Choi
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Point-Cloud Neural Network Using Transfer Learning-Based Multi-Fidelity Method for Thermal Field Prediction in Additive Manufacturing
Melt pool modeling is critical for model-based uncertainty quantification (UQ) and quality control in metallic Additive Manufacturing …
Xufeng Huang, Zhen Hu, Tingli Xie, Zhuo Wang, Lei Chen, Qi Zhou
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