Condition-aware meta-learning for few-shot fault diagnosis across multiple conditions
Experimental results on Tennessee Eastman processes and Wastewater Treatment Plant demonstrate that the diagnostic performance of KG-CAML outperforms state-of-the-art methods under multiple working conditions and few-shot scenarios significantly.