Fault Diagnosis

Fault diagnosis aims to identify and locate malfunctions in complex systems, improving safety and efficiency. Current research emphasizes developing robust and efficient methods, focusing on deep learning architectures like convolutional neural networks, transformers, and graph neural networks, often incorporating techniques such as transfer learning, domain adaptation, and knowledge distillation to handle data scarcity, noise, and varying operating conditions. These advancements are crucial for various applications, including industrial maintenance, process control, and healthcare, enabling proactive interventions and reducing downtime.