Degradation Pattern

Degradation pattern research focuses on understanding and predicting how systems deteriorate over time, aiming to optimize maintenance and extend lifespan. Current efforts leverage machine learning, particularly deep learning architectures like convolutional neural networks and recurrent neural networks, often combined with clustering techniques to identify distinct degradation pathways and improve prediction accuracy. This work is crucial for diverse applications, from infrastructure management and battery technology to healthcare and industrial equipment, enabling proactive maintenance, reducing costs, and improving safety and reliability. The integration of physics-informed models with machine learning is a growing trend, enhancing the accuracy and interpretability of degradation predictions.