83 citations · 84 across the 2 of their papers we have counts for
2 papers
cs.CE2024★ 83 cited
Physics-Informed Machine Learning for Battery Degradation Diagnostics: A Comparison of State-of-the-Art Methods
Sina Navidi, Adam Thelen, Tingkai Li +1
Monitoring the health of lithium-ion batteries' internal components as they age is crucial for optimizing cell design and usage control strategies. However, quantifying component-l…
cs.LG2023★ 1 cited
An interpretable deep learning method for bearing fault diagnosis
Hao Lu, Austin M. Bray, Chao Hu +2
Deep learning (DL) has gained popularity in recent years as an effective tool for classifying the current health and predicting the future of industrial equipment. However, most DL…