Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

Natural Sciences, Computer Science, Physics +16

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

Wěi Zhāng, Gaoliang Peng, Chuanhao Li et al. · Sensors · 2017 · 1.6K citations · Full text

Computing, Computer Science, Artificial Intelligence +16

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

Weihua Li, Ruyi Huang, Jipu Li et al. · Mechanical Systems and Signal Processing · 2021 · 779 citations · Full text

Computing, Computer Science, Industrial Engineering +17

A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

Pinjia Zhang, Yi Du, T.G. Habetler et al. · IEEE Transactions on Industry Applications · 2010 · 694 citations

Engineering, Electrical Engineering, Condition Assessment +16

Physics-Informed Neural Networks with Hard Constraints for Inverse Design

SIAM Journal on Scientific Computing · 2021 · 671 citations

Natural Sciences, Computer Science, Physics +17