4 papers
Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis
Yu Sha, Shuiping Gou, Bo Liu +8
Fault intensity diagnosis (FID) plays a pivotal role in intelligent manufacturing while neglecting dependencies among target classes hinders its practical deployment. This paper in…
Deep learning approaches to extract nuclear deformation parameters from initial-state information in heavy-ion collisions
Jun-Qi Tao, Yang Liu, Yu Sha +5
The deformation of heavy nuclei leaves characteristic imprints on the initial conditions of relativistic heavy-ion collisions. However, event-by-event fluctuations make the quantit…
A Review of Machine Learning for Cavitation Intensity Recognition in Complex Industrial Systems
Yu Sha, Ningtao Liu, Haofeng Liu +10
Cavitation intensity recognition (CIR) is a critical technology for detecting and evaluating cavitation phenomena in hydraulic machinery, with significant implications for operatio…
Hierarchical knowledge guided fault intensity diagnosis of complex industrial systems
Yu Sha, Shuiping Gou, Bo Liu +9
Fault intensity diagnosis (FID) plays a pivotal role in monitoring and maintaining mechanical devices within complex industrial systems. As current FID methods are based on chain o…