Publications (11)
SMTNet: Hierarchical cavitation intensity recognition based on sub-main transfer network
Yu Sha, Johannes Faber, Shuiping Gou +9
With the rapid development of smart manufacturing, data-driven machinery health management has been of growing attention. In situations where some classes are more difficult to be…
Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space
Yu Sha, Johannes Faber, Shuiping Gou +9
Anomalous sound detection (ASD) is one of the most significant tasks of mechanical equipment monitoring and maintaining in complex industrial systems. In practice, it is vital to p…
An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering
Yu Sha, Johannes Faber, Shuiping Gou +9
Valves are widely used in industrial and domestic pipeline systems. However, during their operation, they may suffer from the occurrence of the cavitation, which can cause loud noi…
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design
Xujie Zhang, Yu Sha, Michael C. Kampffmeyer +5
Cross-modal fashion image synthesis has emerged as one of the most promising directions in the generation domain due to the vast untapped potential of incorporating multiple modali…
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…
A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals
Yu Sha, Johannes Faber, Shuiping Gou +9
With the rapid development of smart manufacturing, data-driven machinery health management has received a growing attention. As one of the most popular methods in machinery health…