most citedAn acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering

34 citations · 74 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD202231 cited

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…

physics.geo-ph20225 cited

Deep Learning-based Small Magnitude Earthquake Detection and Seismic Phase Classification

Wei Li, Yu Sha, Kai Zhou +4

Reliable earthquake detection and seismic phase classification is often challenging especially in the circumstances of low magnitude events or poor signal-to-noise ratio. With impr…

cs.SD202234 cited

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…

physics.geo-ph2021

AWESAM: A Python Module for Automated Volcanic Event Detection Applied to Stromboli

Darius Fenner, Georg Ruempker, Wei Li +5

Many active volcanoes in the world exhibit Strombolian activity, which is typically characterized by relatively frequent mild events and also by rare and much more destructive majo…

physics.geo-ph20214 cited

EPick: Multi-Class Attention-based U-shaped Neural Network for Earthquake Detection and Seismic Phase Picking

Wei Li, Megha Chakraborty, Darius Fenner +5

Earthquake detection and seismic phase picking not only play a crucial role in travel time estimation of body waves(P and S waves) but also in the localisation of the epicenter of…