Robust wheel wear detection for solid carbide grinding under strong noise interference: A new approach based on improved ensemble noise-reconstructed empirical mode decomposition
Sign Up to like & getrecommendations! Published in 2021 at "Wear"
DOI: 10.1016/j.wear.2021.204112
Abstract: Abstract Wheel wear detection is of great importance to achieve the desired surface quality and productivity in solid carbide grinding, while the Hilbert–Huang transform composed of empirical mode decomposition (EMD) and Hilbert transform is widely… read more here.
Keywords: wear detection; wheel wear; mode; noise ... See more keywords
Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Sports Sciences"
DOI: 10.1080/02640414.2019.1703301
Abstract: ABSTRACT Detection of non-wear periods is an important step in accelerometer data processing. This study evaluated five non-wear detection algorithms for wrist accelerometer data and two rules for non-wear detection when non-wear and sleep algorithms… read more here.
Keywords: wear detection; non; accelerometer data; non wear ... See more keywords