Two-stage prediction of machinery fault trend based on deep learning for time series analysis

Xu, HL; Ma, RZ; Yan, L; Ma, ZM

Ma, ZM (corresponding author), Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing 211106, Peoples R China.; Ma, RZ (corresponding author), Univ Massachusetts, Dept Comp Sci, Lowell, MA 01854 USA.

DIGITAL SIGNAL PROCESSING, 2021; 117 ():

Abstract

Fault prediction technology provides a way to reduce the loss caused by equipment failure. Currently, many efforts of failure prediction pay more atte......

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