Failure Prognosis of Complex Equipment With Multistream Deep Recurrent Neural Network

Volume: 20, Issue: 2
Published: Jan 3, 2020
Abstract
The failure prognosis is crucial for industrial equipment in prognostics and health management field. The vibration signal is the commonly used data for failure prognosis. The conventional prognostic approaches have limitations to handle the features extracted from the vibration signal because of the large data quantity, complex feature relations, and limited degeneration mechanisms. In this paper, a deep learning-based approach is proposed to...
Paper Details
Title
Failure Prognosis of Complex Equipment With Multistream Deep Recurrent Neural Network
Published Date
Jan 3, 2020
Volume
20
Issue
2
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