<i>D-dCNN</i>: A Novel Hybrid Deep Learning-Based Tool for Vibration-Based Diagnostics

<i>D-dCNN</i>: A Novel Hybrid Deep Learning-Based Tool for Vibration-Based Diagnostics

This paper develops a novel hybrid feature learner and classifier for vibration-based fault detection and isolation (FDI) of industrial apartments. The trained model extracts high-level discriminative features from vibration signals and predicts equipment state. Against the limitations of traditiona...

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Bibliographic Details
Main Authors: Ugochukwu Ejike Akpudo, Jang-Wook Hur
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Energies
Subjects:
parallel learning
vibration monitoring
fault detection and isolation
convolutional neural network
deep neural network
Online Access:https://www.mdpi.com/1996-1073/14/17/5286

Internet

https://www.mdpi.com/1996-1073/14/17/5286

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