A Deep Feature Learning Method for Drill Bits Monitoring Using the Spectral Analysis of the Acoustic Signals

A Deep Feature Learning Method for Drill Bits Monitoring Using the Spectral Analysis of the Acoustic Signals

Machine fault diagnosis (MFD) has gained an important enthusiasm since the unfolding of the pattern recognition techniques in the last three decades. It refers to all of the studies that aim to automatically detect the faults on the machines using various kinds of signals that they can generate. The...

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Bibliographic Details
Main Authors: Caleb Vununu, Kwang-Seok Moon, Suk-Hwan Lee, Ki-Ryong Kwon
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Sensors
Subjects:
machine fault diagnosis
sound and acoustic processing
pattern recognition
machine learning
deep convolutional autoencoder
deep learning
smart factory
artificial neural network
Online Access:http://www.mdpi.com/1424-8220/18/8/2634

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http://www.mdpi.com/1424-8220/18/8/2634

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