A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement...

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Bibliographic Details
Main Authors:	Muhammad Sohaib, Cheol-Hong Kim, Jong-Myon Kim
Format:	Article
Language:	English
Published:	MDPI AG 2017-12-01
Series:	Sensors
Subjects:	autoencoders bearing fault diagnosis fault diagnosis fault severity hybrid features multi crack size stacked autoencoders
Online Access:	https://www.mdpi.com/1424-8220/17/12/2876

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