Can I read A Review on Deep Learning Based Condition Monitoring and Fault Diagnosis of Rotating Machinery on EtoBox?

A Review on Deep Learning Based Condition Monitoring and Fault Diagnosis of Rotating Machinery by Purushottam Gangsar; Aditya Raj Bajpei; Rajkumar Porwal is a Engineering article available to read on EtoBox.

What is A Review on Deep Learning Based Condition Monitoring and Fault Diagnosis of Rotating Machinery about?

Rotating machine faults are unavoidable; thus, early diagnosis is essential to avoid further damage to the machine or other machine attached to it. Various signal analysis based conventional techniques have been developed and used in the industries to identify various defects in the rotating machines. In last two decades, researchers have shifted their focus to automated or intelligent fault diagnosis based on Artificial Intelligence (AI) techniques due to a variety of issues in conventional fault analysis techniques, such as a dependence on machine operating circumstances, human interference, and expert abilities. In AI based techniques, various machine learning (ML) and deep learning (DL) techniques have been successfully applied for fault diagnosis of various rotating machines. From last half decade DL have been gaining popularity due to its attractive characteristic of automated feature learning and solving big data, unbalanced data, big computational burden and over-fitting problems of conventional ML techniques. Advances in DL methodologies have prompted interest in DL based intelligent fault diagnosis in the industry in the last five to 6 years. This review paper summarizes

Who reads A Review on Deep Learning Based Condition Monitoring and Fault Diagnosis of Rotating Machinery?

Author

Purushottam Gangsar; Aditya Raj Bajpei; Rajkumar Porwal

Publisher

SAGE Publications

Published

2022

Language

EN

Field

Engineering (Physical Sciences)