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Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals

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Bibliographic Details
Main Authors: Bayu Adhi, Tama, Malinda, Vania, Seungchul, Lee
Format: Book
Language:English
Published: Springer 2023
Subjects:
rotating machinery using vibration signals
Online Access:https://link.springer.com/article/10.1007/s10462-022-10293-3
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8303
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spelling oai:localhost:PNK-83032023-04-25T09:20:11Z Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals Bayu Adhi, Tama Malinda, Vania Seungchul, Lee rotating machinery using vibration signals CC BY Vibration measurement and monitoring are essential in a wide variety of applications. Vibration measurements are critical for diagnosing industrial machinery malfunctions because they provide information about the condition of the rotating equipment. Vibration analysis is considered the most effective method for predictive maintenance because it is used to troubleshoot instantaneous faults as well as periodic maintenance. Numerous studies conducted in this vein have been published in a variety of outlets. This review documents data-driven and recently published deep learning techniques for vibration-based condition monitoring. Numerous studies were obtained from two reputable indexing databases, Web of Science and Scopus. Following a thorough review, 59 studies were selected for synthesis. The selected studies are then systematically discussed to provide researchers with an in-depth view of deep learning-based fault diagnosis methods based on vibration signals. Additionally, a few remarks regarding future research directions are made, including graph-based neural networks, physics-informed ML, and a transformer convolutional network-based fault diagnosis method. 2023-04-25T09:20:11Z 2023-04-25T09:20:11Z 2022 Book https://link.springer.com/article/10.1007/s10462-022-10293-3 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8303 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic rotating machinery using vibration signals
spellingShingle rotating machinery using vibration signals
Bayu Adhi, Tama
Malinda, Vania
Seungchul, Lee
Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
description CC BY
format Book
author Bayu Adhi, Tama
Malinda, Vania
Seungchul, Lee
author_facet Bayu Adhi, Tama
Malinda, Vania
Seungchul, Lee
author_sort Bayu Adhi, Tama
title Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
title_short Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
title_full Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
title_fullStr Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
title_full_unstemmed Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
title_sort recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10462-022-10293-3
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8303
_version_ 1764268032921698304
score 8.891053

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