Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles

The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly imp...

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Autores principales:	Krzysztof Lalik, Filip Wątorek
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	vibrodiagnostics smart sensors augmented reality intelligent systems Technology T
Acceso en línea:	https://doaj.org/article/fcb09428c0cb4e54ac0f321cb454d183
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id	oai:doaj.org-article:fcb09428c0cb4e54ac0f321cb454d183
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spelling	oai:doaj.org-article:fcb09428c0cb4e54ac0f321cb454d1832021-11-25T17:27:26ZPredictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles10.3390/en142276321996-1073https://doaj.org/article/fcb09428c0cb4e54ac0f321cb454d1832021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7632https://doaj.org/toc/1996-1073The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user. The presented platform allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system to determine the technical condition of a wind turbine model monitored by an image processing system that measures frequencies generated by the machine.Krzysztof LalikFilip WątorekMDPI AGarticlevibrodiagnosticssmart sensorsaugmented realityintelligent systemsTechnologyTENEnergies, Vol 14, Iss 7632, p 7632 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	vibrodiagnostics smart sensors augmented reality intelligent systems Technology T
spellingShingle	vibrodiagnostics smart sensors augmented reality intelligent systems Technology T Krzysztof Lalik Filip Wątorek Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
description	The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user. The presented platform allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system to determine the technical condition of a wind turbine model monitored by an image processing system that measures frequencies generated by the machine.
format	article
author	Krzysztof Lalik Filip Wątorek
author_facet	Krzysztof Lalik Filip Wątorek
author_sort	Krzysztof Lalik
title	Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
title_short	Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
title_full	Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
title_fullStr	Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
title_full_unstemmed	Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
title_sort	predictive maintenance neural control algorithm for defect detection of the power plants rotating machines using augmented reality goggles
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/fcb09428c0cb4e54ac0f321cb454d183
work_keys_str_mv	AT krzysztoflalik predictivemaintenanceneuralcontrolalgorithmfordefectdetectionofthepowerplantsrotatingmachinesusingaugmentedrealitygoggles AT filipwatorek predictivemaintenanceneuralcontrolalgorithmfordefectdetectionofthepowerplantsrotatingmachinesusingaugmentedrealitygoggles
_version_	1718412386687254528

Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles

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