The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process

Condition monitoring of the cutting process is a core function of autonomous machining and its success strongly relies on sensed data. Despite the enormous amount of research conducted so far into condition monitoring of the cutting process, there are still limitations given the complexity underlini...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rui Silva, António Araújo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	condition monitoring tool wear non-linearity time series sensors cutting process Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/5b5f8b8275c9405a8089be72b40f5792
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:5b5f8b8275c9405a8089be72b40f5792
record_format	dspace
spelling	oai:doaj.org-article:5b5f8b8275c9405a8089be72b40f57922021-11-25T18:12:11ZThe Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process10.3390/machines91102702075-1702https://doaj.org/article/5b5f8b8275c9405a8089be72b40f57922021-11-01T00:00:00Zhttps://www.mdpi.com/2075-1702/9/11/270https://doaj.org/toc/2075-1702Condition monitoring of the cutting process is a core function of autonomous machining and its success strongly relies on sensed data. Despite the enormous amount of research conducted so far into condition monitoring of the cutting process, there are still limitations given the complexity underlining tool wear; hence, a clearer understanding of sensed data and its dynamical behavior is fundamental to sustain the development of more robust condition monitoring systems. The dependence of these systems on acquired data is critical and determines the success of such systems. In this study, data is acquired from an experimental setup using some of the commonly used sensors for condition monitoring, reproducing realistic cutting operations, and then analyzed upon their deterministic nature using different techniques, such as the Lyapunov exponent, mutual information, attractor dimension, and recurrence plots. The overall results demonstrate the existence of low dimensional chaos in both new and worn tools, defining a deterministic nature of cutting dynamics and, hence, broadening the available approaches to tool wear monitoring based on the theory of chaos. In addition, recurrence plots depict a clear relationship to tool condition and may be quantified considering a two-dimensional structural measure, such as the semivariance. This exploratory study unveils the potential of non-linear dynamics indicators in validating information strength potentiating other uses and applications.Rui SilvaAntónio AraújoMDPI AGarticlecondition monitoringtool wearnon-linearitytime seriessensorscutting processMechanical engineering and machineryTJ1-1570ENMachines, Vol 9, Iss 270, p 270 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	condition monitoring tool wear non-linearity time series sensors cutting process Mechanical engineering and machinery TJ1-1570
spellingShingle	condition monitoring tool wear non-linearity time series sensors cutting process Mechanical engineering and machinery TJ1-1570 Rui Silva António Araújo The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
description	Condition monitoring of the cutting process is a core function of autonomous machining and its success strongly relies on sensed data. Despite the enormous amount of research conducted so far into condition monitoring of the cutting process, there are still limitations given the complexity underlining tool wear; hence, a clearer understanding of sensed data and its dynamical behavior is fundamental to sustain the development of more robust condition monitoring systems. The dependence of these systems on acquired data is critical and determines the success of such systems. In this study, data is acquired from an experimental setup using some of the commonly used sensors for condition monitoring, reproducing realistic cutting operations, and then analyzed upon their deterministic nature using different techniques, such as the Lyapunov exponent, mutual information, attractor dimension, and recurrence plots. The overall results demonstrate the existence of low dimensional chaos in both new and worn tools, defining a deterministic nature of cutting dynamics and, hence, broadening the available approaches to tool wear monitoring based on the theory of chaos. In addition, recurrence plots depict a clear relationship to tool condition and may be quantified considering a two-dimensional structural measure, such as the semivariance. This exploratory study unveils the potential of non-linear dynamics indicators in validating information strength potentiating other uses and applications.
format	article
author	Rui Silva António Araújo
author_facet	Rui Silva António Araújo
author_sort	Rui Silva
title	The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
title_short	The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
title_full	The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
title_fullStr	The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
title_full_unstemmed	The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process
title_sort	deterministic nature of sensor-based information for condition monitoring of the cutting process
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5b5f8b8275c9405a8089be72b40f5792
work_keys_str_mv	AT ruisilva thedeterministicnatureofsensorbasedinformationforconditionmonitoringofthecuttingprocess AT antonioaraujo thedeterministicnatureofsensorbasedinformationforconditionmonitoringofthecuttingprocess AT ruisilva deterministicnatureofsensorbasedinformationforconditionmonitoringofthecuttingprocess AT antonioaraujo deterministicnatureofsensorbasedinformationforconditionmonitoringofthecuttingprocess
_version_	1718411499252219904

The Deterministic Nature of Sensor-Based Information for Condition Monitoring of the Cutting Process

Ejemplares similares