Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring
Tool condition monitoring systems are essential in micromilling applications. A tool's slenderness requires high-precision monitoring systems for online measurements. In most cases, tool health is indirectly estimated by processing and analyzing the cutting process parameters. In that sense, th...
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doaj-deb4797ff8fc47168de94f388812f4d42021-03-29T20:38:16ZengIEEEIEEE Access2169-35362018-01-0166400641010.1109/ACCESS.2018.27970038267054Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition MonitoringJuan C. Jauregui0Juvenal R. Resendiz1https://orcid.org/0000-0001-8598-5600Suresh Thenozhi2Tibor Szalay3Adam Jacso4Marton Takacs5Faculty of Engineering, Autonomous University of Queretaro, Santiago de Queretaro, MexicoFaculty of Engineering, Autonomous University of Queretaro, Santiago de Queretaro, MexicoFaculty of Engineering, Autonomous University of Queretaro, Santiago de Queretaro, MexicoFaculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, HungaryFaculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, HungaryFaculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, HungaryTool condition monitoring systems are essential in micromilling applications. A tool's slenderness requires high-precision monitoring systems for online measurements. In most cases, tool health is indirectly estimated by processing and analyzing the cutting process parameters. In that sense, the main challenge lies in the proper selection of the process parameters and their processing techniques, so that a robust and accurate assessment of the tool's health is obtained. This paper proposes a frequencyand time-frequency-based analysis of cutting force and vibration signals for estimating the tool condition of a high-speed micromilling process. Measurements obtained from different cutting conditions were utilized in the analysis. The results indicate variations in the dominant frequencies, which result from tool wear. Furthermore, it is important to note that the analysis results obtained from the two process signals provide more reliable results and improve the sensing bandwidth.https://ieeexplore.ieee.org/document/8267054/Condition monitoringcutting toolsfault detectionmicromachining |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Juan C. Jauregui Juvenal R. Resendiz Suresh Thenozhi Tibor Szalay Adam Jacso Marton Takacs |
spellingShingle |
Juan C. Jauregui Juvenal R. Resendiz Suresh Thenozhi Tibor Szalay Adam Jacso Marton Takacs Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring IEEE Access Condition monitoring cutting tools fault detection micromachining |
author_facet |
Juan C. Jauregui Juvenal R. Resendiz Suresh Thenozhi Tibor Szalay Adam Jacso Marton Takacs |
author_sort |
Juan C. Jauregui |
title |
Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring |
title_short |
Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring |
title_full |
Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring |
title_fullStr |
Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring |
title_full_unstemmed |
Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring |
title_sort |
frequency and time-frequency analysis of cutting force and vibration signals for tool condition monitoring |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
Tool condition monitoring systems are essential in micromilling applications. A tool's slenderness requires high-precision monitoring systems for online measurements. In most cases, tool health is indirectly estimated by processing and analyzing the cutting process parameters. In that sense, the main challenge lies in the proper selection of the process parameters and their processing techniques, so that a robust and accurate assessment of the tool's health is obtained. This paper proposes a frequencyand time-frequency-based analysis of cutting force and vibration signals for estimating the tool condition of a high-speed micromilling process. Measurements obtained from different cutting conditions were utilized in the analysis. The results indicate variations in the dominant frequencies, which result from tool wear. Furthermore, it is important to note that the analysis results obtained from the two process signals provide more reliable results and improve the sensing bandwidth. |
topic |
Condition monitoring cutting tools fault detection micromachining |
url |
https://ieeexplore.ieee.org/document/8267054/ |
work_keys_str_mv |
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_version_ |
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