Volume 37, Issue 3, October 2022, Pages 659–672
Jean Claude Mukaz Ilunga1, Dany Katamba Mpoyi2, Chritian Katayi3, and Moise Ngoyi Kasanji4
1 Institut Supérieur de Techniques Appliquées, Kinshasa, RD Congo
2 Université Pédagogique Nationale, Kinshasa, RD Congo
3 Mechanics, High Institute of Applied Techniques, Kinshasa, RD Congo
4 Electronics, High Institute of Applied Techniques, Kinshasa, RD Congo
Original language: English
Copyright © 2022 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this work, it is a question of the cutting tool wear monitoring in mechanical turning. We did this monitoring in three phases which correspond to the life of our tool. To achieve this objective of improving monitoring, we have used a processing method (EMD) that breaks down a large signal into small signals (IMFs). The cut up or processed signals are yet applied in the temporal (RMS) and frequency (Spectrum) indicators in order to monitor the evolution of the tool in relation to its degradation and to check the reliability of the indicators. The obtained results will be optimized in an on-line monitoring system and incorporated into a microcontroller dealing with its three phases, in order to make the comparison of informations each time they are generated by the machine.
Author Keywords: mechanical turning, vibratory analysis, wear, EMD, IMF, monitoring, sieving, indicators.
Jean Claude Mukaz Ilunga1, Dany Katamba Mpoyi2, Chritian Katayi3, and Moise Ngoyi Kasanji4
1 Institut Supérieur de Techniques Appliquées, Kinshasa, RD Congo
2 Université Pédagogique Nationale, Kinshasa, RD Congo
3 Mechanics, High Institute of Applied Techniques, Kinshasa, RD Congo
4 Electronics, High Institute of Applied Techniques, Kinshasa, RD Congo
Original language: English
Copyright © 2022 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In this work, it is a question of the cutting tool wear monitoring in mechanical turning. We did this monitoring in three phases which correspond to the life of our tool. To achieve this objective of improving monitoring, we have used a processing method (EMD) that breaks down a large signal into small signals (IMFs). The cut up or processed signals are yet applied in the temporal (RMS) and frequency (Spectrum) indicators in order to monitor the evolution of the tool in relation to its degradation and to check the reliability of the indicators. The obtained results will be optimized in an on-line monitoring system and incorporated into a microcontroller dealing with its three phases, in order to make the comparison of informations each time they are generated by the machine.
Author Keywords: mechanical turning, vibratory analysis, wear, EMD, IMF, monitoring, sieving, indicators.
How to Cite this Article
Jean Claude Mukaz Ilunga, Dany Katamba Mpoyi, Chritian Katayi, and Moise Ngoyi Kasanji, “The empirical mode decomposition (EMD) application for the monitoring of the cutting tools wear,” International Journal of Innovation and Applied Studies, vol. 37, no. 3, pp. 659–672, October 2022.
