Affiliation:
1. Marine Maintenance Department, Gdynia Maritime University, Morska, POLAND
Abstract
Nowadays acoustic emission (AE) method is used in many fields of science, including in thediagnosis and monitoring of machining processes such as turning, grinding, milling, etc. Monitoring of millingprocess allows to ensure stable conditions of treatment. Stable conditions of milling process have a great impacton the quality of the surface. There are different methods used for monitoring machining processes, i.e.dynamometer methods, thermography, vibrations measurement, acoustic emission, etc. The research wascarried out on a universal FUW3157 III milling machine using end mills made of HSS. Tools were in differentstages of wear. The research was carried out at constant rotational speed and variable other cutting parameters,i.e. feed, depth of cut. Milling process was performed on a sheet made of EN AW-7020 aluminium alloy. Themilling process was monitored by an acoustic emission set made by Physical Acoustics Corporation (PAC).The PAC system consists of: preamplifier USB AE Node, type 1283 with bandpass 20 kHz – 1 MHz, AE signalmeasurement sensor type VS 150M, with a frequency range 100 – 450 kHz, computer with AE Win for USBVersion E5.30 software for recording and analysing AE data. During the study, the acoustic emission signalsgenerated during milling process were recorded and then chosen parameters were analyzed e. g.: amplitude,number of events - hits, the effective value of the signal (RMS). The study can be the basis for the use ofacoustic emission method for monitoring milling process and determining the parameters to ensure stableconditions of that process and the same to obtain a high quality surface
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
Subject
Artificial Intelligence,General Mathematics,Control and Systems Engineering
Reference19 articles.
1. W. Labuda, The Influence of Treatments Conditions on Cutting Forces and Temperature during Finish Turning of Stainless Steel by CCET09T302R-MF. In Proceedings of 27th Anniversary International Conference on Metallurgy and Materials. Ostrava, Czech Republic, 2018, pp. 1163 – 1168.
2. W. Labuda, The Influence of Cutting Parameters on Cutting Forces and Surface Roughness, Journal of KONES Powertrain and Transport; Vol. 21, No. 3, 2014, pp. 199-204.
3. A. Matras, W. Zębala, Optimization of Cutting Data and Tool Inclination Angles During Hard Milling with CBN Tools, Based on Force Predictions and Surface Roughness Measurements, Materials, Vol. 13, 1109, 2020.
4. A.V. Filippov, A. Y. Nikonov, V. E. Rubtsov, A. I. Dmitriev, S. Tarasov, Vibration and Acoustic Emission Monitoring the Stability of Peakless Tool Turning: Experiment and Modelling, Journal of Materials Processing Technology, Vol. 246, 2017, pp. 224-234.
5. V. Balsamo, A. Caggiano, K. Jemielniak, J. Kossakowska, M. Nejman, R. Teti, Multi Sensor Signal Processing for Catastrophic Tool Failure Detection in Turning, In Research and Innovation in Manufacturing: Key enabling technologies for the factories of the future - Proceedings of the 48th CIRP Conference On Manufacturing Systems, Vol. 41, Ischia, Italy, 2016,pp. 939-944.
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3 articles.
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