Harmonic-based-on analysis to discriminate different mechanical actions involved in the machining of hard-to-cut materials
Author:
Funder
European Commission
Junta de Comunidades de Castilla-La Mancha
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00170-024-13773-8.pdf
Reference37 articles.
1. Peng Y, Song Q, Wang R et al (2024) A tool wear condition monitoring method for non-specific sensing signals. Int J Mech Sci 263:108769. https://doi.org/10.1016/j.ijmecsci.2023.108769
2. Wang Y, Gao G, Zhang K et al (2024) Modelling of tribological behavior and wear for micro-textured surfaces of Ti2AlNb intermetallic compounds machined with multi-dimensional ultrasonic vibration assistance. Tribol Int 191:109167. https://doi.org/10.1016/j.triboint.2023.109167
3. Jiang B, Li F, Zhao P et al (2024) Cross-scale identification method for friction damage on the tool flank of high-feed milling cutter. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-024-13122-9
4. Gao S, Duan X, Zhu K, Zhang Y (2024) Investigation of the tool flank wear influence on cutter-workpiece engagement and cutting force in micro milling processes. Mech Syst Signal Process 209:111104. https://doi.org/10.1016/j.ymssp.2024.111104
5. García-Martínez E, Miguel V, Martínez-Martínez A et al (2022) Optimization of the dry turning process of Ti48Al2Cr2Nb aluminide based on the cutting tool configuration. Materials (Basel) 15:1472. https://doi.org/10.3390/ma15041472
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