Unlocking Dual Utility: 1D-CNN for Milling Tool Health Assessment and Experimental Optimization

Autor: Ghazal Farhani, Srihari Kurukuri, Ryan Myers, Nelson Santos, Mohammed Tauhiduzzaman

Publikováno v: IEEE Access, Vol 12, Pp 105096-105107 (2024)

In a novel application of 1D Convolutional Neural Networks (1D-CNN), this study pioneers a tri-class classification framework for accurately forecasting the Remaining Useful Life (RUL) of milling tools. By harnessing the 1D-CNN’s innate capability

Externí odkaz: https://doaj.org/article/db3cee96598c42ff999ebc20a0a28f7e

Influence of initial texture on mechanical response of AZ31B and ZEK100 Mg sheets

Autor: Srihari Kurukuri, Worswick, M. J., Mishra, R. K., Carter, J. T.

Publikováno v: Scopus-Elsevier

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0de88ddabf1be4cc9925ded4dc0c1952
http://www.scopus.com/inward/record.url?eid=2-s2.0-84893456890&partnerID=MN8TOARS

Rate sensitivity and tension-compression asymmetry in AZ31B magnesium alloy sheet.

Autor: Srihari Kurukuri, Worswick, Michael J., Ghaffari Tari, Dariush, Mishra, Raja K., Carter, Jon T.

Publikováno v: Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences; 5/13/2014, Vol. 372 Issue 2015, p10-10, 1p