Experimental investigation of different NN approaches for tool wear prediction based on vision system in turning of AISI 1045 steel
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Modeling and Simulation
Link
https://link.springer.com/content/pdf/10.1007/s12008-022-01072-z.pdf
Reference41 articles.
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3. Thakre, A.A., Lad, A.V., Mala, K.: “Measurements of tool wear parameters using machine vision system,” Model. Simul. Eng., vol. pp. 1–10, 2019, doi: (2019). https://doi.org/10.1155/2019/1876489
4. Prabhu, S., Karthik Saran, S., Majumder, D., Siva Teja, P.V.: A Review on Applications of Image Processing in Inspection of Cutting Tool Surfaces. Appl. Mech. Mater. (2015). doi: https://doi.org/10.4028/www.scientific.net/amm.766-767.635
5. Mikołajczyk, T., Nowicki, K., Kłodowski, A., Pimenov, D.Y.: “Neural network approach for automatic image analysis of cutting edge wear,” Mech. Syst. Signal Process., vol. 88, no. October pp. 100–110, 2017, doi: (2016). https://doi.org/10.1016/j.ymssp.2016.11.026
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