Tool Wear Analysis on Time-Domain and Frequency-Domain Data of Machining S45C Using Signal Processing Technique
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-6841-9_7
Reference20 articles.
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4. Chen, T.-H., et al.: Study of sound signal for tool wear monitoring system in micro-milling processes. In: International Manufacturing Science and Engineering Conference (2009)
5. García-Ordás, M.T., et al.: A computer vision approach to analyze and classify tool wear level in milling processes using shape descriptors and machine learning techniques. Int. J. Adv. Manuf. Technol. 90(5), 1947–1961 (2017)
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